Introducing the New Generation of Chinese Geostationary Weather Satellites, Fengyun-4

INTRODUCING THE NEW GENERATION OF CHINESE GEOSTATIONARY WEATHER SATELLITES, FENGYUN-4

Jun Yang, Zhiqing Zhang, Caiying Wei, Feng Lu, and Qiang Guo

Fengyun-4 is the new generation of Chinese geostationary meteorological satellites with greatly enhanced capabilities for high-impact weather event monitoring, warning, and forecasting.

n 7 September 1988, the Long March rocket FY-2 satellites carry the Visible and Infrared Spin Scan carried the Fengyun-1A (FY-1A) polar-orbiting Radiometer (VISSR) capable of imagery in five spectral O satellite into orbit, marking the start of the bands. Derived products include atmospheric motion Chinese Fengyun (FY; meaning wind and cloud in vectors (AMVs), sea surface temperatures (SSTs), total Chinese) meteorological satellite observing systems pro- precipitable water vapor (TPW), quantitative precipi- gram. On 10 June 1997, the FY-2A geostationary satellite tation estimations (QPEs), fire locations and intensity, was successfully launched and the Chinese meteorologi- surface albedo, and several others. cal satellite program took a large step toward its goal The FY-4 introduces a new generation of Chinese of establishing both polar-orbiting and geostationary geostationary meteorological satellites, with the first observational systems. Over time the Fengyun satellites have become increasingly important for protecting lives and property from natural disasters in China. Table 1. FY-2D/FY-2E overlap region observation The Chinese FY satellites are launched as a series. schedule. Full-disc and north-disc observations The odd numbers denote the polar-orbiting satellite are abbreviated as F and N, respectively. series, and the even numbers denote the geostationary Time (UTC) Region Satellite satellite series. After launch, a letter is appended to 0000 F FY-2E indicate the order in the satellite series; for instance, 0015 F FY-2D FY-2F is the sixth satellite that has been launched 0030 N FY-2E in the first generation of the Chinese geostationary 0045 N FY-2D satellites (FY-2). The FY-2, the first generation of the Fengyun geostationary weather satellite series, includes 0100 F FY-2E seven satellites launched since 1997; another will follow 0115 F FY-2D around 2017 to conclude the FY-2 mission. The Chinese 0130 N FY-2E geostationary weather satellite system operates two 0145 N FY-2D satellites located at 86.5°E (FY-2 West) and 105°E (FY-2 — — — East); they provide full-disc observations every 30 min 2300 F FY-2E and observations every 15 min in their overlap region 2315 F FY-2D (see Fig. 1 for the current FY-2 coverage). The FY-2D 2330 N FY-2E (West) and FY-2E (East) observation schedule is shown in Table 1. The two satellites also back each other up. 2345 N FY-2D

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1637 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC Fig. 1. The 10.8-µm (left) FY-2D and (right) FY-2E BT (K) images showing coverage of (left) FY-2 East and (right) FY-2 West.

FY-4A launched on 11 December 2016. The remain- per pixel (up from 10 bits for FY-2) and sampled at ing satellites of this series are planned to be launched 1 km at nadir in the visible (VIS), 2 km in the near- from 2018 to 2025 and beyond. FY-4 has improved infrared (NIR), and 4 km in the remaining IR spectral capabilities for weather and environmental monitor- bands (compared with 1.25 km for VIS, no NIR, and ing, including a new capability for vertical tempera- 5 km for IR of FY-2). FY-4 will improve most prod- ture and moisture sounding of the atmosphere with ucts of FY-2 and introduce many new products [such its high-spectral-resolution infrared (IR) sounder, as atmospheric temperature and moisture profiles, the Geostationary Interferometric Infrared Sounder atmospheric instability indices, layer precipitable (GIIRS). Following 15 years, the three-axis stabilized water vapor (LPW), rapid developing clouds, and FY-4 series will offer full-disc coverage every 15 min others]. Products from FY4 series are expected to pro- or better (compared to 30 min of FY-2) and the option vide enhanced applications and services. These new for more rapid regional and mesoscale observation products are compared with those of FY-2 in Table 2. modes. The Advanced Geosynchronous Radiation FY-4’s AGRI will be operated in conjunction Imager (AGRI) has 14 spectral bands (increased from with GIIRS. FY-4’s GIIRS is the first high-spectral- the five bands of FY-2) that are quantized with 12 bits resolution advanced IR sounder on board a geostationary weather satellite, complementing the advanced IR sounders in polar orbit. These include AFFILIATIONS: Yang, Zhang, Wei, Lu and Guo—National the Atmospheric Infrared Sounder (AIRS) on board Satellite Meteorological Center, China Meteorological the National Aeronautics and Space Administra- Administration, Beijing, China tion (NASA) Earth Observing System (EOS) Aqua CORRESPONDING AUTHOR: Zhiqing Zhang, platform (Chahine et al. 2006), the Infrared Atmo- [email protected] spheric Sounding Interferometer (IASI) on board The abstract for this article can be found in this issue, following the Europe’s Meteorological Operational (MetOp) satel- table of contents. lites (Clerbaux et al. 2007; Smith et al. 2009), and the DOI:10.1175/BAMS-D-16-0065.1 Cross-Track Infrared Sounder (CrIS) on board the In final form 6 December 2016 Suomi National Polar-Orbiting Partnership (SNPP; ©2017 American Meteorological Society www.nasa.gov/mission_pages/NPP/main/index.html For information regarding reuse of this content and general copyright ; information, consult the AMS Copyright Policy. Bloom 2001). They have had a large positive impact in global and regional numerical weather prediction

1638 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC Table 2. Products of FY-4 and FY-2.

FY-2 FY-4 Products Payloads Products Payloads Cloud detection VISSR Cloud masks AGRI Cloud classification VISSR Cloud type AGRI Total cloud amount VISSR Total cloud amount AGRI Precipitation estimation VISSR Rainfall rate/quantitative precipitation estimate AGRI Atmospheric motion vector VISSR Atmospheric motion vector AGRI Outgoing longwave radiation VISSR Outgoing longwave radiation AGRI Blackbody brightness temperature VISSR Blackbody brightness temperature AGRI Surface solar irradiance VISSR Surface solar irradiance AGRI Humidity product analyzed by cloud VISSR Legacy vertical moisture profile GIIRS information Total precipitable water VISSR Layer precipitable water AGRI Upper-tropospheric humidity VISSR Layer precipitable water Dust detection VISSR Aerosol detection (including smoke and dust) AGRI Sea surface temperature VISSR Sea surface temperature (skin) AGRI Snow cover VISSR Snow cover AGRI Land surface temperature VISSR Land surface (skin) temperature AGRI Cloud-top temperature VISSR Cloud-top temperature AGRI Cloud-top height AGRI Cloud-top pressure AGRI Cloud optical depth AGRI Cloud liquid water AGRI Cloud particle size distribution AGRI Cloud phase AGRI Downward longwave radiation: surface AGRI Upward longwave radiation: surface AGRI Reflected shortwave radiation: top of atmosphere AGRI Aerosol optical depth AGRI Convective initiation AGRI Fire/hot spot characterization AGRI Fog detection AGRI Land surface emissivity AGRI Land surface temperature AGRI Land surface albedo AGRI Tropopause folding turbulence prediction AGRI Legacy vertical temperature profile GIIRS Ozone profile and total GIIRS Atmosphere instability index GIIRS Lightning detection LMI Space and solar products SEP

(NWP) applications (Le Marshall et al. 2006; McNally (Li et al. 2011, 2012), nowcasting, and short-range et al. 2014; Wang et al. 2014; Li et al. 2016) and forecasting require nearly continuous monitoring climate research (Yoo et al. 2013). However, severe of the vertical temperature and moisture structure weather warning in a preconvective environment of the atmosphere on small spatial scales that only

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1639 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC a geostationary advanced IR sounder can provide. other countries, FY-4 will become an important GEO The GIIRS will provide breakthrough measurements component of the global Earth-observing system. with the temporal, horizontal, and vertical resolution Overall, FY-4 represents an exciting expansion in needed to resolve the quickly changing water vapor Chinese geostationary remote sensing capabilities. and temperature structures associated with severe FY-4A will be considered experimental and the subse- weather events. GIIRS will be an unprecedented quent satellites in the FY-4 series will be operational. source of information on the dynamic and thermo- Compared with the current operational FY-2 series, dynamic atmospheric fields necessary for improved the FY-4 satellites are designed to have a longer oper- nowcasting and NWP services (Schmit et al. 2009). ating life. Table 3 summarizes some of the significant High-spectral-resolution IR measurements will also improvements in instrument performance expected provide estimates of diurnal variations in tropo- from FY-4 compared with the current operational FY-2 spheric trace gases like ozone and carbon monoxide series. For the FY-4 operational series of satellites, the (Li et al. 2001; J.-L. Li et al. 2007; Huang et al. 2013) main observation capabilities are similar to those of FY- that will support forecasting of air quality and moni- 4A, with some significant performance improvements. toring of atmospheric minor constituents. The AGRI channel number will be increased from 14 to The FY-4 GIIRS is one of the Group on Earth Ob- 18 with IR spatial resolution of 2 km, and the full-disc servations (GEO) sounders planned by Global Earth temporal resolution will be enhanced from 15 to 5 min. Observation System of Systems (GEOSS) member states GIIRS spectral and spatial resolutions will be increased in response to the call from the World Meteorological to 0.625 cm–1 and 8 km, respectively. Lightning Map- Organization (WMO) for advanced sounders in the ping Imager (LMI) coverage will be enlarged to full geostationary orbit. Another is the Infrared Sounder disc. Space-monitoring instruments will be increased; (IRS) planned by the European Organisation for the for example, a solar X-ray and extreme ultraviolet Exploitation of Meteorological Satellites (EUMETSAT) imager will be on the following FY-4 series satellites. for the geosynchronous Meteosat Third Generation This paper provides an introduction to the (MTG) satellite systems in the 2020 time frame and Chinese FY-4 observation capabilities, the derived beyond. Together with the new generation of geosta- products, and the associated applications. The ground tionary weather satellite systems being developed by system components are briefly described in the next

Table 3. Advancement of FY-4A compared with the current operational FY-2 series. SEM = Space Environment Monitor. SSP = subsatellite point.

FY-4A (experimental) FY-4 (operational) FY-2 (operational) Stabilization Three axis Three axis Spin Designed life 7 years (designed life) 7 years (operation life) 4 years Observation efficiency 85% 85% 5% Observation mode Imaging + Imaging + sounding + sounding + Imaging only lightning mapping lightning mapping AGRI: 14 channels AGRI: 18 channels VISSR: 5 channels Resolution: 0.5–4 km Resolution: 0.5–2 km Resolution: 1.25–5 km Full disc: 15 min Full disc: 5 min Full disc: 30 min GIIRS: 913 channels GIIRS: >1,500 channels SSP resolution: 16 km SSP resolution: 8 km — Spectral resolution: Spectral resolution: 0.8, 1.6 cm−1 0.625 cm−1 Main instruments LMI LMI Area coverage Full-disc coverage — SSP resolution: 7.8 km SSP resolution: 7.8 km SEP SEP SEM High-energy particles High-energy particles, High-energy particles Magnetic field magnetic field, solar Solar X-ray fluxes imager

1640 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC section. The following sections provide an overview 3) monitoring the satellite and controlling the pay- of the four FY-4A instruments, products, and related loads; application areas, and the final section offers a sum- 4) undertaking the mission management and opera- mary and conclusions. tion control of the satellite and ground systems; 5) processing data for geolocation and registration; FY-4A GROUND SEGMENT. A new ground 6) processing data for measurement calibration; segment has been designed and is being built to 7) producing quantitative products; accommodate the technical requirements of the FY-4 8) providing an archive and distribution service for satellites. The primary ground missions are as follows: the data and products; 9) carrying out applications for the weather, climate, 1) receiving raw data from the satellite; and environment; and 2) determining and predicting the satellite orbit based 10) accomplishing monitoring and predicting ser- on ranging measurements to the satellite; vices for space weather.

Fig. 2. Flowchart of FY-4 ground segment.

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1641 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC Figure 2 presents a flowchart of FY-4 ground that describe the relationship between the optical segment. In addition to the backup Data and Telemetry line of sight of instrument and structural thermal System (DTS) located in Guangzhou in southern distortion and determines the equivalent variation China, the new DTS facilities will be located in of yaw, pitch, and roll once every 24 h. The pixels of Beijing, China. The ground segment is being developed an image should be Earth-located to within 112 μrad in five phases, which include user requirement analy- (3σ, within 64.5° of geocentric angle) at the subsatel- sis, algorithm development for quantitative products, lite point during the daytime. Geographical location system design, engineering, and in-orbit testing. error is estimated from landmark navigation. Image The navigation and registration of AGRI, GIIRS, navigation and registration (INR) specification is and LMI data from a three-axis stabilized satellite listed in Table 4. is a great challenge. A method has been designed in Unlike FY-2, FY-4A will have enhanced calibra- which the satellite platform, payloads, and ground tion, including a full-path blackbody for AGRI and segment cooperate with each other. As part of the GIIRS in the thermal infrared bands (TIBs) and a ground segment, the Navigation and Registration standard reflective board for AGRI in the reflective System (NRS) calculates the scan and step angles solar band (RSB). The calibration accuracy of FY-4A from each instrument to the predicted stars that can will be better than 1 K for TIB and 5% for RSB; this be observed by the two payloads and arranges the will benefit quantitative applications greatly. observation timetable for AGRI and GIIRS based on After launch and an in-orbit test of FY-4A, the those predicted stars. The NRS solves the equations new data and products will be used in NWP, weather, climate, environment, and other areas; data distri- Table 4. Image navigation and registration specification. bution and applications are shown in Fig. 3. The FY-4A Requirement Conditions processing of FY-4A raw At the subsatellite point within data includes navigation, Navigation 112 μrad 64.5° of geocentric angle except calibration, inversion, and ±2 h around satellite midnight generation of various-level Band-to-band registration 1/4 pixel — products. The Level 1B

Fig. 3. FY-4A data distribution and application flowchart.

1642 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC (L1B) and some L2 products will be broadcast by advanced imagers, such as the new generation of U.S. FY-4A directly and users will be able to receive the Geostationary Operational Environmental Satellite High Rate Information Transmission in horizontal (GOES-R series) Advanced Baseline Imager (ABI; link or vertical polarization link (HRIT-H or Schmit et al. 2005, 2017) and the European MTG HRIT-V) or Low Rate Information Transmission Flexible Combined Imager (FCI; www.eumetsat (LRIT). The contents, bit rate, and frequency of .int/website/home/Satellites/FutureSatellites broadcast specifications are listed in Table 5. The L2 /MeteosatThirdGeneration/index.html), as well as and L3 products generated by the ground segment other similar instruments on board geostationary of FY-4A will also be distributed by the National meteorological satellites. Figure 4 shows the AGRI Meteorological Information Center (NMIC) through spectral band locations compared with ABI, FCI, CMACast (Satellite Data Broadcasting System of and others. Five bands of AGRI are heritage from China Meteorological Administration). All datasets FY-2 VISSR (0.55–0.75, 3.5–4.0, 6.3–7.6, 10.3–11.3, of FY-4A, both real time and historical, will be avail- and 11.5–12.5 µm) and similar to those on the cur- able to the global community on the National Satellite rent GOES Imager (Menzel and Purdom 1994) and Meteorological Center (NSMC) satellite data server the Japanese Multifunctional Transport Satellite http://satellite.nsmc.org.cn website ( ). (MTSAT) Imager. The CO2-sensitive spectral band (13.5 µm) of AGRI is also found on the GOES-12, THE FY-4 AGRI. FY-4A’s AGRI has 14 spectral -13, -14, and -15 imagers; the GOES-8 and -15 bands that are similar to those planned for other sounders (Menzel et al. 1998); and the Moderate

Table 5. FY-4A direct broadcast capabilities.

Channel Bit rate Max daily data (GB) Contents Frequency 1 HRIT-H 11.6 Mbps 123 L1 of all 14 channel data of AGRI 1,680 MHz 2 HRIT-V1 9.3 Mbps 65.9 a) GIIRS data 1,679 MHz b) LMI data c) Part of L2 products 3 HRIT-V2 750 Kbps 2.6 A part of AGRI data 1,679 MHz 4 LRIT 150 Kbps 1.58 Low-resolution image of AGRI 1,697 MHz

Fig. 4. The spectral band locations of AGRI compared with FCI (European imager), Advanced Meteorological Imager (AMI, South Korea), AHI (Japanese imager), and ABI (U.S. imager).

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1643 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC Resolution Imaging Spectroradiometer (MODIS) signal-to-noise specification, and the associated main (Menzel et al. 2008). The additional bands of applications. The spectral coverage for the six VIS/ AGRI are comparable with those of GOES-16 ABI NIR bands of FY-4A AGRI are shown in the top-left (Schmit et al. 2005, 2017) and the Himawari-8 panel of Fig. 5, along with spectral reflectance plots Advanced Himawari Imager (AHI; Bessho et al. for snow and vegetation [the spectral plots are from 2016). Similar to ABI (Schmit et al. 2005, 2017), the Advanced Spaceborne Thermal Emission and AGRI includes 0.47 µm for aerosol detection and Reflection Radiometer (ASTER) library (see online at visibility estimation; 0.83 µm for aerosol detec- http://speclib.jpl.nasa.gov/)]. The AGRI spectral bands tion and estimation of vegetation health; 1.378 µm will enable generation of new products and refinement for sensing very thin cirrus clouds; 1.61 µm for of existing products of FY-2. These VIS/NIR bands snow/cloud discrimination; 2.23 µm for aerosol will introduce or improve detection of haze, clouds, and cloud particle size estimation and vegetation surface vegetation, cirrus, snow cover, and aerosol detection; 3.75 µm for cloud properties/screening, particle sizes. The first three VIS/NIR bands can be hot spot detection, moisture determination, and composited to produce color images with respect to snow detection; 6.25 µm and 7.10 µm for middle- red, green, and blue (RGB) applications, that is, dust and upper-tropospheric water vapor detection and volcanic ash monitoring recommended by WMO. and tracking; 8.5 µm for detection of volcanic ash In fact, these composited images are quite different clouds containing sulfuric acid aerosols and esti- from the natural or near-natural ones generated by mation of cloud phase; 10.8 µm for determination polar-orbiting imagers such as MODIS on board of SST and surface temperature, and 12.0 µm for the NASA EOS Terra and Aqua platforms, Medium estimation of low-level moisture. Resolution Spectral Imager (MERSI) on board the Compared with the current FY-2 VISSR, the Chinese FY-3 series (Dong et al. 2009), and Visible FY-4A AGRI will have nine more spectral bands, Infrared Imaging Radiometer Suite (VIIRS) on board increased spectral resolution, improved radiometric the U.S. SNPP satellite. For the geostationary orbiting accuracy, and improved imager registration and imagers, the true color images are now being pro- navigation. Table 6 summarizes the FY-4A AGRI duced using a new process called the Simple Hybrid spectral bands, along with the spatial resolution, the Contrast Stretch (SHCS) method developed by the

Table 6. Specifications for AGRI on board FY-4A. S/N = signal to noise. NE∆T = noise equivalent differential temperature. WV = water vapor.

Spectral coverage Spectral band (µm) Spatial resolution (km) Sensitivity Main applications VIS/NIR 0.45–0.49 1 S/N ≥ 90 (p = 100%) Aerosol, visibility 0.55–0.75 0.5 S/N ≥ 150 (p = 100%) Fog, clouds 0.75–0.90 1 S/N ≥ 200 (p = 100%) Aerosol, vegetation 1.36–1.39 2 S/N ≥ 150 (p = 100%) Cirrus 1.58–1.64 2 S/N ≥ 200 (p = 100%) Cloud, snow 2.10–2.35 2 S/N ≥ 200 (p = 100%) Cloud phase, aerosol, vegetation 3.50–4.00 2 NE∆T ≤ 0.7 K (300 K) Clouds, fire, moisture, snow 3.50–4.00 4 NE∆T ≤ 0.2 K (300 K) Land surface Midwave IR 5.8–6.7 4 NE∆T ≤ 0.3 K (260 K) Upper-level WV 6.9–7.3 4 NE∆T ≤ 0.3 K (260 K) Midlevel WV Longwave IR 8.0–9.0 4 NE∆T ≤ 0.2 K (300 K) Volcanic ash, cloud-top phase 10.3–11.3 4 NE∆T ≤ 0.2 K (300 K) SST, LST 11.5–12.5 4 NE∆T ≤ 0.2 K (300 K) Clouds, low-level WV 13.2–13.8 4 NE∆T ≤ 0.5 K (300 K) Clouds, air temperature

1644 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC University of Wisconsin (UW) Space Science and display the vertical distribution of the upwelling Engineering Center (SSEC) and the National Oceanic radiances sensed by the AGRI IR bands. The two and Atmospheric Administration (NOAA)’s Center 3.9-µm bands have the same spectral response func- for Satellite Applications and Research (STAR). This tion (SRF), but different dynamic ranges; one covers simple algorithm combines four of the spectral bands 260–450 K for fire detection and characterization from the AHI into a true color RGB image (Miller et and the other covers 200–340 K for cloud and Earth al. 2016), providing added clarity. surface property determination. For improved fire The top-right and bottom panels of Fig. 5 also applications, the spatial resolution of the 3.9-µm show the spectral coverage of the seven IR bands high-range band is 2 km. The calculations to produce for FY-4A AGRI. In general, AGRI has IR spectral Fig. 6 relied on FY-4A SRFs used in a fast radiative coverage similar to that on the Spinning Enhanced transfer model developed in a joint effort between the Visible and Infrared Imager (SEVIRI) on board NSMC and the SSEC. Meteosat Second Generation (MSG). Weighting func- With 14 spectral bands (see Fig. 7 for an example tions, shown in Fig. 6 for a U.S. standard atmosphere of simulated images in all spectral bands), FY-4 will at zero satellite zenith angle, indicate the peaks of the improve the current operational FY-2 satellite prod-

two water-vapor-sensitive bands, the CO2-sensitive ucts and introduce many new products. In addition band, and the various surface viewing bands and to spectral band imagery and color composite

Fig. 5. (a) The spectral coverage of the six visible/near-infrared bands of AGRI along with spectral plots of reflectance from grass (green curve) and snow (red curve); and (b, c, and d) the coverage of seven AGRI IR bands in the infrared region superimposed on a calculation of Earth-emitted spectral BT for the U.S. standard atmosphere, along with the spectral coverage of the VISSR (green) on board the FY-2, AGRI (red) on board the FY-4, and SEVIRI (blue) on board the MSG.

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1645 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC images, the quantitative products expected from with embedded thunderstorms oriented from FY-4A AGRI data are summarized in Table 2. Most southwest to northeast across much of northeast- FY-4A AGRI products will have improved spatial ern China. The 5-km-resolution FY-2E 10.8-µm IR and temporal resolutions compared to the current channel images (not shown) revealed the development operational FY-2 products [cloud mask, land surface of very cold cloud-top brightness temperatures (–60° temperature (LST), SST, QPE, AMV, and radiation] to –75°C) with embedded thunderstorms and a period and are expected to provide enhanced applications of back building of convection in the vicinity of and services. Beijing after around 1500 UTC. The 5-km-resolution Figure 8 shows the anticipated FY-4A-like cloud FY-2E 6.8-µm water vapor channel images (see Fig. 9) products (optical depth at 0.55 µm in the top-left indicated a pronounced warming/drying signature panel, cloud-top height in kilometers in the top-right (yellow color) associated with a deepening shortwave panel, ice water path in the bottom-left panel, and trough that was approaching from the northwest. liquid water path in the bottom-right panel) retrieved This approaching trough may have played a role in using the FY-4 algorithm (Min et al. 2017) on data enhancing the synoptic-scale upward vertical motion from SEVIRI (Schmetz et al. 2002) on board the across the Beijing region that created a more favorable Meteosat-8 at 1200 UTC 1 August 2006. A convective environment for formation and maintenance of cloud system containing mainly ice particles is well strong convection. The small green square denotes depicted. AGRI will offer the same cloud products the location of Beijing International Airport (see for applications over China and its adjacent regions. Fig. 9). The spatial resolution of AGRI will be higher FY-4A AGRI will also provide critical information than FY-2; the spatial resolution of a 0.55–0.75-µm for monitoring and forecasting severe storms, such as band is 0.5 km, that of the IR band (10.3–11.3 µm) a major flooding event that occurred in Beijing, on is 4 km, and the time for a full disc is 15 min, hence 21 July 2012. The heaviest rainfall in over 60 years more spatial and temporal details of storms will be caused at least 77 fatalities, cancelled over 500 air- detected. Since the quantization depth for all bands port flights, and forced more than 65,000 people increases to 12 bits (and 3.9 µm high, it is 16 bits), to be evacuated. Much of the city averaged around the temperature resolution will be higher also. And 18–23 cm of rainfall within a 10-h period, with the AGRI has two water vapor bands so that not only heaviest total rainfall accumulation being 46 cm in two-dimensional but three-dimensional water vapor the Fangshan District of Beijing. Analysis of this structure will be detected. storm with FY-2E satellite images is available on the With more spectral bands, increased spatial Cooperative Institute for Meteorological Satellite resolution, and improved navigation, FY-4A will offer Studies (CIMSS) satellite blog (http://cimss.ssec.wisc enhanced and new information/products for moni- .edu/goes/blog/?s=beijing+). The 1.25-km resolution, toring and forecasting high-impact weather events 0.73-µm visible channel image from the Chinese like the storm discussed in the previous paragraph. FY-2E satellite showed an elongated band of clouds A new product called Rapid Developing Convection

Fig. 6. (left) Temperature weighting functions (Jacobian) from seven AGRI bands and (right) water vapor mixing ratio weighting functions from two AGRI water vapor absorption bands for a U.S. standard atmosphere.

1646 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC (RDC) aims to monitor mesoscale convection over convective clouds with cloud-top temperature cooling China for nowcasting applications. The RDC uses and checks their spectral characteristics. If the cloud- a multispectral thresholding algorithm that tracks top cooling rate (CTC) threshold is exceeded, then the

Fig. 7. Simulated FY-4A AGRI 14 spectral bands images from the high-spatial-resolution Weather Re- search and Forecasting (WRF) Model for a case of storm development (Beijing 21 Jul 2012 storm case).

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1647 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC Fig. 8. Cloud products [(top left) optical depth at 0.55 µm, (top right) cloud-top height in kilometers, (bottom left) ice water path, and (bottom right) liquid water path] derived from SEVIRI data at 1200 UTC 1 Aug 2006 using the FY-4A cloud retrieval algorithm.

pixels within the cloud object are flagged for RDC. China with a temporal resolution of 55 min and cov- The RDC product will detect not only convective ini- erage of 5,000 × 5,000 km2. The second mode is the tiation (CI) but also vigorous deep convective clouds mesoscale mode with a temporal resolution of 10 min and cloud systems. The CI algorithm (Table 7 shows and coverage of 2,000 × 2,000 km2. Some specifics of the specific attributes) of RDC is similar to that of GIIRS are shown in Table 8. GOES-16 (Mecikalski and Bedka 2006). Figure 10 The main optical structure of GIIRS is almost the shows the RDC test results using Himawari-8 AHI same as that of AGRI; an off-axis primary telescope data from 0000 UTC 20 August 2015; RDC levels is supplemented by secondary and tertiary mirrors are indicated by colors, with green for CTC > 0 K, so that the effects of sunlight shining directly into medium green for –2 ≤ CTC < 0 K, light green for the instrument aperture around local midnight –4 ≤ CTC < –2 K, yellow for –6 ≤ CTC < –4 K, orange are mitigated. Two scan mirrors, in contrast to the for CTC < –6 K, and red for CI. gimbaled two-axis scan mirror adopted for other instruments [i.e., Japanese Advanced Meteorological THE FY-4A GIIRS. The GIIRS on board FY-4A will Imager (JAMI)] in GEO platform, are utilized for be used for hourly (or better) atmospheric soundings. mesoscale and synoptic-scale observations so that Two observation modes of GIIRS are planned. One the traditional image rotation effects are removed mode is designed for synoptic-scale coverage over completely. Moreover, a Sterling cooler is adopted by

1648 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC Fig. 9. FY-2E 6.8-µm water vapor image at 1931 UTC 21 Jul 2012 visualized with the Man Computer Interactive Data Access System (McIDAS) from CIMSS/SSEC. The green square is the location of Beijing.

Table 7. The CI interest fields of FY-4A.

Interest field Thresholds Physical description Cloud tops cold enough to support supercooled 10.8-µm B <260 K T water and ice mass growth; cloud-top glaciation −1 10.8-µm BT time trends (absolute value) >6 K (15 min) Cloud growth rate (vertical)

7.3–6.2-µm BT difference <10 K Cloud thickness

10.8–6.2-µm BT difference <20 K Cloud-top height relative to mid-/upper troposphere −1 10.8–6.2-µm BT time trend (absolute value) >5 K (15 min) Cloud growth rate (vertical) toward dry air aloft

10.8–8.6-µm BT difference <4 K Cloud-top glaciation Cloud-top height relative to mid-/upper troposphere;

13.3–10.8-µm BT difference <13 K better indicator of early cumulus development but sensitive to cirrus −1 13.3–10.8-µm BT time trend (absolute value) >4 K (15 min) Cloud growth rate (vertical) toward dry air aloft

12–10.8-µm BT difference >−3 K Cloud thickness

GIIRS to enable its two detector arrays to operate at 65 found to be very useful for preconvective warnings and 75 K for longwave and midwave infrared spectra, and weather forecasts by providing near-real-time respectively. products that include clear-sky radiances, profiles of Since 1994, the United States has had a broadband temperature and moisture, atmospheric instability IR sounder on the GOES series (Menzel and Purdom indices, LPW, TPW, cloud-top retrievals (pressure, 1994; Menzel et al. 1998). The GOES Sounder mea- temperature, and effective cloud amount), surface sures emitted radiation in 18 IR spectral bands and skin temperature, water vapor atmospheric motion reflected solar radiation in one visible band. With vectors, and total ozone (Menzel et al. 1998; Velden spectral measurements from bandwidths at the order et al. 1998; Li et al. 2001; J.-L. Li et al. 2007; Li et al. of tens of wavenumbers, the GOES Sounder has been 2008). FY-4A with GIIRS will have spectral coverage

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1649 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC water vapor mixing ratio (in grams per kilogram), and ozone (in parts per million by volume), respectively. Figure 12 shows the temperature Jacobian from the FY-4A GIIRS longwave IR band, water vapor mixing ratio Jacobian (Li 1994) from the midwave IR band, and ozone mixing ratio Jacobian from the longwave IR band, along with a BT spectrum and noise equivalent delta temperatures [NeDT (NE∆T) at 250, 280, and 300 K] for a U.S. standard atmosphere. From the Jacobians shown in Fig. 12, it can be seen that the temperature vertical information in the troposphere can be derived mainly from the longwave IR channels, while the tropospheric moisture can be derived from the midwave IR channels. The upper-tropospheric and lower-stratospheric ozone can also be derived from the

Fig. 10. The RDC image at 0000 UTC 20 Aug 2015, longwave IR channels. The high spectral resolution using 2-km-resolution Himawari-8 data as test. of GIIRS is necessary to approach the observation requirements for weather forecasting, including retrieval of vertical profiles of atmospheric moisture [root- similar to the advanced IR sounders AIRS, CrIS, IASI, mean-square error (rmse) of 10% relative humidity and IRS (see Fig. 11). The GIIRS 913 channels will have (RH) for 2-km layers] and temperature (rmse of 1 K for spectral widths of less than a wavenumber in both the 1-km layers), trace gas concentrations, cloud-top pres- longwave and midwave IR spectrum and will enable sures (Yao et al. 2013), surface IR emissivity (J. Li et al. similar but improved applications as those of the 2007; Li and Li 2008), and surface temperatures. The GOES Sounder. Jacobians indicate the sensitivities of spatial resolution is 16 km for the first GIIRS on the brightness temperature (BT) viewed by the satellite experimental FY-4A and will be improved to 8 km on to the changes of atmospheric parameters, such as air the following operational FY-4 systems. The primary temperature, water vapor, and ozone. The Jacobians products of FY-4A GIIRS include atmospheric tem- of temperature, water vapor, and ozone are defined as perature and moisture profiles, instability indices, and

dBT/dT, dBT/dlog (Q), and dBT/dlog (O3), where T, Q, trace gases derived in clear skies and partially cloudy

and O3 are the profiles of air temperature (in kelvins), skies (Smith et al. 2012; Weisz et al. 2013). It could be

Table 8. Specification for GIIRS on board FY-4A. LWIR = longwave IR. MWIR = midwave IR

FY-4A (Experimental) Range Resolution Channels Spectral parameters (normal mode) LWIR: 700–1,130 cm−1 0.8 538 MWIR: 1,650–2,250 cm−1 1.6 375 VIS: 0.55–0.75 µm 1 Spatial resolution (subsatellite point) LWIR/MWIR: 16-km SSP VIS: 2-km SSP Operational mode China area 5,000 × 5,000 km2 Mesoscale area 2,000 × 2,000 km2 Temporal resolution China area <1 h Mesoscale area <1/6 h Sensitivity (mW m−2 sr cm2) LWIR: 0.5–1.1 MWIR: 0.1–0.14 VIS: S/N > 200 (ρ = 100%) Calibration accuracy 1.5 K (3σ) radiation Calibration accuracy 10 ppm (3σ) spectrum Quantization bits 13 bits

1650 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC used together with AGRI for AMV height assignment. Figure 13 shows the rmse of temperature retrievals for 1-km layers and RH retrievals for 2-km layers from simulated FY-4A GIIRS radiances and radiances having the same characteristics of the GOES Sounder. The retrieval algorithm is based on the one-dimensional variational (1DVAR) approach (Li and Huang 1999; Li et al. 2000). The simulated FY-4A GIIRS radiances are degraded with an assumed observation error and then inverted into soundings. The rmse is calculated by comparison between the “true” profiles used in the Fig. 11. AIRS, CrIS, IASI, IRS, and GIIRS spectral coverage.

Fig. 12. (top left) The temperature Jacobian from FY-4A GIIRS longwave IR band, (top right) water vapor mixing ratio Jacobian from midwave IR band, (bottom left) ozone mixing ratio Jacobian from longwave IR band for a U.S. standard atmosphere, and (bottom right) a BT spectrum and NeDT at 250, 280, and 300 K.

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1651 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC radiance simulation and the retrieved profiles. The local severe storm that occurred on 7–8 August 2010 results indicate that the FY-4A GIIRS soundings will in Zhou Qu, China, which caused more than 1,400 improve upon the current GOES Sounder retrievals deaths and left another 300 or more people missing. for temperature and relative humidity. With the FY-4A GIIRS, atmosphere instability can Li et al. (2012) have summarized several poten- be continuously monitored in real time for storms tial applications of high-temporal-resolution and that have not been anticipated by NWP like the one high-spectral-resolution IR data from the literature. occurring on 6–7 August 2013 in Beijing, which was For example, Sieglaff et al. (2009) showed that the not anticipated in the numerical weather forecasts. spectral “online” and “offline” absorption features This storm produced a very uneven distribution of in the IR window region of the spectrum are related precipitation with heavy local rainfall accompanied to low-level temperature and moisture. Schmit et al. by hail and gusts of 14–24 m s–1; Pinggu, Miyun, and (2008) demonstrated that the equivalent potential Shunyi, China, experienced heavy rainfall. The high- temperature differences between 800 and 600 hPa resolution Rapid Update Cycling Data Assimilation can be a useful indicator of thunderstorm potential. and Forecasting System at the Beijing Meteorological Li et al. (2011) noted that the advanced IR sounder Bureau, version 2.0 (BJ-RUCv2.0) NWP (Chen et al. is able to depict an unstable region similar to the 2014) at 3-km resolution forecasted 24-h precipitation “truth” field in a simulation using an International accumulations of only 30 mm in the northwestern edge

H2O Project (IHOP) case; equally important is that of Beijing and totally missed the heavy precipitation the atmospheric stability derived from an advanced over the city area. With FY-4A GIIRS measurements, IR sounder may suggest the region of stable air im- the forecasts (location, time occurred, QPE, and more) portant for reducing false alarms when forecasting could be improved with better moisture initialization convective events. in the NWP model (Li and Liu 2009; Liu and Li 2010). In another study, Li et al. (2012) showed that the For the same storm, another important indicator derived atmospheric stability indices such as con- is the warning of the preconvective environment. The vective available potential energy (CAPE) and lifted FY-2E 11-µm BT image indicates that the storm devel- index (LI) from geostationary advanced IR sounders oped at 1500 UTC, while the simulated FY-4A GIIRS may provide critical information 1–6 h before the LI indicates that the atmosphere is extremely unstable development of severe convective storms, such as the at 1200 UTC, 3 h before the storm. Figure 14 shows the simulated FY-4A LI (color) at 1200 UTC along with the FY-2E 6.8-µm BT image at 1500 UTC. The European Centre for Medium- Range Weather Forecasts (ECMWF) analysis was used in FY-4A GIIRS retrieval simulation. A large unstable region (yellow and red) was identified before the severe storm development.

THE FY-4A LMI. The FY-4A LMI will be the first lightning detection sensor on Chinese satellites. LMI will be able to detect the presence of total lightning activity (in-cloud and cloud- to-ground lightning), which is useful for early predic-

Fig. 13. (left) Simulated temperature at 1-km-layer rmse and (right) RH at tions of storms and severe 2-km-layer rmse for FY-4A GIIRS and the current GOES sounder over the weather events (Schultz et al. China region. 2009; Gatlin and Goodman

1652 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC 2010; Stano et al. 2014). The specific parameters of Table 9. The performance of LMI on board FY-4A. LMI, similar to that of the GOES-R Geostationary Lightning Mapper (GLM; Goodman et al. 2013), are Spatial resolution About 7.8 km at SSP shown in Table 9. Sensor size 400 × 300 × 2 LMI will measure the total lightning activity Center wavelength 777.4 nm over China continuously day and night. The spatial Bandwidth 1 nm ± 0.1 nm resolution is 7.8 km at nadir. The LMI’s 400 × 600 Detection efficiency >90% pixel charge-coupled device (CCD) camera will op- False alarm ratio <10% erate at 777.4 nm to count flashes and measure their Dynamic range >100 intensity. False alarms are nonlightning artifacts generated in the processing of LMI data due to natural or Signal-to-noise ratio >6 anthropogenic causes. To deal with these false alarms, Frequency of frames 2 ms (500 frames per second) a set of filtering algorithms have been developed to Quantization 12 bits categorize them as dedupe, ghost, lollipop, track and solar flares, and so on. A surface validation system is built to carry out a comparison of LMI flashes with Measuring Mission (TRMM) Lightning Imaging surface total lightning observation data. To meet the Sensor (LIS) and GOES-16 GLM. Data from the 10% requirement on false alarms, the FY-4 LMI will ground-based lightning network in China and LIS combine a set of signal enhancements to retrieve equipped on TRMM (Albrecht et al. 2016) have been the lightning signal from the CCD data flow. These combined to generate simulated LMI proxy data for enhancements include 1) spatial filtering by matching algorithm development and product evaluation. The the instantaneous field of view of each detector to proxy data were generated as follows (Finke 2011): the typical cloud-top area illuminated by a lightning stroke, 2) spectral filtering by using a narrowband 1) According to the position and intensity of a interference filter with a 1-nm bandwidth and cen- “strike” (just like the return stroke of a cloud-to- tered at 777.4 nm to enhance the lightning signal from ground flash), the position and time of optical the background, 3) 2-ms integration on the focal plane pulse associated with the strike are generated. to enhance the radiation signal of the lightning over The optical pulse parameters (size and energy) the background, and 4) utilizing the Real-Time Event are generated using a random number generator Processor (RTEP) to carry out background subtraction that depends on a distribution function. and lightning event pickup. In addition to these, we 2) The photons are generated according to the pa- will also build a set of false-alarm-filtering algorithms rameters (size and energy) of each optical pulse. to decrease false events in the L1B data flow. 3) The output of the detected event data are gener- The LMI’s Level 2 algorithm identifies “group” ated according to the pixels with energy above a and “flash” from Level 1 geolocated time-tagged detection threshold. lightning event data; a tree-structured algorithm will be developed that clusters optical events into groups Figure 14a shows the distribution of photons. and groups into flashes as used for Tropical Rainfall Figure 15b shows the expanded bottom-right corner

Fig. 14. Simulated LI (left) from FY-4A GIIRS at 1200 UTC and (right) from FY-2E 6.8-µm WV BT image at 1500 UTC.

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1653 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC of Fig. 15a. Figure 15c shows the distribution of the There are 4,721 optical events (radiance is the sum of accumulated radiance of “optical events.” Figure 15d every optical event, in units of μJ m–2 sr–1); those are shows the expanded bottom-right corner of Fig. 15c. filtered and clustered to 25 flashes and 363 groups.

Fig. 15. Detected lightning events generated from proxy data: (a) a simulated storm in an area of 10° × 10° with the photons (black dots) and optical events (red squares) during 1 h, (b) zoom-in of the bottom-right corner of (a),(c) accumulated radiance of detected events for a simulated storm distribution for an hour on 16 Aug 2007, and (d) zoom-in of the bottom-right corner of (c). The units of (c) and (d) are μJ m−2 sr−1.

1654 | AUGUST 2017 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC The different colors indicate the intensity of radiance field vector will give a better understanding of the of the optical events. dynamic processes of particles near the geosynchro- The LMI products will be used to identify risk nous orbit. Another component of SEP is a magne- areas for convective storms by detecting total tometer that measures the magnetic field vector in lightning and to improve warnings regarding severe the range of ±400 nanotesla (nT). It consists of two storm hazards, convection precipitation, and light- triaxial fluxgate sensors and the associated electron- ning strike alerts. The LMI data will be integrated ics. The electronics are inside the spacecraft, and the with other observations (satellite, radar, in situ) sensors are mounted on a 6-m deployable boom, with and models; it will be used for applications like cell one sensor at the tip of the boom and the other one tracking and QPEs. It will also be used to research located 1 m inboard. The dual-sensor configuration lightning-produced NOx, to study the Earth’s electric will enable a separation of stray field effects generated field, to accumulate a long-term database useful for by the spacecraft from the ambient space magnetic tracking decadal changes of lightning, and to as- field. The measurements are the sum of the ambi- sess the impact of climate change on thunderstorm ent space field and stray fields originating from the activity. spacecraft; the difference between two sensors can be considered to originate from the spacecraft and thus THE FY-4A SPACE ENVIRONMENT the ambient space field can be inferred. PACKAGE (SEP). Geostationary satellites are The magnetic field products from FY-4 have vulnerable to space weather events such as energetic various purposes, both operational and scientific. particles damage and severe geomagnetic distur- The products can be used to evaluate the level of bance. Therefore, it is necessary to monitor and geomagnetic activity and the solar wind dynamic forecast the near-Earth space environment condi- pressure, to estimate the magnetopause crossings and tions. The SEP on FY-4A consists of energetic particle shocks, to provide input to the space weather fore- detectors and a magnetometer that will be used for in casting model, to provide a database for improving situ monitoring of the near-Earth (at geostationary knowledge of the magnetosphere and solar–terrestrial altitude) space environment for the National Center interactions, and last, but not least, to process the for Space Weather. The energetic particle detectors pitch-angle production after combination with the will measure the energetic particle environment in energetic electron data. orbit. Electrons will be measured over the range of 0.4–4 MeV. Protons will be measured over the SUMMARY AND CONCLUSIONS. FY-4A, range 1–165 MeV and over 165 MeV. The detectors launched on 11 December 2016, represents an will also give a directional observation of particle improved and new capability of the Chinese flux from multidirectional sensors mounted on the geostationary weather satellite system. With ad- three-axis-stabilized satellite platform. The space vanced imaging and sounding instruments on board particle environment in geosynchronous orbit is FY-4A providing high temporal, spatial, and spectral dynamic and composed of trapped particles, solar resolution measurements, the benefit is expected to energetic particles, and a cosmic-ray background. be large for severe weather monitoring, warning, and These energetic particles could cause spacecraft forecasting. With the first lightning imager on board surface and deep dielectric charging, single event the Chinese geostationary satellite, the added valuable upsets (SEUs), electronic component degradations, lightning information is expected to significantly and other effects. Some measurements will continue improve warnings of severe storm hazards, convec- to be used for operational alerts and warnings of tion precipitation, and lightning strikes. A primary potentially hazardous conditions. For example, the use of the AGRI and GIIRS data will be to improve energetic proton flux (>10 MeV) alert will be issued to NWP through data assimilation of both radiances civil aviation users that need to consider the polar cap (AGRI, GIIRS) and L2 products (TPW, LPW, and absorption induced by the solar proton events. The AMVs from AGRI). Those data will be assimilated energetic electron flux (>2 MeV) has been used as the in the operational Global and Regional Assimilation proxy that indicates the possible levels of electrostatic and Prediction System (GRAPES) models and will discharge in spacecraft instrumentation. In addition, also be distributed to the user community for opera- the energetic particle measurements have also served tional applications. Assimilation of data and derived as the basis for postevent analyses and study of the products from the AGRI, GIIRS, and LMI in both space environment. The pitch-angle distribution global and regional NWP models is expected to show calculated from the directional flux and the magnetic valuable improvement in forecast skill. FY-4A will

AMERICAN METEOROLOGICAL SOCIETY AUGUST 2017 | 1655 Unauthenticated | Downloaded 10/08/21 08:18 AM UTC also enhance space weather monitoring and warning. potential contribution to GMES. Space Res. Today, Together with the new generation of geostationary 168, 19–24, doi:10.1016/S0045-8732(07)80046-5. weather satellites planned by the international sat- Dong, C., and Coauthors, 2009: An overview of a new ellite community, the FY-4 series will become an Chinese weather satellite FY-3A. Bull. Amer. Meteor. important geostationary component of the global Soc., 90, 1531–1544, doi:10.1175/2009BAMS2798.1. Earth-observing system. Finke, U., 2011: Statistics of LIS data used for proxy data generation for the future geostationary lightning de- ACKNOWLEDGMENTS. The authors thank the tector. Proc. XIV Int. Conf. on Atmospheric Electricity, BAMS Editor Timothy J. Schmit for carefully reviewing the Rio de Janeiro, Brazil, International Commission on manuscript. The three anonymous reviewers are thanked Atmospheric Electricity. for their valuable comments on improving the manuscript. Gatlin, P. N., and S. J. Goodman, 2010: A total light- The authors also would like to thank Drs. Xiang Fang, Min ning trending algorithm to identify severe thun- Min, Wenguang Bai, Chunqiang Wu, Danyu Qin, Xiaoxin derstorms. J. Atmos. Oceanic Technol., 27, 3–22, Zhang, Lei Yang, Jian Shang, Xiaohu Zhang, Jiawei Li, doi:10.1175/2009JTECHA1286.1. and Dongjie Cao of the National Satellite Meteorological Goodman, S. J., and Coauthors, 2013: The GOES-R Center (NSMC) for their assistance on tables and figures geostationary lightning mapper (GLM). Atmos. Res., for this manuscript. Dr. W. Paul Menzel and Dr. Jun Li of 125–126, 34–49, doi:10.1016/j.atmosres.2013.01.006. the Cooperative Institute for Meteorological Satellite Stud- Huang, M., and Coauthors, 2013: Impact of Southern ies (CIMSS) provided valuable input and suggestions. 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