Fengyun-4 Geostationary Satellite-Based Solar Energy Nowcasting System and Its Application in North China

Surface solar irradiance(SSI)nowcasting(0-3 h)is an effective way to overcome the intermittency of solar energy and to ensure the safe operation of grid-connected solar power plants.In this study,an SSI estimate and nowcasting system was established using the near-infrared channel of Fengyun-4A(FY-4A)geostationary satellite.The system is composed of two key components:The first is a hybrid SSI estimation method combining a physical clear-sky model and an empirical cloudy-sky model.The second component is the SSI nowcasting model,the core of which is the derivation of the cloud motion vector(CMV)using the block-matching method.The goal of simultaneous estimation and nowcasting of global horizontal irradiance(GHI)and direct normal irradiance(DNI)is fulfilled.The system was evaluated under different sky conditions using SSI measurements at Xianghe,a radiation station in the North China Plain.The results show that the accuracy of GHI estimation is higher than that of DNI estimation,with a normalized root-mean-square error(nRMSE)of 22.4%relative to 45.4%.The nRMSE of forecasting GHI and DNI at 30-180 min ahead varied within 25.1%-30.8%and 48.1%-53.4%,respectively.The discrepancy of SSI estimation depends on cloud occurrence frequency and shows a seasonal pattern,being lower in spring-summer and higher in autumn-winter.The FY-4A has great potential in supporting SSI nowcasting,which promotes the development of photovoltaic energy and the reduction of carbon emissions in China.The system can be improved further if calibration of the empirical method is improved.

Data-driven Estimation of Cloud Effects on Surface Irradiance at Xianghe,a Suburban Site on the North China Plain

Clouds are a dominant modulator of the energy budget.The cloud shortwave radiative effect at the surface(CRE)is closely related to the cloud macro-and micro-physical properties.Systematic observation of surface irradiance and cloud properties are needed to narrow uncertainties in CRE.In this study,1-min irradiance and Total Sky Imager measurements from 2005 to 2009 at Xianghe in North China Plain are used to estimate cloud types,evaluate cloud fraction(CF),and quantify the sensitivities of surface irradiance with respect to changes in CF whether clouds obscure the sun or not.The annual mean CF is 0.50,further noting that CF exhibits a distinct seasonal variation,with a minimum in winter(0.37)and maximum in summer(0.68).Cumulus occurs more frequently in summer(32%),which is close to the sum of the occurrence of stratus and cirrus.The annual CRE is–54.4 W m^(–2),with seasonal values ranging from^(–2)9.5 W m^(–2)in winter and–78.2 W m^(–2)in summer.When clouds do not obscure the sun,CF is a dominant factor affecting diffuse irradiance,which in turn affects global irradiance.There is a positive linear relationship between CF and CRE under sun-unobscured conditions,the mean sensitivity of CRE for each CF 0.1 increase is about 1.2 W m^(–2)[79.5°<SZA(Solar Zenith Angle)<80.5°]to 7.0 W m^(–2)(29.5°<SZA<30.5°).When clouds obscure the sun,CF affects both direct and diffuse irradiance,resulting in a non-linear relationship between CF and CRE,and the slope decreases with increasing CF.It should be noted that,although only data at Xianghe is used in this study,our results are representative of neighboring areas,including most parts of the North China Plain.

Estimation of PM2.5 Mass Concentration from Visibility

Aerosols in the atmosphere not only degrade visibility,but are also detrimental to human health and transportation.In order to develop a method to estimate PM2.5 mass concentration from the widely measured visibility,a field campaign was conducted in Southwest China in January 2019.Visibility,ambient relative humidity(RH),PM2.5 mass concentrations and scattering coefficients of dry particles were measured.During the campaign,two pollution episodes,i.e.,from 4-9 January and from 10-16 January,were encountered.Each of the two episodes could be divided into two periods.High aerosol hygroscopicity was found during the first period,when RH was higher than 80%at most of the time,and sometimes even approached 100%.The second period experienced a relatively dry but more polluted condition and aerosol hygroscopicity was lower than that during the first period.An empirical relationship between PM2.5 mass concentration and visibility(ambient aerosol extinction)under different RH conditions could thus be established.Based on the empirical relationship,PM2.5 mass concentration could be well estimated from visibility and RH.This method will be useful for remote sensing of PM2.5 mass concentration.

A Thorough Evaluation of the Passive Microwave Radiometer Measurements onboard Three Fengyun-3 Satellites

Microwave Radiometer Imager(MWRI) is a key payload of China’s second generation polar meteorological satellite, i.e., Fengyun-3 series(FY-3). Up to now, 5 satellites including FY-3A(2008), FY-3B(2010), FY-3C(2013), FY-3D(2018), and FY-3E(2021) have been launched successfully to provide multiwavelength, all-weather, and global data for decades. Much progress has been made on the calibration of MWRI and a recalibrated MWRI brightness temperature(BT) product(V2) was recently released. This study thoroughly evaluates the accuracy of this new product from FY-3B, 3C, and 3D by using the simultaneous collocated Global Precipitation Measurement(GPM)Microwave Imager(GMI) measurements as a reference. The results show that the mean biases(MBEs) of the BT between MWRI and GMI are generally less than 0.5 K and the root mean squares(RMSs) between them are less than1.5 K. The previous notable ascending and descending difference of the MWRI has disappeared. This indicates that the new MWRI recalibration procedure is very effective in removing potential errors associated with the emission of the hot-load reflector. Analysis of the dependence of MBE on the latitude and earth scene temperature shows that MBE decreases with decreasing latitude over ocean. Furthermore, MBE over ocean decreases linearly with increasing scene temperature for almost all channels, whereas this does not occur over land. A linear regression fitting is then used to modify MWRI, which can reduce the MBE over ocean to be within 0.2 K. The standard deviation of error of GMI, FY-3B, and FY-3D MWRI BT data derived by using the three-cornered hat method(TCH) shows that GMI has the best overall performance over ocean except at 10.65 GHz where its standard deviation of error is slightly larger than that of FY-3D. Over land, the standard deviation of error of FY-3D is the lowest at almost all channels except at 89V. MWRI onboard FY-3 series satellites would serve as an important passive microwave radiometer member of the constellation to monitor key surface and atmospheric properties.

A Deep-Learning and Transfer-Learning Hybrid Aerosol Retrieval Algorithm for FY4-AGRI:Development and Verification over Asia

The Advanced Geosynchronous Radiation Imager(AGRI)is a mission-critical instrument for the Fengyun series of satellites.AGRI acquires full-disk images every 15 min and views East Asia every 5 min through 14 spectral bands,enabling the detection of highly variable aerosol optical depth(AOD).Quantitative retrieval of AOD has hitherto been challenging,especially over land.In this study,an AOD retrieval algorithm is proposed that combines deep learning and transfer learning.The algorithm uses core concepts from both the Dark Target(DT)and Deep Blue(DB)algorithms to select features for the machinelearning(ML)algorithm,allowing for AOD retrieval at 550 nm over both dark and bright surfaces.The algorithm consists of two steps:①A baseline deep neural network(DNN)with skip connections is developed using 10 min Advanced Himawari Imager(AHI)AODs as the target variable,and②sunphotometer AODs from 89 ground-based stations are used to fine-tune the DNN parameters.Out-of-station validation shows that the retrieved AOD attains high accuracy,characterized by a coefficient of determination(R2)of 0.70,a mean bias error(MBE)of 0.03,and a percentage of data within the expected error(EE)of 70.7%.A sensitivity study reveals that the top-of-atmosphere reflectance at 650 and 470 nm,as well as the surface reflectance at 650 nm,are the two largest sources of uncertainty impacting the retrieval.In a case study of monitoring an extreme aerosol event,the AGRI AOD is found to be able to capture the detailed temporal evolution of the event.This work demonstrates the superiority of the transfer-learning technique in satellite AOD retrievals and the applicability of the retrieved AGRI AOD in monitoring extreme pollution events.