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PROGRESS ON METEOROLOGICAL SATELLITE AND SATELLITE METEOROGY IN CHINA

 

XU Jianmin, FANG Zongyi and GUO Lujun

National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China

ABSTRACT

The meteorological satellite has got great developments since its first launch. Under such condition, the activities for meteorological satellite data receiving, processing, distributing, archiving, and especially the application have been largely expanded throughout the world.

In addition to the applications of weather forecast and climate monitoring, the meteorological satellite is also extensively used in the ecological and environmental monitoring. It plays a great role in the disaster monitoring, such as forest fire, flooding, blizzard fatality etc., Nowadays the meteorological satellite has become a very important part of the Earth Observation System.

In this articale, it just provides a brief introduction to the latest activities of Chinese meteorological satellite system, its products and applications. We wish reader could have a general idea on the work we have done in the recent years through the article.

Key words:  meteorological satellite, FY-1 satellite, FY-2 series satellite, FY-3 series satellite, application

 

I.  SATELLITE SYSTEM

The Chinese meteorological satellite program involves both polar orbiting and geostationary satellite series. The main objective of the program is to establish a comprehensive operational meteorological satellite system, as well as a ground monitoring and application system in order to meet the demand of various sectors in China.

The meteorological satellites of China are named as Feng-Yun (abbreviated as FY), which stands for "Wind and Cloud" in English. The odd number series FY-1, FY-3, etc., is to indicate the polar orbiting satellite series, while the even number, i.e. FY-2, FY-4 is for the geostationary series.

1.  China's First Generation of Polar Orbiting Meteorological Satellites: FY-1

According to the current plan, China's first generation of polar orbiting meteorological satellite system, FY-1, consists of four satellites, as well as the corresponding ground data acquisition, processing and application systems.

(1)  FY-1C and FY-1D

The FY-1C and FY-1D satellites are developed on the basis of the previous experimental meteorological satellites FY-1A and FY-1B. Besides the foreseen improvement on the reliability of the satellites, there are some changes in the imaging instrument and data transmission as follows:

(a) The number of channels of the Visible and Infrared Radiometer is increased to ten, enabling more useful observation over the land and ocean.

(b) The on-board satellite data storage capacity is increased to 300 min (60 min for FY-1A and B only), making it possible to acquire once per day the global CHRPT data of four pre-selected channels with 4-km resolution (defined as Delayed Global Picture Transmission-DGPT), as well as 20 min of ten-channel original resolution data at any region of the world (defined as Delayed Local Picture Transmission, DLPT).

(c) The FY-1C and FY-1D's High Resolution Picture Transmission is very similar to the NOAA/HRPT, except for the data transmission rate. It means that the systems receiving and processing NOAA/HRPT data can receive and process FY-1 satellite data with just a little modification. The data transmission rate is 1.3308 Mbps, double that of current NOAA/HRPT. The transmission modulation is PSK and bit format is split phase.

(d) The designed life time of FY-1C/D is two years.

(e) There is no APT in FY-1C and FY-1D.

The instantaneous field of view of the radiometer is 1.2 mrad and the resolution at the satellite sub-point (SSP) is 1.1 km. The scan rate is 6 lines per second and the total pixels of each scan line are 2048. The channel features of the main payload on FY-1C and FY-1D are indicated in Table 1.

Table 1.  The Channel Characteristics of MVISR Onboard FY-1C and FY-1D

Channel

Wavelength (mm)

Primary Use

1

0.58-0.68

Daytime cloud, ice and snow, vegetation

2

0.84-0.89

Daytime cloud, vegetation

3

3.55-3.95

Heat source, night cloud

4

103.-11.3

SST, day/night cloud

5

11.5-12.5

SST, day/night cloud

6

1.58-1.64

Soil moisture, ice/snow distinguishing

7

0.43-0.48

Ocean color

8

0.48-0.53

Ocean color

9

0.53-0.58

Ocean color

10

0.90-0.985

Water vapor

 

(2) Current status of FY-1C and FY-1D

FY-1C polar orbiting meteorological satellite, carrying a ten-channel radiometer as the primary sensing instrument, was launched on May 10, 1999. The FY-1C satellite weighs about 950 kg. The two solar cell arrays mounted on both sides of the main body make the total length of the satellite 8.6 m. The attitude of the satellite is three-axes stabilized with a precision of no less than 1 degree in all three axes. FY-1C operates in a sun-synchronous orbit with the orbit parameters listed in Tables 2 and 3.

Table 2.  Orbit Parameters of FY-1C Meteorological Satellite

Satellite

FY-1C

Launch date

May 10,1999

Orbit

Sun-synchronous

Altitude (km)

863

Period (min)

102.332

Inclination (deg)

98.79

Eccentricity

<0.00188

Descending Node (LST)

08:34

Average Power Output (W)

229

Design Life (year)

 2

Attitude Control

Three-axis stabilized

 

Table 3.  CHRPT Parameters of FY-1C

CHRPT transmission frequency

1708.0 MHz (1704.5 MHz as backup)

DPT transmission frequency

1700.0 MHz

EIRP

39.4 dbm

Polarization

Right hand circular

Modulation

PCM-PSK

Modulation index

67.5 o ± 7.5 o

Bit rate

1.3308 Mbps

 
 
 

FY-1C has worked for nearly four years since its launch. It is still in a good condition except a little attenuation in the IR channels. FY-1C is in operation now and many products are produced, some products are under development. FY-1C products are now used in everyday weather forecasting and environmental monitoring in China.

FY-1D satellite was launched on May 15, 2002. It has come into operational mode after a few months on-orbit test. The structure of FY-1D satellite is similar to FY-1C.

2. Geostationary Meteorological Satellite Program of China

China launched the first geostationary meteorological satellite FY-2A on June 10, 1997. Then the second geo-satellite was launched on June 25, 2000. At present the main operational satellite is the FY-2B, it is located at 105oE. The satellite is now in a limited operation due to a malfunction in its upper converter. It provides 28 images a day and temporarily puts out of operation during the satellite eclipse time for a special maintenance.

FY-2 satellite data are open to international users, shareable to all countries. User stations within the FY-2 coverage can receive S-VISSR high resolution digital data and WEFAX low resolution analog data.

(1)  Specifications of FY-2 satellite and the radiometer

(a) Functions of the satellite

FY-2 meteorological satellite has the following functions:

l         Obtaining visible, infrared and water vapor images by a radiometer onboard satellite. Sea surface temperature, cloud analysis chart, cloud parameters and wind vectors can be derived from these data.

l         Collecting and transmitting observed data from widely dispersed data collection platforms.

l         Broadcasting S-VISSR data and WEFAX

l         Monitoring space environment.

 

Table 4.  FY-2 Satellite Specifications

 
 

Dimensions

Diameter

Height

2.1 m

1.6 m (cylinder )

Mass

Launch

On Station

1200 kg

520 kg

Life span

Designed

3 years

Orbit

Geostationary

located at 105oE

Attitude

Spin-stabilized, Spin rate

100±1 rpm

Launch Vehicle

Long March-3

 

 
 
 

(b) Visible and infrared spin scan radiometer

The major payload of FY-2 meteorological satellite is the Visible and Infrared Spin Scan Radiometer (VISSR). The characteristics of the instrument are shown in Table 5.

Table 5.  Major Characteristics of VISSR
 

 

Visible

Infrared

Water Vapor

Wavelength

0.5-1.05 mm

10.5-12.5mm

6.2-7.6mm

Resolution

1.25 km

5 km

5 km

FOV

35 mrad

140 mrad

140 mrad

Scan Line

2500×4

2500

2500

Detector

Si-photo-diode

HgCdTe

HgCdTe

Noise Performance

S/N=6.5 (albedo=2.5%)

S/N=43 (albedo=95%)

NEDT=0.5-0.65 K

    (300 K)

NEDT=1 K

 (300 K)

Quantification Precision

6 bits

8 bits

8 bits

Scan step angle

140 mrad (N-S scanning)

 

 

Frame time

30 minutes

 

 

 
 

The VISSR performs the Earth observation from the space to obtain visible, infrared and water vapor images of the Earth and the clouds. The VISSR scans to collect through the Optical Telescope the energy emitted from the Earth and clouds, then focuses the energy onto the Focal Plane by the primary and secondary mirrors. The Visible Fiber Optics and Infrared Relay Optics System relay the energy from the Focal Plane to the visible, infrared and water vapor detectors. Si detectors convert visible light into visible analog signals and HgCdTe detectors, cooled by radiation coolers, convert the Earth's radiation into infrared analog signals. The S-VISSR output is sent to a VISSR Digital Multiplexer (VDM) unit with redundancy.

l        Visible Channel (0.55-1.05 mm)

Four Si detectors and redundant sets simultaneously convert visible light into four-channel visible analog signals of 1.25 km resolution at the sub-satellite point (SSP) with one west-east scanning.

l         Infrared Channel (10.5-12.5 mm)

High sensitive HgCdTe detectors with redundancy, which are kept at a temperature of 100K by the radiation cooler, convert Earth radiation into infrared analog signals with 5 km resolution images at SSP.

l         Water Vapor Channel (6.3-7.6 mm)

Extremely sensitive HgCdTe detectors with redundancy, which are kept at a temperature of 100 K by the radiation cooler, convert Earth radiation into infrared analog signals with 5 km resolution images at SSP.

l         Imaging

A complete 20 o×20o scan covering the full Earth disk can be accomplished every 30 min by means of combination of satellite spin motion (100 rpm from west-east) and step action of the scan mirror (2500 steps from north to south). It takes 25 min for taking picture, 2.5 min for mirror retrace, and 2.5 min for VISSR stabilization.

(2)  FY-2 ground application facilities

The FY-2 ground system consists of the following parts: A Command and Data Acquisition Station (CDAS), a Data Processing Center (DPC), a Satellite Operation Control Center (SOCC), Ranging Stations (one primary station, three secondary stations including one in Australia), widely dispersed Data Collection Platforms (DCP), Medium-scale Data Utilization Stations (MDUS) and Small-scale Data Utilization Stations (SDUS), and a Ground Communication System etc.

The tasks of FY-2 ground system are as follows:

l         To receive day and night cloud, water image data from VISSR;

l         To produce a variety of images and products after processing by DPC;

l         To receive, edit, and distribute meteorological, oceanographic, hydrological observation data collected by DCP;

l         To retransmit stretched VISSR data and WEFAX;

l         To extract information of solar protons and other particles from telemetry data stream and distribute them to users;

l        Satellite operation management and control, VISSR scan mode selection and satellite status monitoring.

(3)  Data broadcasting

One of the major functions of FY-2 system is to broadcast data including S-VISSR, WEFAX and S-FAX data via FY-2 satellite.

The S-VISSR data are transmitted to the Medium-scale Data Utilization Station (MDUS) through the FY-2 during the VISSR observation. WEFAX data are retransmitted to Small-scale Data Utilization Station (SDUS).

(a)  Transmission characteristics of FY-2 S-VISSR

The S-VISSR data are the digital image data originated from VISSR on board satellite and are stretched at CDAS in time. The transmission rate is reduced. The S-VISSR data are retransmitted to MDUS via the FY-2 during the VISSR observation. The signal characteristics of FY-2 S-VISSR data are as follows:

 
 

Frequency:

1687.5 MHz

Modulation:

PCM/BPSK, NRZ-M

Bit rate:

660 Kb/s (fixed)

EIRP:

57+1 dBm

Polarization:

Linear

Bandwidth:

2 MHz

Data Volume:

329.872 bits/line (including SYNC code)

Data Coding:

Byte complimenting and PN scrambling

 
 

Since the signal characteristics of FY-2 S-VISSR data are the same as GMS S-VISSR data except for frequency, the user stations for receiving GMS S-VISSR data can also receive FY-2 S-VISSR data by changing the antenna direction and frequency of local oscillator.

(b) Transmission of the FY-2 WEFAX

The WEFAX is disseminated to SDUS users via FY-2 satellite. The WEFAX transmission format is completely compatible with those of other geostationary meteorological satellites in service.

The WEFAX is composed of gray scales, marks, annotation and earth image. The annotation signal is inserted at the head of the picture, so as to recognize the image information automatically. The Earth images contain latitude-longitude grids and coastline bases of the prediction of the satellite's orbit and attitude.

(4)  The FY-2 data collection system

There are 133 data Collection Platform (DCP) channels in FY-2 system, including 100 regional DCP channels and 33 international DCP channels, which can collect data from a wide variety of platforms. The regional DCPs are stationary DCPs that installed on buoys, isolated islands, rivers, mountains or ships for meteorology, oceanography, hydrology and other purposes. The collected data are edited at the NSMC and distributed to the user via GTS.

3.  Future Plan

(1)  Considerations on development of FY-3 series satellite

FY-3 series, the second generation of Chinese polar orbiting meteorological satellites is now in design phase, it is expected that the first satellite be launched in 2004. The main mission objectives of FY-3 are:

l         To provide global sounding of 3-dimensional atmospheric thermal and moisture structures and the cloud and precipitation parameters to support global numerical weather prediction.   

l         To provide global images to monitor large scale meteorological and/or hydrological disasters and biosphere environment anomaly.

l         To provide important geophysical parameters to support study on global change and climate monitoring.

l         To perform data collection.

To achieve above-mentioned objectives, a meteorological core payload with eight main instruments and two complementary instruments is considered as follows:

 

l         The Imaging Mission

 
 

VIRR

Visible and Infrared Radiometer

MODI

Moderate Resolution Visible and Infrared Imaging Spectroradiometer

MWRI

Microwave Radiation Imager

 
 

l         The Sounding Mission

 

IRAS

InfraRed Atmospheric Sounder

MIRS

Multi-channel InfraRed atmospheric Sounder (stage-II)

MWTS

MicroWave atmospheric Temperature Sounder

MWHS

MicroWave atmospheric Humidity Sounder (stage-II)

SBUV/TO

Solar Backscatter Ultraviolet/Total Ozone Sounder

 

l         The Complementary Mission

 
 

ERBU

Earth Radiation Budget Unit

SEM

Space Environment Monitor

 
 

(2)  FY-2 series satellite

In order to meet the need of weather forecast and global climate change research, China plans to develop 3 successive satellites: FY-2C, D, and E, with necessary improvements on the basis of the two experimental satellites FY-2A and 2B. It is expected that FY-2C will be launched in April 2004, FY-2D in 2007 and FY-2E in 2010.

The function of FY-2C, D and E is similar to FY-2 A, B, it includes:

l         Acquiring visible, infrared and water vapor cloud images;

l         Transmitting S-VISSR images and low resolution images;

l         Data collecting;

l         Space environment monitoring.

(a) Major improvement for FY-2C, D and E

The number of spectral channels of Visible and Infrared Spin Scan Radiometer (VISSR) will be increased from 3 to 5.

l         The infrared long wave window 10.5-12.5μm will be split into two channels :10.3-11.3μm and 11.5-12.5μm, so as to improve the capability of detecting and calculating water vapor contents, to support semi-transparent ice cloud detecting, and to have a better accuracy of atmospheric absorption correction in order to improve sea temperature estimation.

l         To increase the temperature resolution of the infrared channels and the signal/noise ratio of the visible channels, and to support the application of the split window.

l         To have an additional 3.5-4.0μm mid-infrared window channel. As this channel is less affected by water vapor contents, when it combines with IR long wave window channel, more accurate surface temperature can be acquired. The channel is sensitive to heat temperature therefore it is helpful for detecting warm targets on surface. It is also used to obtain information of low-level cloud and fog. It is a good help to distinguish low-level cloud and ice and snow coverage.

l         The data quantization level of the IR and WV channel will be increased from 256 to 1024.

Other changes

The S-Fax broadcasting function will be cancelled and the frequency of 1699.5 MHz will not be used. The WEFAX will be replaced by LRIT. And the power supply of the satellite will be increased.

bSpecifications of VISSR of FY-2C/D/E

Spectral channels of VISSR are shown in Table 6

Table 6. The Spectral Channels of VISSR
 

Channel

Wavelength (μm)

FY2 A,B

FY-2C ,D, E

VIS

0.501.05

0.50-0.75

IR1

10.512.5

10.3-11.3

IR2

 

11.5-12.5

IR3

 

3.5-4.0

WV

6.37.6

6.3-7.6

 

The major characteristics of VIS channels are shown in Table 7.

 
 
Table 7. The characteristics of VIS channels of VISSR
 

Item

Characteristics

FY-2 A,B

FY-2 C,D,E

Wavelength (μm)

0.50-1.05

0.50-0.75

FOV(μr ad)

40

35

Space resolution (km)

1.44

1.25

Dynamic range

0-95%

0-98%

S/N

6.5 (2.5%)

1.5 (0.5%)

 

43 (95%)

50 (95%)

Number of detectors

4 (main) + 4 (alternate)

4 (main) + 4 (alternate)

Quantization level

64

64

Calibration

cool-space images and solar image to realize in-orbit calibration

  same as FY-2 A,B

 

The major characteristics of IR, WV channels are shown in Table 8.

Table 8.  The Characteristics of IR, WV Channels of VISSR
 

 

FY-2 A,B

FY-2 C,D,E

IR

WV

IR1

IR2

IR3

WV

Wavelength(μm)

10.5-12.5

6.3-7.6

10.3-11.3

11.5-12.5

3.5-4.0

6.3-7.6

FOV (μrad)

160

160

140

140

140

140

Space resolution(km)

5.76

5.76

5

5

5

5

Dynamic range

180-330 K

190-290 K

180-330 K

180-280 K

Temperature resolution

0.6 K

1.0 K

0.4-0.2 K

0.4-0.2 K

0.5-0.3 K

0.6-0.5 K

Number of detectors

1(main)+

1 (alter)

1(main)+

1 (alter)

1(main)+

1 (alter)

1(main)+

1 (alter)

1(main)+

1 (alter)

1(main)+

1 (alter)

Quantization level

256

256

1024

1024

1024

1024

Calibration

Onboard blackbody calibration, once every 3 disks

The ground calibration accuracy is 1K.Cool space and planet calibration is used for on-board calibration, once every 2 disks.

 
 
4.  Satellite Products

Following are the satellite products of NSMC.

.
 
 
Table 9.  Image Products of FY-2C/D
 

Product

Coverage

Times/day

Requirement

Accuracy

Stretched full disk image

Satellite coverage

28

After the third scan line

Image registration

Line: 1/4 pixel

Channel: 1/8 pixel

Location: 1-2 IR pixel

Calibration: 1.5-2.0K

Nominal image

Centered at

105oE, 0oN

24

Within 10 min. after observation

Location: <1 IR pixel

Image over China

Lambert projection,

its four points as: 48N-62E, 52N-142E, 12N-81E, 13N-128E

24

As nominal image

As nominal image

 
Table 10.  Digital Products of FY-2C/D
 
 

product

coverage

Times/day

requirement

Accuracy

Cloud wind vector

50oN-50oS, 55oE-155oE

4

After observation

6-8 m/s

Sea surface temperature

50oN-50oS, 55oE-155oE

8

After observation

1-1.5oC

Outgoing long-wave radiation

50oN-50oS, 55oE-155oE

8

After observation

Similar to MTSAT

Tropical cyclone location

West of 150oE over Pacific Ocean, Indian Ocean

24

After observation

Operational standard

Dust storm monitoring

China

8

After observation

Similar to NOAA product

 
Table 11.  Products of FY-1C/D Satellite over World
 

No

Product

Resolution

Coverage

Times/day

Accuracy

1

Data set for LDPT in

1A.5 and 1B level

1 km

Selected region

in the world

6

1 km

2

Data set for GDPT in

1A.5 and 1B level

4 km

Global coverage

6

4 km

3

Projection data set for high resolution local coverage over the world

1 km

Selected region

in the world

On request

1 km

4

Low resolution clear sky data set

4 km

Global coverage

On request

4 km

5

Stereo-graphic projection Mosaics

8 km

hemisphere

2

4 km

6

Mercator projection mosaics

8 km

45oN-45oS

2

4 km

7

Sea surface temperature

50 km

Global coverage

2

±1.5o

8

Vegetation index

4.16 km

Global coverage

2

4 km

9

Cloud parameter

50 km

Global coverage

2

±1 km (height)

±1.5o (amount)

10

Out going long-wave radiation

50 km

Global coverage

2

7W/m2

 
Table 12.   Products of FY-1C/D Satellite over China
 

No

Product

Resolution

Coverage

Times/day

Accuracy

1

Data set for CHRTP in 1A.5 and 1B level

1 km

China and surrounding region

7+14

1 km

2

High resolution clear sky data base over China  

1 km

China and surrounding region

2+4

1 km

3

Mosaics of Eurasia

4 km

Eurasia

2

2 km

4

Stretched single orbit image

2 km

Eurasia

7+14

2 km

5

Forest fire monitoring

1 km

China

7

1 km

6

Soil moisture

<10 km

China

1

±15%

7

Sea ice

1 km

North China Sea

1

1 km

8

Snow coerage

1-4 km

China

1

1 km

9

Monitoring of snow disaster

1 km

China

On request

1 km

10

Outgoing longwave radiation

50 km

China and surrounding region

2

7 W/m2

 
 
Table 13.  Sounding Products of NOAA Satellite
 

No

Product

resolution

coverage

times/day

accuracy

1

Atmospheric temperature of 15 standard levels

(1000—10hPa)

75km

China and surrounding region

2

0.1K

2

Geopotential height  of

15 standard levels

(1000—10hPa)

75km

China and surrounding region

2

m

3

Dew-point temperature of 6 standard levels

(1000-300hPa)

75km

China and surrounding region

2

0.1K

4

Direction of thermal wind of 6 standard levels

(850-100hPa)

75km

China and surrounding region

2

Degree

5

Speed of thermal wind

of 6 standard levels

(850-100hPa)

75km

China and surrounding region

2

M/S

6

Index of atmospheric stability

75km

China and surrounding region

2

0.01%

7

Total water vapor content  in the atmospheric column under clear sky

75km

China and surrounding region

2

0.01mm

8

Total ozone content in the atmospheric column

75km

China and surrounding region

2

0.01dB

9

Cloud amount

75km

China and surrounding region

2

0.01%

10

Pressure on cloud top

75km

China and surrounding region

2

hPa

11

Temperature at cloud top

75km

China and surrounding region

2

0.1K

12

Brightness temperature of 19 HIRS/2 channels

75km

China and surrounding region

2

0.0K

13

Brightness temperature of 4 MSU channels

75km

China and surrounding region

2

0.1K

 
 

II.  RESEARCH AND APPLICATIONS

 

The observation ability of meteorological satellite has got a remarkable development since the end of last century. It provides a basis for the further research on meteorological satellite data application and service. In this chapter, it introduces some results on the applications of both Chinese and foreign meteorological satellites in China.

1. Meteorological Applications

(1)  Weather analysis and forecast

Meteorological satellite imagery is one of the most effective methods for revealing the evolution of weather systems. With the increase of sensor channel and the enhancement of detecting ability, the research on its application is growing continuously. 

Through the analysis of 293 mesoscale convective systems (MCS) occurring in the Tibetan Plateau from June to August in 1994, it reveals: (1) Most of the MCS occurred in the region east of 80oE, their moving paths were mainly eastward. (2) Most of the severe convective systems had the meso-ß-scale features and 90.4% of them had a life time from 3-9 h (among which 67.2% from 3-6 h). Besides, these cloud clusters had an obvious daily variation feature, 94.3% of them occurred between 15-17 LST. (3) Most of the MCS were with shower and some of them even with lightning.

A study on the seasonal and daily variation, as well as the moving rule of the convective cloud system over the Tibetan Plateau was made with the GMS TBB data (8 times/day, 1981-1994) and NOAA OLR data (twice/day, 1978-1994). It is found that the convective cloud system had an obvious daily variation in summer. It was weak in 00-05UTC and strong in 15-17UTC. There were three lower TBB centers in the central (30-32oN, 90oE), east (30oN, 99oE) and west (30oN, 85-87oE) parts of the Plateau when the monsoon occurred during July to August. With a multi-year average, the height of cloud top in the convective center could be up to 9.6 km while in some regions the cloud top height could even reached 13 km on the 10-day average. The study also presents that the convective cloud normally generated in the east part of the Tibetan Plateau and then moving eastward steadily. It reached the west end of the Plateau in the end of July.

The study on TBB data shows the convective cloud cluster that generated in Tibetan Plateau and with lower TBB value were mostly moving eastward to the mid and lower reaches of the Yangtze River and brought heavy precipitation to the region. It reveals that the generation of convection cell in the Plateau is closely related to the vertical structure of the upper divergence and low level convergence. The eastward moving of these cloud systems is favored by the steering of upper and low level jets.

The TBB data were also used to analyze the heavy precipitation happening in the mid and lower reaches of the Yangtze River in the summer of 1998. The result indicates that the storm rainfalls from June 11-26 and August 1-18 were closely related to the eastward MCS while the heaviest storm rainfall of the period (July 20-21) was caused by the activity of local rainfall clusters.

The cloud clusters of heavy rainfall and thunderstorm over North-China were analyzed with the satellite data of summer of 1998 in a study. It shows that these two kinds of cloud clusters have the obvious difference in their generation, development and moving. For example, the moving of thunderstorm cloud cluster is with a typical propagation feature while the moving of heavy rainfall cloud cluster is mainly by the steering of environmental airflow. Besides, the severe convective system with the thunderstorm cloud cluster is caused by the unstable flow and strong vertical wind shear, and the heavy precipitation associated with the heavy rainfall cloud cluster is the result from deep warm and wet condition in the mid and low level of troposphere, continuous ascent movement as well as the effect of upper jet etc.

In a study of high density cloud moving wind, it reveals that the wind flow field at the upper troposphere is quite different for developed and undeveloped tropical cyclone. For the undeveloped tropical cyclone, it only has an eastward wind in the upper troposphere while for the developed tropical cyclone, its outflow in the upper troposphere normally has several directions.

(2)  Application on numerical forecast model

With the limited accuracy of atmospheric character from meteorological satellite and the limitation of processing ability in handling the initial value of numerical forecast model, it just had little progress in the application of meteorological satellite data in numerical forecast model for a long time. Up to end of last century, the abilities in both satellite sensor and computer handling have been largely enhanced, thus it makes a great improvement in the application of meteorological satellite data in the field of numerical forecast model.

It firstly sets up a statistical relationship between satellite multi-channel radiation value and the moisture distribution of atmosphere with the analysis. Then the satellite obtained brightness temperature is converted into moisture field. It has got a great improvement when the high time and spacial resolution satellite data with mesoscale information are put into the mesoscale model.

On a research, the satellite TOVS data are assimilated and put into MM-5 model with Nudging Method. Based on this, many studies have been done. Such as:

The objectivity and reliability of Plateau analysis as well as the precipitation prediction ability are improved with the insertion of the assimilated data into initial field. Based on the Wuhan Spate of July 20, 1998, it reveals a MCS mesoscale front convective system in the large scale Mei-yu system. The mesoscale front convective system often makes heavy rainfall for the region. The process of Wuhan Spate occurred in July 20, 1998 is successfully simulated with one hour interval TBB data from geostationary meteorological satellite and the Nudging Method. It shows the main facts for causing the spate are the low mesoscale vortex and the low southwest jet.

With the three-dimension variational system developed by China, cloud moving wind data are assimilated into regional numerical forecast model and has got good result.

For assimilating TOVS radiation value into numerical model directly, it should have an operator between satellite value and model variate. In the field of atmospheric IR remote sensing, this is called as radiative transfer equation. With the RTTOV5, the contributions of radiative feature and cloud parameter to the error of RTTOV5 simulation were analyzed by calculating and contrasting the in-site data. This provides a basis for the directly assimilation of three and four dimension variation for the satellite radiation dada.

(3)  Snow cover remote sensing with multi-sensor data

Snow cover is an important water resource on the Earth. It is a critical factor relating to climate and global change. In order to study and understand the impact of snow cover on climate and hydrologic budgets, it is necessary to have long term information on the variation and distribution of snow cover.

Snow cover remote sensing has special meaning in China. 40% of Chinese territory is grass covered, and nearly half of this grassland is pasture distributing mainly in Tibet, Qinghai, Xinjiang and Inner Mongolia areas where people lives on breeding animals, such as cattle and sheep, from which large amount of meat, milk and fur is produced. But frequent snow disasters during winter and early spring seasons bring serious damage to lives and properties of local people. Because of the sparse population and less developed communications in these areas, satellite remote sensing becomes the only way to provide information on snow, such as the extent of snow cover, the places where a snow disaster is likely to occur and the severity.

Since late 1980s, methods for snow cover remote sensing have been developed in NSMC. A great deal of information on snow is provided each winter. Since Dec. 1996, an operational system for snow cover monitoring over China with NOAA/AVHRR data has been set up. Based on the analysis of the spectral characteristics between snow, cloud and other types of earth surface with AVHRR data, a multi-channel thresholds test method is worked out to separate snow from cloud. With a spatial resolution of 0.05°´0.05°, pixels covered with snow and the other land surface types are discriminated for China and the surrounding areas. By composite processing using satellite data from every ten days, a cloud free data set with the maximum snow cover information is able to acquire, and snow cover area in each province is calculated and analyzed.

Since the launch of FY1-C, NSMC has been calculating the snow cover information with the MVISR radiometer data. Based on the fact that snow reflects visible radiation more strongly than it does in the middle-infrared spectral regions, the Normalized Difference Snow Index (NDSI) is calculated from the reflectance of MVISR channel 1 and channel 6. This index is an effective discriminator for snow and cloud for the fact that the reflectivity of cloud remains high with MVISR channel 6, and drops nearly to zero with channel 1. FY1-C data played a very important role in snow disasters monitoring in Xinjiang and Inner Mongolia in winter 2000.

(4)   Fog area detection with meteorological satellite data

Fog is a kind of weather phenomenon that has influences on traffic. The increasing traffic has raised high requirement for fog detection and forecasting. The distribution of meteorological observation network over land is insufficient to detect fog. Meteorological satellite has many advantages for fog detection.

During daytime, when it is free of high-level cloud, fog and low-level cloud are easily observed on the visible satellite imagery. Fog top is smooth, edge sharp but irregular, and frequently bounded by terrain features. The difficulty in detecting fog and low-level cloud at night with infrared imagery arises from the similarity of temperature and texture shown by fog, cloud and the underlying surface.  It is found that cloud emissivity observed with shorter infrared band is significantly lower than the longer infrared band due to either water droplets or ice particles in the cloud. Thus, we select the brightness temperatures of a long wave channel and a short wave channel, to calculate the difference that is sensitive to the presence of fog and low cloud.

Our research data come from NOAA/AVHRR, FY-1C, D/CHRPT and GMS data. At daytime, we use reflectivity at different visible channels and brightness temperature and brightness temperature difference between different infrared channels (3.7 and 11.0 mm or 11.0 and 12.0 mm) to detect fog. While in the night we use three infrared channels to calculate brightness temperature at infrared channels and differences between them. According to different terrain and atmospheric conditions, we set up a set of threshold values to detect fog. At last, use other observing data to verify detecting results. The analyzed examples showed that our method performed fine. If there have high or middle clouds above the fog, the detection methods fail. These methods still need further improvement at the distinction between fog and very low cloud.

(5)  Automatic navigation of FY-2 geostationary meteorological satellite images

Parameters and coordinates used in FY-2 spinning geostationary meteorological satellite image navigation are derived, with emphasis on attitude parameters. It is noticed that in the time series of sub-satellite line count, there is information on the direction of spinning axis of the satellite. With this information, the automatic landmark matching routines get convergence quickly, and quality control of the routine performance becomes an easy job.

An automatic image navigation system for FY-2 geostationary meteorological satellites have been developed in NSMC. The system is based on a PC Workstation running Windows 2000. The orbital parameters, attitude parameters, misalignment parameters and beta angle parameters are turned out automatically and routinely without any manual operation. Image navigation quality of FY-2 geostationary meteorological satellites was improved.

2.  Natural Disaster and Environment Monitoring

Satellite meteorological application in natural disaster and environment monitoring has become a focal point in recent years. In the area, the FY-1C polar orbiting meteorological satellite provides an evident contribution. For many years, the meteorological satellite natural disaster monitoring system located in the National Satellite Meteorological Center is working in the daily operational mode.

(1)  Natural disaster monitoring

(a) Forest and grassland fire monitoring

NOAA-12, 16, 17 and FY-1C/D are the major data source in monitoring forest and grassland fire. AVHRR channel 3 of FY-1 and NOAA satellites is used to detect hot spots. The major forest and grassland areas susceptible to fires are divided into 15 sectors, covering the most part of forest and grassland regions in China. During the fire season (in the North China, the fire season is spring and autumn, and in the South China fire is likely to occur in winter), we receive and process all NOAA and FY-1 satellites data passing the monitored area. The fire monitoring products are generated if a fire spot is detected. The products include the list of fire spot location, which indicates the latitude and longitude, provincial, division, and county name, the nature of land utilization (like forest, grassland, crop field, etc.) of fire spot; the multiple channel composition image, which shows the fire information, like active fire, burned and non-burned area, smoke, cloud and water body. The products are disseminated to the relevant government department, including the National Forest Administration, Agricultural Ministry and local provincial government agency. During a year, about 1000 fires can be spotted in the average.

(b) Flood monitoring

China uses FY-1 and NOAA satellite data to monitor the flood in daily operational mode. The monitored regions include seven major rivers, sub-divided into 14 sectors. For example, all FY-1C and NOAA-14 orbits passing the monitored area in daytime were received and processed from May to September of 2000. The information of water body was derived from multiple channels of AVHRR data, and several methods were used to delete the influence of thin cloud and fog over the water body. The historical database was used to compare with the water body derived from the current image. The product image were generated and disseminated to the relevant government departments after the flooded water body was detected. The information of flood monitoring includes the rage, size and nature of land utilization of flooded water body.

(c) Snow disaster monitoring

FY-1C/D and NOAA-12, 16, 17 data are used to monitor the snow disaster in the operational mode in the winter. The FY-1C/D data is useful in this aspect. The AVHRR channel 6 of FY-1C/D is efficiently used to distinguish the snow coverage and lower cloud. The major product of snow monitoring includes:

Ten days Composition
This product covers national wide area with the resolution of 6 km, the product uses NOAA afternoon satellite data and started from 1997.
Regional Snow Disaster Monitoring

The 8 regions where snow disaster may easily happen in the country are monitored in operational mode in daytime during winter season. The information of snow cover in each region is derived from FY-1C/D data everyday from the early of winter season. The composite multiple scene images are generated to show how long the snow coverage remained in certain area. The administrative boundary and grassland distribution are overlapped on the composite multiple scene image.

(d)  Duststorm monitoring

North China is easy to be attacked by duststorm weather processes in the spring of each year. For example, 11 duststorm weather processes were caught and analyzed with the satellite data in the year of 2000. The result shows that for the Beijing region the dust is mainly from the Inner Mongolia Autonomous Region and Hebei Province. This information is provided to the related Governments Departments and Provinces for the planning of environmental protects.

According to the users' requirement, two types of duststorm monitoring and forecasting techniques are developed.

l         One of them is to use polar orbiting meteorological satellite data, which has the advantage of high spectral and spatial resolution. But as the time resolution is not good enough for the timely monitoring, it is suitable for the manually analysis and forecasting.

l         The other technique is to accept geostationary meteorological satellite data, it is more practical and valuable in the automatic dust storm monitoring and forecasting with the good time resolution and the spilt window technique and multispectial technique. The automatic dust storm monitoring and forecasting system is on the operational running in NSMC, its accuracy is over 80%.

(2)  Environment monitoring

(a) Sea Ice Monitoring

The sea ice monitoring in the Bohai Sea in the north part of China is carried on with FY-1 and NOAA satellite during the winter season. This application started from 1988. During winter, sea ice monitoring is performed everyday using FY-1C/D and NOAA-16/17 data, and the derived products are transmitted to the users. The products include the edge line of sea ice, the size and density of sea ice, and the temperature contour lines on the sea ice and sea surface.

(b) Environment Change

Analysis is made using FY-1 and NOAA satellite data to look into the variation of snow coverage, water body and vegetation growth in West Part of China over 10 year's time. The preliminary result shows that in the certain area of the West Part of China, the permanent snow coverage, water body and vegetation coverage were shrunken during the past ten years. This information is useful for the study of environment changing.

(c) Vegetation Growth Monitoring

In the past few years, severe draught happened in the northern China, especially in the northeast part. NDVI derived from FY-1 was used to assess the influence of draught on crops. We used the regional ten-day NDVI composition in July and August of 1999 and 2000 to compare the difference.  The land utilization database was also used to refer to the crop field, grassland and forest, etc. In this way the effect on the crop field and grassland by the draught is revealed. This product is provided to the local and provincial meteorological agencies and it is found to be useful in evaluating the drought situation.

3.  The China Radiance Calibration Site of Remote Sensing Satellite (CRCS)

The application of quantitative technologies is a mile-store for the development of satellite remote sensing. The key point of this technology is the radiance calibration of the sensor onboard satellite. As we know, the sensor has an attenuation during its life time and it is pretty difficult to make the on-orbit calibration. For solving this problem, it needs a ground site with good radiometric feature and clear atmosphere to make the on-site radiance calibration. With this radiance calibration site, the satellite sensor can be accurately calibrated via synchronous measurement when it passes over the area.

For selecting a suitable place for the Radiance Calibration Site, it has made several surveys and analyses in Northewest China since 1994. The Dunhuang Gobi Desert and Qinghai Lake were chosen as the land radiance calibration site and water surface radiance calibration site respectively then. The construction of China Radiance Calibration Site of Remote Sensing Satellite was completed in 2001.

(1)  The calibration sites

The operation of the China Radiance Calibration Site of Remote Sensing Satellite is managed by the National Satellite Meteorological Center of China Meteorological Administration. It is an international calibration site with advanced equipment and good environment condition.

The Dunhuang calibration site is for absolute radiance calibration for visible, near IR and short wave IR band sensors. It is in the southwest of Gansu Province (to the west of Dunhuang City), with a location of 40.1No, 94.3Eo. The size of the calibration field is 30 km×40 km.

The Qinghai Lake site is for absolute radiance calibration for thermal IR band and the absolute radiometric calibration of low reflectance target in visible and near IR band. It is in the Northeast of Qinghai Lake of Qinghai Province, with a location of 37No, 100Eo. The size of the test site is 4685 km2.

(2)  Field experiment at the test site

The comprehensive field experiments were made at the China Radiance Calibration Site of Remote Sensing Satellite (CRCS) in summer of 1999 and 2001 respectively. In the experiments, the ground reflectance and bi-direction reflectance (BRF) as well as the atmospheric aerosols optical depth were acquired at the Dunhuang test site. Besides, the brightness temperature and off-water radiance atmospheric aerosols optical depth were also obtained at Dunhuang test site. At same time, the brightness temperature, off-water radiance and atmospheric attenuation were measured at the Qinghai Lake test side.

(3)  Measuring result analysis

The measured ground reflectance results show that the Dunhuang site's ground average reflectance is between 10% and 35% from visible to short wave infrared range. The reflectance standard deviation is less than 0.02 at the 20×20 km2 region while it is less than 0.01 at the 500×500 m2 region. The analysis of above data represents that the Dunhuang site's optical uniformity is very good. The reflectance is less than 5% in the VIS band at the water surface of Qinghai Lake, it means that the water in the lake is very clean.

With the data acquired by sun photometer at Dunhuang site and the calculation of langley method, the aerosols optical depths were estimated. It is from 0.10 to 0.18 at 0.55μm wavelength and Junge parameter is about 0.26 at Dunhuang site.

These data show that the atmosphere over the sites is clean and the aerosol type is approached to desert model at Dunhuang site. From the results at Qinghai Lake, it presents a very clean atmosphere and belongs to continent aerosol model. In addition, the water vapor contents around the sites were also estimated.

(4)  Synchronous satellite-ground measurement

A synchronous measurement from both satellite and ground was made at the test site in June 1999 for the on-orbit radiometric calibration. The calibration coefficients from seven channels of FY-1C (center wavelength: 455 nm 505 nm 555 nm 630 nm 866.5 nm 932.5nm 1610 nm) were determined. An error budget of the reflectance-based calibration method shows that the uncertainty is 6%. Comparing the calibration results with the pre-launch calibration, a better agreement at five channels is achieved except the ones in channels 9 (555 nm) and channel 6 (1610 nm).

In addition, the on-orbit various radiometric calibrations for three satellites' sensors (FY-1C, FY-2B, CBERS-1) were also performed in August-September, 2000. Comparing the calibration results of FY-1C in 2000 with that of 1999, it is found the sensitivity of sensors is attenuated, especially at channel 1 (0.58-0.68 mm) which has an attenuation of more than 30%. By on-orbit radiometric calibration in 2000, the calibration coefficient is updated.

In June of 2000, an aerial experiment was made at Dunhuang site. In order to validate the meteorological satellite data, the field investigations and measurements were made at the Inner Mongolia. In the experiment three targets were selected which include grassland, lake and sand.

Up to now, the China Radiance Calibration Site of Remote Sensing Satellite has made the on orbit calibrations for many domestic and foreign remote sensing satellites which include: FY-1C, FY-1D, FY-2B, CBERS-1, GMS-5.

4.  The Development of EOS Data Receiving and Processing System

The first satellite in a new generation of environmental satellite EOS-AM1 was launched in December 1999. With various kinds of new instruments, it makes a comprehensive observation on the land and sea surface characters, cloud, radiation, aerosol and radiation balance etc.

To make a good use of EOS satellites data, NSMC started to develop the data receiving and processing system of EOS-TERRA/MODIS in June of 2000. The system was completed in December 2000. At present the system has been put into operation. It can receive EOS-TERRA/MODIS data and generate the projection image. The system has made its contribution to the dust storm warning and flood monitoring etc.

REFERENCES

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