This paper analyzes the sea surface backward thermal radiation data in the China Sea observed by the mmwave channel of FY3 MWRI, explains the reason for which the analysis method combined with multiple mmwave channels is conducive to wind inversion, uses the complex model of the two-scale randomly rough surface with foam scattering layer to calculate the backward heat emission, analyzes the different response characteristics of the thermal radiation characteristics of each channel with the change of the sea surface wind speed, and establishes the wind speed inversion model applying to the microwave radiometer, achieving better results than in previous studies. The sea surface medium-low wind speed precision standard deviation of new model reaches 1.2 m/s (0 - 15 m/s); the inversion strong wind data are consistent with the island fixed buoys data, and the global sea surface wind speed image schematic diagram is given.
Throughout the world, many measuring methods for the sea surface wind field based on the satellite have been put into use, such as active radar and the common scatterometer (e.g. Seasat, ERS-I and II, ADEOS), and have achieved great success. However, the back scattering properties received by the scatterometer will tend to saturate, due to the influence of the sea surface foam under the high wind conditions, thus the highest operational sea wind speed [
Wind field measurement using passive radiometer has been performed throughout the world. Goodberlet et al. developed the D-matrix algorithm, and carried out relevant research. Studies similar to mmwave imaging have also been performed in China. In Reference 12, Laurence N Connor and Paul S Chang adopted a TMI radiometer containing channel of 10.7 GHz on the TRMM satellite, and achieved a good effect. However, due to the settings of the medium-low latitude orbit of TRMM satellite, it was difficult for the satellite to obtain the global sea surface wind speed, and its wide application is limited. Based on the research of Jin Yaqiu et al., it can be observed that the heat radiation effect received by the microwave radiometer [
In this study, we used the MWRI of the Fengyun-3C meteorological satellite, which has channels of 10.65, 18.7, 23.8, 36.5 and 89 GHz, along with a large number of mmwave bands, including a high frequency channel similar to SSM/I, as well as a 10.7 GHz channel which can pass through the atmosphere [
The basic assumption of the D-matrix arithmetic is that the required physical geography parameters, for example the sea surface wind speed (WS), can be represented as the linear combination of the measured brightness temperatures, i.e. the general type shown in Formula (1):
The variables in Formula (1) are the brightness temperatures, which are related to the selected channels. Coefficients of variables are determined by regression analysis. Based on previous research, this algorithm was corrected once again, and the new model which is fit to be used by MWRI for the sea surface wind speed inversion was established. This model applies to the range of 0 - 15 m/s, i.e.:
It is well known that the global sea surface wind speed is uneven and unsymmetrical, and wind speeds of 95% are mainly concentrated in the range of 2 - 15 m/s [
We adopted the wind field inversion algorithm model shown in Formula (2). 1195, 1162 pieces of data from 2014 were collected through the fitting of the FY3B, C-MWRI and buoy, in order to generate the scatter plot for the MWRI wind speed shown in
By means of analyzing the phenomenon that backward heat radiation tends to saturate as a two-scale randomly rough surface of the sea surface foam layer, according to the different saturation characteristics in each channel, we extracted the wind sample data from recent years, and obtained the wind inversion algorithm using the regression and fitting method. The sea surface will be covered with one layer of crushed foam layer in the case of the strong wind, as shown in
Considering the atmosphere heat radiation, the radiation brightness temperature received by satellite MWRI should be as follows:
where the vertical polarization heat emission rate is:
where the horizontal polarization heat emission rate is:
where the sea surface reflectivity
From
The regression analysis is a statistical analysis method which is used to study the dependency relationship of one random variable Y with another (X) or a set of variable (X1, X2, ・・・, Xk). It requires a large number of data for analysis, must collect the global wind sample (15 - 45 m/s) observed by the MWRI of FY-3C in orbit, and the coefficient can be adjusted slightly according to the channel frequency, sensitivity, etc. Finally, the new wind inversion model applying to MWRI is established.
The regression analysis model is as follows:
where
of
Hereby, we must also consider the selection of the coefficient
Frequency (GHz) | 10.65 | 18.7 | 23.8 | 36.5 | ||
---|---|---|---|---|---|---|
V | H | V | V | V | H | |
Sensitivity (K) | 0.5 | 0.54 | 0.5 | 0.8 | 0.31 | 0.5 |
Calibration precision (K) | 1 | 1 | 1.5 | 2 | 2 | 2 |
Influence coefficient |
variation, and the channel with the greatest difference corresponds to the coefficient with the largest variation. The new model is obtained as follows:
The differences among channel frequency
For the monochromatic frequency
From the two-dimensional function curvilinear relationship, it can be seen that near to the frequencies of 10, 19 and 37 GHz, the transmittance shows the function characteristic of monotone decreasing, namely near this frequency point, the lower the frequency is, the smaller the attenuation will be; and the smaller the attenuation is, the smaller the disturbing influence from rainfall when the wind is measured will. In addition, the higher the frequency is, the greater the effect from rainfall will be; however, it is sensitive to the subtle variations of the sea surface roughness.
The horizontal coordinates in
channel of 10.65 GHz and H and V channels of 36.5 GHz are sensitive to the thermal radiation. From the standard deviation, it can be seen that in the left
The imaging products for global sea surface wind speed on July 7, 2014 are shown in the following
In
carried by European METOP, are compared, while the wind speeds of the island fixed buoys in the same region and same time are used to compare and verify the maximum wind speed.
It can be seen that, due to the single frequency measurement of ASCAT, the storm foam layer under wind conditions causes the radar backscattering coefficient to be saturated, and all of the measured maximum wind speeds are 25 m/s. The maximum wind speeds inversed by FYS-WMRI are respectively 45, 45 and 43 m/s, and the actual maximum wind speeds measured by island fixed buoy are respectively 55, 52 and 40 m/s. It can be seen that the maximum wind speeds inversed by FY3-WMRI are closer to the actual values. This is crucial for coastal wind monitoring.
Typhoon Rammasun, shown in the middle of
This paper first introduced the development of the sea surface wind speed model inversed using a satellite-borne scatterometer and microwave radiometer and wind inversion problems throughout the world, as well as the preparation of the data source, including the introduction of the MWRI instrument and verification of the buoy. The brightness temperature data of Fengyun-3C meteorological
“NEOGURI” 7.7 | “RAMMASUN” 7.18 | “MATMO” 7.22 | |
---|---|---|---|
ASCAT | 25 m/s | 55 m/s | 25 m/s |
FY3-WMRI | 45 m/s | 55 m/s | 43 m/s |
Ture | 55 m/s | 55 m/s | 42 m/s |
satellite MWRI for one year were analyzed, providing the 0 - 15 m/s wind speed inversion effect. This paper proved that the analysis method, combined with multiple channels, is helpful for the wind inversion. The backward heat emission was calculated, using the complex model of the two-scale randomly rough surface with foam scattering layer; the different response characteristics of the thermal radiation characteristics for each channel with the change of the sea surface wind speed were analyzed, and the wind speed inversion model applying to the microwave radiometer was established, achieving better results than in previous research. The sea surface medium-low wind speed precision standard deviation of the new model reaches 1.2 m/s (0 - 15 m/s); the inversion strong wind data are consistent with the island fixed buoys data, and the global sea surface wind speed schematic diagram was given.
An, D.W., Dou, F.L. and Zhang, P. (2017) Algorithm for the Sea Surface Wind Imaging Products of Fengyun-3C Meteorological Satellite MWRI. Journal of Geoscience and Environment Protection, 5, 49-58. https://doi.org/10.4236/gep.2017.57006