Optimized Tropical Cyclone Winds From QuikSCAT: A Neural Network Approach

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.