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27 results on '"Fore, Alexander G."'

1. Exploring the Impact of Sea Surface Temperature and Salinity on SMAP Excess Surface Emissivity

Author

Said, Faozi, Jelenak, Zorana, Chang, Paul S., Tang, Wenqing, Fore, Alexander G., Akins, Alexander, and Yueh, Simon H.

Abstract

The soil moisture active passive (SMAP) instrument has been used to infer sea surface wind speed from its brightness temperature measurements. To do so, the SMAP wind speed retrieval process requires the removal of sea surface temperature (sst) and sea surface salinity (sss) impact on brightness temperature. Estimating the so-called excess surface emissivity ( $\Delta {e}$ ), that is the sst normalized difference between the measured brightness temperature of the sea surface and the corresponding brightness temperature of a flat surface, is one way of accomplishing such a task. In this article, we investigate whether SMAP $\Delta {e}$ contains residual dependencies to sst and sss. To do so, v5.0 SMAP brightness temperature measurements, derived by the Jet Propulsion Laboratory, are used. For any fixed numerical weather prediction model wind speed above 15 m/s, down to a 20% decrease in SMAP $\Delta {e}$ is observed as the sst increases from 274 to 304 K. For any fixed wind speed between 8 and 15 m/s, the sst residual dependence is weaker with SMAP $\Delta {e}$ exhibiting a 1%–2% decrease as the sst increases. Below 8 m/s, this pattern becomes prevalent again, when the significant wave height (Hs) is greater than 3.5 m. SMAP $\Delta {e}$ decreases as much as 50% with increasing sss, most notably below 8 and above 15 m/s when Hs is considered. This analysis has also shown that below 8 m/s and for swell dominant seas, a decrease in either sss or sst results in a decrease in SMAP $\Delta {e}$ sensitivity to wind-induced sea surface roughness.

Published
2024
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7. Application of Reflected Global Navigation Satellite System (GNSS-R) Signals in the Estimation of Sea Roughness Effects in Microwave Radiometry

Author

Voo, Justin K, Garrison, James L, Yueh, Simon H, Grant, Michael S, Fore, Alexander G, Haase, Jennifer S, and Clauss, Bryan

Subjects
Oceanography
Abstract

In February-March 2009 NASA JPL conducted an airborne field campaign using the Passive Active L-band System (PALS) and the Ku-band Polarimetric Scatterometer (PolSCAT) collecting measurements of brightness temperature and near surface wind speeds. Flights were conducted over a region of expected high-speed winds in the Atlantic Ocean, for the purposes of algorithm development for salinity retrievals. Wind speeds encountered were in the range of 5 to 25 m/s during the two weeks deployment. The NASA-Langley GPS delay-mapping receiver (DMR) was also flown to collect GPS signals reflected from the ocean surface and generate post-correlation power vs. delay measurements. This data was used to estimate ocean surface roughness and a strong correlation with brightness temperature was found. Initial results suggest that reflected GPS signals, using small low-power instruments, will provide an additional source of data for correcting brightness temperature measurements for the purpose of sea surface salinity retrievals.

Published
2010

10. Evaluating and Extending the Ocean Wind Climate Data Record

Author

Wentz, Frank J., primary, Ricciardulli, Lucrezia, additional, Rodriguez, Ernesto, additional, Stiles, Bryan W., additional, Bourassa, Mark A., additional, Long, David G., additional, Hoffman, Ross N., additional, Stoffelen, Ad, additional, Verhoef, Anton, additional, O'Neill, Larry W., additional, Farrar, J. Tomas, additional, Vandemark, Douglas, additional, Fore, Alexander G., additional, Hristova-Veleva, Svetla M., additional, Turk, F. Joseph, additional, Gaston, Robert, additional, and Tyler, Douglas, additional

Published
2017
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13. SMAP L-Band Passive Microwave Observations Of Ocean Surface Wind During Severe Storms

Author

Yueh, Simon H., Fore, Alexander G., Tang, Wenqing, Hayashi, Akiko, Stiles, Bryan, Reul, Nicolas, Weng, Yonghui, Zhang, Fuqing, Yueh, Simon H., Fore, Alexander G., Tang, Wenqing, Hayashi, Akiko, Stiles, Bryan, Reul, Nicolas, Weng, Yonghui, and Zhang, Fuqing

Abstract

The L-band passive microwave data from the Soil Moisture Active Passive (SMAP) observatory are investigated for remote sensing of ocean surface winds during severe storms. The surface winds of Joaquin derived from the real-time analysis of the Center of Advanced Data Assimilation and Predictability Techniques in the Penn State University support the linear extrapolation of the Aquarius and SMAP Geophysical Model Functions (GMFs) to hurricane force winds. We apply the SMAP and Aquarius GMFs to the retrieval of ocean surface wind vectors from the SMAP radiometer data to take advantage of SMAP’s two-look geometry. The SMAP radiometer wind speeds are compared with the winds from other satellites and numerical weather models for validation. The root-mean-square-difference (RMSD) with WindSat or SSMIS is 1.7 m/s below 20 m/s wind speeds. The RMSD with the ECMWF direction is 18 degrees for wind speeds between 12 and 30 m/s. We find that the correlation is sufficiently high between the maximum wind speeds retrieved by SMAP with 60 km resolution and the best track peak winds estimated by the National Hurricane Center and Joint Typhoon Warning Center to allow them to be estimated by SMAP with a correlation coefficient of 0.8 and an underestimation by 8 to 18 percent on average, which is likely due to the effects of spatial averaging. There is also a very good agreement with the airborne Stepped Frequency Radiometer (SFMR) wind speeds with an average RMSD of 4.6 m/s for wind speeds in the range of 20 to 40 m/s.

Published
2016
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15. Aquarius Scatterometer Calibration

Author

Fore, Alexander G., primary, Neumann, Gregory, additional, Freedman, Adam P., additional, Chaubell, Mario Julian, additional, Tang, Wenqing, additional, Hayashi, Akiko K., additional, and Yueh, Simon H., additional

Published
2015
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17. UAVSAR Polarimetric Calibration

Author

Fore, Alexander G., primary, Chapman, Bruce D., additional, Hawkins, Brian P., additional, Hensley, Scott, additional, Jones, Cathleen E., additional, Michel, Thierry R., additional, and Muellerschoen, Ronald J., additional

Published
2015
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27. Optimized Tropical Cyclone Winds From QuikSCAT: A Neural Network Approach.

Author

Stiles, Bryan W., Danielson, Richard E., Poulsen, W. Lee, Brennan, Michael J., Hristova-Veleva, Svetla, Tsae-Pyng Shen, and Fore, Alexander G.

Subjects
TROPICAL cyclones, WINDS, ARTIFICIAL neural networks, REMOTE sensing, SPACE-based radar
Abstract

We have developed a neural network technique for retrieving accurate 12.5-km resolution wind speeds from Ku-band scatterometer measurements in tropical cyclone conditions including typical rain events in such storms. The method was shown to retrieve accurate wind speeds up to 40 m/s when compared with aircraft reconnaissance data, including GPS dropwindsondes and Stepped-Frequency Microwave Radiometer surface wind speed measurements, and when compared to global best track maximum wind speeds. Wind directions were unchanged from the current (version 3) Jet Propulsion Laboratory (JPL) global wind vector product. The technique removes positive biases with respect to best track winds in the developing phase of tropical cyclones that occurred in the nominal (version 2) JPL QuikSCAT product. The new technique also reduces negative biases with respect to best track wind speeds that occurred in the nominal product (both versions 2 and 3) during the most extreme period of the lifetime of intense storms. The wind regime with the most notable improvement is 20-40 m/s (40-80 kn), with more modest improvement for higher winds and the improvement at lower winds comparable to that achieved previously by the version 3 JPL global rain-corrected product. The net effect of all the wind speed improvements is a much better measurement of storm intensity over time in the new product than what has been previously available. When compared with speed data from aircraft flights in Atlantic hurricanes, the new product exhibited a 1-2-m/s positive overall bias and a 3-m/s mean absolute error. The random error and systematic positive bias in the new scatterometer wind product is similar to that of the Hurricane Research Division H*WIND analyses when aircraft data are available for assimilation. This similarity may be explained by the fact that H*WIND data are used as ground truth to fit the coefficients used by the new technique to map radar measurements to wind speed. The fact that H*WIND was designed to match maximum winds while preserving radial symmetry may explain the overall positive biases that we observe in both H*WIND and the new scatterometer wind product which compared to aircraft reconnaissance data. The new scatterometer product could also be inheriting systematic biases in the presence of rain from H*WIND. Under the most extreme rain conditions, the radar signal from the surface can be lost. In such cases, the technique makes use of measurements in the 87.5-km region comprising the 7 $\times$ 7 neighboring cells around the target 12.5-km wind vector cell. In so doing, we sacrifice resolution in cases where the highest resolution region has no useful measurements. Even so, the most extreme rain conditions can result in reduced accuracy. The new technique has been used to retrieve wind fields for every tropical cyclone of tropical storm force or above that has been observed by QuikSCAT during the period of time from October 1999 to November 2009. The resulting data set has been made available online for use by the tropical cyclone research community. [ABSTRACT FROM PUBLISHER]

Published
2014
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