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Infrared Radiance Simulation and Application Under Cloudy Sky Conditions Based on HIRTM

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Infrared Radiance Simulation and Application Under Cloudy Sky Conditions Based on HIRTM JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY, VOL. 17, NO. 2, JUNE 2019 161 Digital Object Identifier:10.11989/JEST.1674-862X.80730010 Infrared Radiance Simulation and Application under Cloudy Sky Conditions Based on HIRTM Jian-Hua Qu | Jun-Jie Yan* | Mao-Nong Ran Abstract—An algorithm based on hyperspectral infrared cloudy radiative transfer model (HIRTM) is introduced and a simulation method for infrared image of the generation geostationary meteorological satellite is proposed. Based on the parameters from weather research and forecast (WRF), such as the water content, atmospheric temperature, and humidity profile, the simulation data for the advanced Himawari imager (AHI) infrared radiative (IR) channels of Himawari-8 are obtained. Simulated results based on HIRTM agree well with the observed data. Further, the movement, development, and change of the cloud are well predicated. And the simulation of IR cloud image for the weather forecast has been obtained. This paper provides an improved method for evaluation and improvement of regional numerical model for weather forecast. Index Terms—Hyperspectral infrared cloudy radiative transfer model (HIRTM), regional numerical model, satellite cloud image. 1. Introduction The meteorological satellite data has attracted lots of attention of research institutes, companies, and governments for its unique characteristics and advantages[1]. High-resolution remote sensing data plays a key role in the fields of weather analysis and forecasting, climate change research[2], environmental monitoring[3], and disaster prevention and reduction[4],[5], which is critical for the economic development of a country. Recently, the weather forecast theory and the data acquisition technology have been improved effectively. Meanwhile, methods and technologies have been greatly improved for weather forecast. However, the catastrophic weather, such as rainstorm, is still hard to be predicted, and the meteorological departments are unable to present a timely warning for residents[6]. In addition, the rainstorm details (time, location, and intensity) and prediction timeliness still have great limitations. Therefore, making full use of the observed data, especially the high-resolution data of the new geostationary meteorological satellite, is one of the effective means to improve the early warning and the prediction of the disaster weather in the future. The new generation geostationary meteorological satellites has been launched by China, United States, and Japan. These satellites carry advanced high-resolution observation instrument (1-minute to 15-minute observational frequency, 0.5 km to 4.0 km spatial resolution), which can be helpful to increase the forecast *Corresponding author Manuscript received 2018-07-25; revised 2018-09-19. This work was supported by the Climate Change Special Project under Grant No. CCSF201834. J.-H. Qu, J.-J. Yan, and M.-N. Ran are with Huayun Shinetek Company, China Meteorological Administration, Beijing 100081, China (e-mail: [email protected]; [email protected]; [email protected]). Publishing editor: Xin Huang 162 JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY, VOL. 17, NO. 2, JUNE 2019 accuracy of weather and climate in China[7],[8]. Although the quantitative application of Fengyun-4 will be the main development direction, the traditional qualitative identification (satellite cloud image) is still a popular method for weather analysis and severe convective weather monitoring. With the high temporal and spatial resolution of the multi-spectral infrared brightness temperature measurement, the forecasters need to recognize current weather situation from the cloud map, and then predict the change of the mesoscale weather system in the next 1 day to 7 days according to the numerical weather forecast (NWP). Compared with the situation of NWP, simulated satellite cloud images can provide more information for forecasters. The simulated method based on the NWP can improve the effect of the observed data of the new geostationary meteorological satellite, which is significant for the daily weather forecast. Cloud simulation can convert the output of the NWP model into the simulated satellite cloud image, establishing an operator or mapping between the atmospheric state and the satellite observation for transforming the atmosphere parameters into satellite observed data. Since cloud has great influence on the simulation results of the radiative transfer model, more attention has been attributed to researches on cloud simulation under cloudy conditions. Two typical radiative transfer models, the general radiative model community radiative transfer model (CRTM)[9] from United States and the radiative transfer for the tiros operational vertical sounder (RTTOV)[10] developed by Europe, have been widely used. Although these two models consider the radiative effects of aquatic products and have been improved effectively, there are still lots of limitations in the simulation of the infrared band under the cloudy sky, especially in cloud radiance or brightness temperature calculation. Aiming to solve the problems of slow calculation speed and low precision, a fast and accurate radiative transfer model: Hyperspectral infrared cloudy radiative transfer model (HIRTM)[11],[12], for infrared bands is proposed to improve the simulated accuracy of brightness temperature in the cloudy sky based on RTTOV and CRTM. This research proposes a simulation system based on HIRTM by transferring weather research and forecast (WRF) data to the simulated data. 2. Algorithm and Processes The radiative transfer model is an observation operator, which is the fundamental for the direct assimilation of satellite radiative data and cloud simulation. According to the atmospheric temperature, humidity profile, and surface state variables, the fast radiative transfer model follows the observation direction (scanning angle) of the satellite scanner and calculates the simulated observation value of the satellite in high precision by using the spectral response function (SRF) of the instrument detection channel. The simulated results under the clear air condition have quite high precision. In addition, the assimilation application of satellite data in current NWP model should be under the clear air condition. However, the calculation precision under the cloudy and rain conditions needs to be improved because of the complexity of the radiative effect of water. Several key problems remain unsolved in the simulation of cloud atmosphere radiance in the infrared radiative (IR) channels. Firstly, there are lots of uncertain parameters for both the numerical forecast and the radiative transfer model in the cloud region. Secondly, the results of the satellite observation may not be consistent with the results of the numerical prediction. Thirdly, the atmospheric temperature and humidity in the clear sky and cloudy sky have obvious structural differences in the vertical direction. Lastly, the energy of infrared radiance in the cloudy region is more nonlinear than other atmospheric parameters[12]. Based on the advantages and disadvantages of various models, HIRTM considers the atmospheric transmittance caused by molecular absorption, cloud absorption, and scattering of water under the condition of cloud. Further, compared with the simple cloud region simulation, HIRTM considers the cloud scattering and absorption model based on the parameters of the effective cloud top, cloud phase, cloud particle size, and cloud optical thickness. QU et al.: Infrared Radiance Simulation and Application under Cloudy Sky Conditions Based on HIRTM 163 2.1. Calculation of Clear Air Atmospheric Radiance The calculation of clear sky atmospheric radiance is relatively mature. The atmospheric state can be interpolated into the vertical pressure layer of the radiative transfer model from the NWP prediction field by the method of linear interpolation, and then the reliable and accurate infrared brightness temperature calculation can be carried out. The calculation of atmospheric transmittance model is critical among the calculation of clear sky radiance. So, based on the typical high temperature humidity profile library and the corresponding accurate transmittance, the linear regression model is applied to calculate the transmittance coefficient to realize the rapid calculation of the atmospheric transmittance. Moreover, the atmospheric transmittance, radiance, and brightness temperature could be calculated according to the real-time profile. HIRTM divides the atmospheric vertical layer from 0.005 hPa to 1100 hPa into 101 layers. The atmospheric transmittance calculation model is from the stand-alone 98 radiative transfer algorithm (SARTA)[13],[14]. 2.2. Cloud Radiative Model In the cloudy sky, different shapes and sizes of cloud and particles have much complex scattering and absorption characteristics in different optical wavebands. Therefore, a lookup table is built, which includes different types of cloud optical thicknesses, cloud particle sizes, and transmittance and reflectivity functions. The model assumes that the cloud is in a plane parallel, uniform, and horizontal isothermal layer in a given perspective. In addition, the model also offers a given angle of view to calculate the absorption of energy by the mixture including nitrogen, oxygen, water vapor, ozone, and carbon dioxide. The main elements of the model include the cloud types, equivalent cloud top pressure height, 0.55-μm cloud optical thickness, and cloud particle size. In the model of cloud
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