Abstract
Total precipitable water (TPW) is an important key factor in the global water cycle and climate change. The knowledge of TPW characteristics at spatial and temporal scales could help us to better understand our changing environment. Currently, many algorithms are available to retrieve TPW from optical and microwave sensors. There are still no available TPW data over land from FY-3D MWRI, which was launched by China in 2017. However, the TPW product over land is a key element for the retrieval of many ecological environment parameters. In this paper, an improved algorithm was developed to retrieve TPW over land from the brightness temperature of FY-3D MWRI. The major improvement is that surface emissivity, which is a key parameter in the retrieval of TPW in all-weather conditions, was developed and based on an improved algorithm according to the characteristics of FY-3D MWRI. The improvement includes two aspects, one is selection of appropriate ancillary data in estimating surface emissivity parameter Δε18.7/Δε23.8 in clear sky conditions, and the other is an improvement of the Δε18.7/Δε23.8 estimation function in cloudy conditions according to the band configuration of FY-3D MWRI. Finally, TPW retrieved was validated using TPW observation from the SuomiNet GPS and global distributed Radiosonde Observations (RAOB) networks. According to the validation, TPW retrieved using observations from FY-3D MWRI and ancillary data from Aqua MODIS had the best quality. The root mean square error (RMSE) and correlation coefficient between the retrieved TPW and observed TPW from RAOB were 5.47 and 0.94 mm, respectively.
Highlights
Total precipitable water (TPW),known as total column water vapor in the atmosphere, is a key meteorological parameter often used by weather forecasting experts to predict heavy precipitation [1,2]
The data used in this study mainly include brightness temperature from FY-3D Microwave Radiation Imager (MWRI), water vapor, and land surface temperature products from FY-3D MERSI and Aqua MODIS, SuomiNet GPS TPW observations from Global Network, and atmospheric profiles from global distributed radiosonde observations (RAOB)
An improved TPW retrieval algorithm was developed according to the characteristics of FY-3D MWRI to create TPW in all-weather conditions over land
Summary
Total precipitable water (TPW),known as total column water vapor in the atmosphere, is a key meteorological parameter often used by weather forecasting experts to predict heavy precipitation [1,2]. Aires et al retrieved total precipitable water, cloud liquid water, surface temperature, and surface emissivity based on SSM/I data over land using the artificial neural network method [12]. By analyzing the data in the simulated database, it was found that the polarization ratio of the 18.7 and 23.8 GHz bands had good linear correlation with the atmospheric water vapor The advantage of this method is that the surface emissivity in the simulation database is obtained by AIEM model. The uncertainty of the land surface emissivity parameter makes it difficult to retrieve total precipitable water over land areas using passive microwave radiometers such as AMSR-E, AMSR2, and FY-3D MWRI. Ji et al [17] developed an algorithm to retrieve total precipitable water over land based on AMSR-E by developing a new land surface emissivity parameter estimation method.
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