Approaches Of Stripe-Noise Mitigation For Space-based Microwave Imager Observations And Application Of The Observations In Climate Analysis

Space-based microwave imagers,play an important role in weather forecasting,climate analysis and environmental monitoring by performing full-weather measurements worldwide.Before using these measurements,quality problems of the data should be solved.Previous study shows that the striping noises in the measurements have detrimental impacts on data assimilation and precipitation retrieval.So,it is necessary to eliminate those noises.With their channels located at the atmospheric window,the microwave imagers are sensitive to features of earth's surface and precipitation.The brightness temperatures measured by these channels show sharp gradients as much as tens of Kelvin at places where the imager scan-lines aligned with either coastlines curves or the edges of deep clouds.This brings extra difficulties for the noise elimination.This study focused on analyzing the striping noises which are common in microwave measurements,developed the method of striping noise mitigation,especially the approaches for space-based microwave imager observations at atmospheric window channels which could overcome the impacts of the sharp gradients near coastlines and edges of the deep clouds.This method had been applied in various microwave imager measurements.Then,we also verified the impacts of the striping noise on precipitation retrieval and climate trends calculation and analyzed the climate trends and four-month oscillations in polar area based on the FY-3B MWRI observations,sea ice data and ERA re-analysis data.The results are summarized as follows:(1)The PCA/EEMD method could eliminate the striping noise in water vapor sounding channels.The new generation microwave imager-GMI water vapor sounding channels display a clear across-track striping noise in the measurements with the amplitude of 0.3 K at frequencies between 0.06s"1 and 0.533s'1.Processed by the PCA/EEMD method,the striping noised disappeared while the weather signals were not affected.(2)The modified PCA/EEMD could reduce the striping noise in surface channels.Different from water vapor sounding channels,the surface channels of the microwave imager are significantly affected by the surface emissivity and precipitation.Due to the sharp gradient of the brightness temperature at the place around the coast or the edges of deep clouds,original PCA/EEMD method is likely to remove the brightness temperatures as striping noised incorrectly.In this study,a modified method was proposed,which adopted an additional step to separate the high-frequency component of the drastic gradient from the observations prior to eliminating the striping noise.Analysis showed that this modified could effectively reduce the striping noise at microwave imager surface channels without affecting the radiance information near the coastlines and the edges of deep-cloud.(3)The accuracy of the precipitation retrievals was improved when the striping noise were eliminated from the microwave imager measurements before retrieving.The precipitation information was retrieved by using NASA GPROF precipitation retrieval algorithm and the brightness temperatures with or without striping noise.By comparing the results,we found that the striping noise in TMI measurements could lead to 0.06kg/m2 errors in LWP or IWP retrievals.(4)In order to further confirm that the modified PCA/EEMD could be applied at the window channels of different microwave imagers and obtain a set of parameters of MWRI de-striping procedure,FY-3C MWRI measurements were analyzed.The results showed that the amplitude of the striping noise at MWRI channel 9 and channel 10 was higher than 1K.At channel 1 and channel 2,the striping noise was 0.6K.The modified method could reduce the striping noise effectively at all channels of MWRI without affecting the surface radiation information and weather signals.The accuracy of the precipitation retrievals was improved when the striping noises were eliminated,especially for deep cloud precipitation(5)The modified PCA/EEMD method was applied in the de-striping of The measurements of MWRI measurements,which was then used in the research of the climate change in the polar area It has been found that the noises were randomly distributed in space during 2011-2016.The maximum was about 0.9K at channel 3 and was about 0.6K at channel 7.Although the striping noise have little impact on climate trends calculations,they should be eliminated before analyzing the spatial distribution.The results showed that brightness temperatures in polar area decreased,especially in the Arctic.Besides,the spectrum results of the brightness temperatures showed a very pronounced four-month oscillation(FMO)with the intensity varying interannually.The intense oscillation areas mainly located in the Chukchi Sea and Beaufort Sea of the Arctic,while in Antarctic,the FMO phase was different,or even opposite in different areas.Melting and freezing process of sea ice and variations of the surface temperature jointly contributed to fluctuation of the brightness temperature,with the former having a greater impact.The sea ice in the Arctic decreased in recent years and had significant FMO.The intense oscillation areas were consistent with the brightness temperature's.