The newly available Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) data set was used to retrieve cloud amount, cloud optical depth, cloud particle phase and size, cloud temperature, surface temperature, surface broadband albedo, radiation fluxes and cloud forcing in the Arctic for the period 1982-1999. The spatial and temporal distributions of those retrieved Arctic climate parameters together with an analysis of their seasonal and interannual variability, especially surface and cloud properties are presented here. The present study indicates that the Arctic has been warming in spring, summer and autumn, the decadal rates are 1.1°C degree, 0.68°C degree and 0.70°C degree, respectively. While in winter the Arctic has been cooling at the decadal rate of -0.34°C degree. The Arctic surface broadband albedo also signals the warming trend of the Arctic at the decadal rate of -3.0% at the confidence level of 98.8% in autumn, indicating a longer melt period and later freeze-up. Results also show that the Arctic has become cloudier in spring and summer, but less cloudy in winter.

For the months July and August, 144 AVHRR images were pre-processed for 1990, 1992, 1994, 1996 and 1999 with a NOAA pre-processing chain (NOAA-CHAIN). A differencing method was applied to estimate the change of the NDVI between different years. The trend lines for six typical region’s NDVI average values in each year were subsequently analyzed. The vegetation condition of most of the regions in the Northwest of China is poor. From 1990 to 1999, most regions have negative NDVI difference values. Concomittantly, locally, some regions show positive NDVI differences, indicating that the vegetation conditions in the regions where an increase occurs, more or less improve. The most largely increasing region with regards to vegetation growth conditions mainly include the North and West of the Xingjiang Province, e.g., the Aertai Mountains, Tacheng, Kelamayi, north of Shihezi, the region between Shihezi and Kuerle, Yining, Akesu, Lanzhou and Dingxi of the Gansu Province. The trend lines of the first three typical regions show an upward path while those of the last three regions a downward one. Comparing the slopes of the six trend lines, it is indicated that the decrease in NDVI range is larger than the NDVI increase for the Northwest of China.

The advection and dispersion of Asian dust events during 2000-2002 from China to the Pacific Ocean around Japan were investigated using meteorological satellite data, NOAA/AVHRR and GMS-5/VISSR. Aerosol Vapor Index (AVI) images, taking the brightness temperature difference between 11 micron and 12 micron, are very effective to monitor the Asian dust phenomenon in the east Asia region, because of their capacity for night-time detection. The remarkable dust events during 2000-2002 were classified into three types based on the weather patterns: 'Dry Slot' type, 'Wedge of High Pressure' type, and 'Travelling High' type.

The east part of Weibei of Shaanxi province situated in Loess Plateau semi-arid and arid region. The soil texture of this area is very loose and easy to cultivate so it is an important planting crops area. In this area the change of precipitation is very large, the drought often come about, so dynamic monitoring the range and extent of drought will have important significance. This area has so much gully that the topography is very complexion the basis of crops` growing period, this study have established a remote sensing drought monitoring model for this area by using data of NOAA/AVHRR and the meteorological observation data through applying stepwise regression method. This model has been used to dynamically monitor the spring drought in 2002. The monitoring results show that the model can express the spatial distribution with different drought levels, as well as various drought degree. The multiple correlation coefficient of drought monitoring result and the relative moisture of the soil run up to above 0.9. and the accuracy of the estimations of drought in this area is higher than only using thermal inertia method or vegetation supply water index method. The model has better prospect in applying.

In order to reduce the human labor in snow cover monitoring, recent study has been done on modification of the multi-spectral thresholds method which was developed in NSMC in 1996. Based on the analysis of the spectral characteristics of snow, cloud and other types of earth surface with multi-spectral data, an automated processing system with the new thresholds method to distinguish snow and cloud have been set up in NSMC. The devised technique is applied to multi-spectral data from FY-1C and NOAA-16 for mapping snow cover over China during winter season. To assess performance of the modification, the automatically produced snow data sets have been compared with the NOAA operational snow products and validated against in situ land surface observations in China. There is a good consistency between our results, NOAA snow data and ground measurements. The correlation coefficient between the snow cover produced by NSMC and NOAA is about 80%. The results of the comparison show us that the 1.6µm band data is very useful for snow and cloud distinguishing. The new method can reduce the human labor in snow cover monitoring and produce accurate snow cover images in China using FY-1C and NOAA-16 satellite data.

Baiu season is the most important precipitation period to the climate of east China. It is often raining day after day with mixed type of precipitation over large area and lasting almost one month. The estimation of 3hr mean areal precipitation over SHIGUANHE catchment during Baiu season by use of GMS IR technique is present here. For getting better estimation of heavy rain, a multilayer feed-forward Artificial Neural Network (ANN) is introduced by training sample pairs of TRMM PR radar and GMS image on raining points and simulating the network in a relative small area nearby and short time span. Parts of raining points estimated by GMS IR method are modified by the output of the network according to data quality. Case studies over one or three consecutive swaths of PR show that the standard deviations of rainfall estimation increase after heavy rain modification while the correlation coefficients between rainfalls estimated and measured by ground based radar keep almost the same before and after data correction.

Seasonal changes in global cloud cover have been monitored with multi-spectral observations from the eleven polar orbiting HIRS (High resolution Infrared Radiation Sounder) since December 1978. The HIRS longwave infrared data have a higher sensitivity to semi-transparent cirrus clouds than visible and infrared window techniques. Clouds are found in 71% of all HIRS observations from 65 S to 65 N; high clouds are observed in 33% of the observations. Closer investigation of the tropics indicates that there has been little overall change in the global total cloud cover. There is the possibility of a small increase in high cloud cover from the first decade to the second (about 1%) however orbit drift of some sensors and instrument differences may be part of this. Significant weather events such as El Nino Southern Oscillation or volcanic eruptions may also be influencing the trends. Since 2000, the Moderate resolution Imaging Spectro-radiometer (MODIS) is starting to generate another cloud data set that must be understood and connected with the HIRS cloud data; early indications are promising that MODIS will be a more than worthy successor to the venerable HIRS.

The Canadian Meteorological Centre’s (CMC) three Dimensional Variational (3D-var) is an incremental analysis system that is currently used by both our global and regional models with very little modifications. During the last few years, it has undergone a series of upgrades from isobaric to a terrain-following coordinate, and most importantly the direct assimilation of satellite radiances. The quality control (QC) of observations was also upgraded to a variational quality control whereby the data rejection/acceptance decisions are taken consistently during the minimization problem. In terms of radiance data, the system currently uses so-called raw level-1b AMSU-A that are QC, and bias controlled by the data user and not the producer. The QC and thinning algorithms of the radiance data are more complex and system dependent, but their impact on analyses and forecasts are very large and now comparable to the radiosonde data in the SH. The resolution of NWP forecast/analysis systems is forever increasing and so is the volume of data from various instruments. The volume of satellite data has become quite a challenge even at the level of ingest and QC. One aspect of NWP systems which definitely can benefit from this additional data is the moisture analysis. In that context we have started to experiment with the ingest of water sensitive radiances from the HIRS and AMSU-B instruments onboard NOAA-15 and NOAA-16. As will be shown, the quality of both the temperature and moisture analyses are significantly improved when using these additional satellite data. Preliminary evaluations from 10-day forecasts indicate marked improvements in Quantitative Precipitation Forecast (QPF).

With incremental form of three-dimensional variational (3D-Var) method as data assimilation method and the MM5 mesoscale model as both assimilation and prediction model, NOAMSUA experiment, where only radiosonde observations were assimilated, was in comparison with AMSUA experiment, where radiosonde observations and AMSU-A channel brightness temperatures were assimilated simultaneously. The comparison results show that direct assimilating AMSU-A data has a positive impact on model prediction as a whole.

This paper addresses using satellite data for nowcasting severe storms in the 0-6 hour time frame. Weather, and weather related phenomena extend across a broad range of scales. In meteorology the link between the synoptic scale and the mesoscale is many times a key factor in controlling the intensity of local weather. The only observing tool capable of monitoring weather across those scales (and those scales interactions) is the geostationary satellite! Just as imagery from polar orbiting satellites helped advance understanding of synoptic scale phenomena, imagery from geostationary satellites is advancing our understanding of the mesoscale. A number of important discoveries using geostationary satellite imagery have had a dramatic impact on mesoscale meteorology and, in turn, our ability to provide short term forecasts and warnings for disaster related weather events, including: areas of incipient squall line development; location of regions with high probability of tornadoes and severe thunderstorms; mesoscale convective complexes; and, areas with heavy convective rainfall. As exciting as current capabilities are, satellite systems that will come into being during the next several years will provide capabilities well beyond the present ones.

The first GOES (Geostationary Operational Environmental Satellite) Users' Conference, focusing on the GOES-R Series was held from May 22 through 24, 2001 in Boulder Colorado, with approximately 200 participants from government, the private sector, academia and the international community. GOES-R is planned to be launched in 2012. The conference was organized by the National Oceanic and Atmospheric Administration (NOAA), with cooperation of the National Aeronautics and Space Administration (NASA), the American Meteorological Society (AMS), the National Weather Association, the World Meteorological Organization (WMO), and the National Institute of Standards and Technology (NIST). The goals of the conference were: (1) to inform GOES users of plans for the next generation capabilities; (2) to provide information on the potential applications; (3) to determine user needs for new products, data distribution, and data archiving; (4) to assess potential user and societal benefits of GOES capabilities; and (5) to develop methods to improve communication between the National Environmental Satellite, Data, and Information Service (NESDIS) and the GOES user community. Sessions included: (1) planned and potential sensors for U.S. geostationary satellites; (2) user requirements, applications, and potential benefits from future GOES; (3) future international geostationary satellites; and (4) communications, ancillary services and training issues. The third day of the conference consisted of facilitated breakout sessions in which the user community provided input to ten questions on their future needs for products, services, data distribution, archiving, training and potential benefits of the next generation GOES to their operations and to society. A second GOES Users' Conference will be held in Boulder, Colorado from October 1 to 3, 2002. This paper will provide a summary of the recommendations provided by the first GOES Users' Conference and some expectations of topics to be covered at the second conference. A brief summary of a new requirements generation process that incorporates input from both conferences will also be provided.

The Advanced Baseline Sounder (ABS), now named Hyperspectral Environmental Sounder (HES) is being designed for future Geostationary Operational Environmental Satellites (starting with GOES-R in 2012). ABS/HES will have thousands of channels with widths on the order of single wavenumber, while the current GOES sounder has only 18 bands with widths on the order of tens of wavenumbers. With high temporal resolution (better than 1 hour), high spatial resolution (better than 10 km), high-spectral-resolution (better than single wavenumber) and broad coverage (hemispheric) ABS/HES measurements will enable monitoring the evolution of detailed temperature and moisture structures in clear skies with high accuracy (better than 1 C root mean square) and improved vertical resolution (about 1 km); the current GOES sounder yields roughly 3 km vertical resolution. Considerations for ABS/HES instrument definition are described. Temperature and moisture retrievals from simulated current GOES radiances and future ABS/HES radiances with required instrument noise contained were compared with the true profiles; results show the large improvement of ABS/HES moisture retrievals over the current GOES sounder. Trade-off studies are conducted to demonstrate the optimal spectral coverage of ABS/HES design and the impact of instrument noise on sounding retrieval.

The Advanced Baseline Imager (ABI) is being designed for future Geostationary Operational Environmental Satellites (starting with GOES-R in 2012). As with the current GOES Imager, this instrument will be used for a wide range of qualitative and quantitative weather and environmental applications. The ABI will improve over the existing GOES Imager with more spectral bands, higher spatial resolution and faster imaging (and more geographical areas scanned). The ABI will improve the spatial resolution from nominally 4 to 2 km for the infrared bands and 1 to 0.5 km for at least one visible band. There will be a five-fold increase of the coverage rate. The ABI expands the spectral band number from five to at least 12. Up to 18 bands on the ABI are being investigated. Every product that is being produced from the current GOES Imager will be improved with data from the ABI.

Estimation of the primary variables describing atmospheric state, namely, temperature, moisture and wind, using space-based observations continues to lead to improved delineation of atmospheric conditions. Errors in the estimation of temperature moisture and wind from these observations, for global, regional and mesoscale applications, have been reduced as the spatial temporal and spectral resolution of these observations has increased. Reduction in the errors has also been greatly assisted by improvements in numerical weather prediction (NWP) models, data assimilation methods and continuing increases in computer power. This paper describes the progress, showing results from recent operational sounding and image data. It presents examples of both the improvements in the estimation of the primary analysis variables and the resultant benefits to NWP from these improved data. The importance of satellite direct readout for providing timely data for regional applications where short data cut-off times are present is also noted. The paper also records the important role of in international collaboration in these activities, and describes the key role played by the International TOVS Working Group (ITWG) and more recently by the International Winds Workshop. The ITWWG first met in 1983 and since then the International TOVS Study Conferences (ITSCs) have become a forum for the exchange of information related to atmospheric sounding. Twelve ITSCs have been held, the next one will be in Beijing in 2003. The ITWG has been responsible for the generation and sharing of community software for ingest, preprocessing and application of operational and research sounding data. Without this software much of the recent research and applications related to atmospheric sounding, would not have occurred. Another important role of the ITWG is the provision of guidance and recommendations to agencies involved in atmospheric sounding related areas, such as data collection, frequency protection, data preprocessing, data application and distribution. Key areas considered by the ITWG include NWP, climate monitoring and global change and radiative transfer. In short the activities of the ITWG have been pivotal in the effective collection, processing and application of sounding data will continue to be so for the foreseeable future. Importantly the coming years will bring several new sounders (both infrared and passive microwave) on polar and geostationary satellites, and this will further consolidate the requirement for worldwide cooperative work.

Water vapor is one of the most significant green house effect gases. A monitoring of water vapor behavior with operational satellite is important to investigate the global changes. Water vapor usually exists at lower troposphere. However, precipitable water is a key property to comprehend the variation since sometimes humid air mass moves to the upper troposphere. Using split window channel data with optical sensors such as AVHRR and VISSR, several retrieval algorithm has been proposed and among them, transmittance ratio method has been often utilized. However, the approach is still controversial because some studies concluded it was available and others not. We investigated the availability of the method with split window channels' data of GMS-5/VISSR on a semi-continental scale. A calibration curve of the precipitable water with radiosonde observation had been made in course of the retrieval procedure. However, the calibration curve are hardly sensitive to the precipitable water. Numerical simulations were carried out for the possible condition, and it turned out that calibration was insensitive to precipitable water under some condition at all: larger water water variation for a given surface temperature range within a given region. The results of a feasibility study will be discussed.

To enable frequent estimates of land surface temperature (LST) from satellite measurements, and to obtain the surface temperature diurnal cycle, two new algorithms are applied to observations from the Geostationary Operational Environmental Satellite (GOES) and the polar orbiting imager NOAA/AVHRR. Results are evaluated against a wide range of ground observations. Evaluations against the Atmospheric Radiation Measurement (ARM) observations and observations within an RMS accuracy of about 1-2 K, standard error of about 1 K and bias of less than 1 K. LSTD from the GOES can be implemented well to the NOAA/AVHRR with the right algorithm.

A quasi real time system for estimate of the surface solar flux is introduced. The system will start to be operated in this year, and provide the solar flux until tomorrow’s morning. The system uses 0.09-degree resolution products from the GMS-5 image data of CEReS, Chiba Univ. It also uses the six-hourly atmospheric objective analysis data from the Japan Meteorological Agency. The solar flux is estimated at each pixel. This system includes four steps to estimate the surface solar flux. (1) The first step discriminates cloud pixel from clear one. The adopted method is similar to ISCCP, in which the reference Tbb for discrimination is created by data before and after the target day. In this system, it is impossible to use tomorrow’s data, because real time operation is needed. Therefore historical data is used to create the reference. (2) Cloud pixel is analyzed using 11/12 micron split window methods and 6.7 micron channel. The methods determine that the pixel is water or ice cloud, and derives the optical thickness for ice cloud. (3) The optical thickness for water cloud is retrieved from the reflection method using visible channel with assumption of the effective radius. (4) Cloud optical thickness and atmospheric information is converted to the surface solar flux from the package RSTAR5B for radiation transfer calculation. The surface solar flux using typical pixels from 0.5-degree grid area had been already derived. A comparison of satellite derived solar flux and the surface observation shows fair result in clear sky days, and overestimate in cloudy days.

A Chinese Energy and Water Balance Monitoring System (CEWBMS) has been run for more than two years in China National Satellite Meteorology Center (CNSMC), which uses geostationary satellite GMS-5/FY-2 S-VISSR image to generate a set of surface energy and water balance parameters including precipitation, global radiation, net radiation, actual evapotranspiration, potential evapotranspiration, relative evapotranspiration and climate and soil moisture index at al. in daily or decade base. The validations show good coincidence with ground measurements and demonstrated the CEWBMS products are meaningful and reliable. An investigation for the potential application of the relative evapotranspiration in drought monitory also has been done. It shows a good coincidence between the detected drought by CEWBMS relative evapotranspiration and the real drought situation and indicates the relative evapotranspiration of CEWBMS may have widely application in drought monitory.

The algorithm for retrieving atmospheric temperature, moisture, and total column ozone using the Moderate Resolution Imaging Spectroradiometer (MODIS) longwave infrared radiances is presented. The operational MODIS algorithm performs clear sky retrievals globally over land and ocean for both day and night. The algorithm is based on a regression and has an option to follow the statistical retrieval with a nonlinear physical retrieval. The regression coefficients are determined from an extension of the NOAA-88 data set containing more than 8400 global radiosonde measurements of atmospheric temperature, moisture and ozone profiles. Evaluation of atmospheric products is performed by a comparison with data from ground-based instrumentation, geostationary infrared sounders, and polar orbiting microwave sounders. MODIS moisture products are in general agreement with the gradients and distributions from the other satellites, while MODIS depicts more detailed structure with its improved spatial resolution.

In this paper, author will firstly discuss the possibility of detecting earthquake precursory by means of NOAA data application on the basis of analysis of the conventional earthquake predicting, and further analysis the problems of earth surface temperature and factors related to earthquake on the earth-surface form energy transmission equation and put forward the modify split windows algorithm to inverse the earth surface temperature in earthquake region. Finally author used the NOAA/AVHRR satellite data to inverse the ground surface temperatures (night) before and after Chinese Zhangbei earthquake (Ms6.2). The result indicated that the ground temperatures before 20 days earthquake was a drop trend. Only 3 days before earthquake, the ground temperature in epicenter just began to go up. Entire temperature changing submitted to a drop tendency.

During the course of weather modification by airplane on March 14, 2000, the polar orbit meteorological satellite real time remote sensing offer us some proof for artificial stimulation of precipitation. We analyze the truth of catalyst diffusion after the airplane flying and discuss the wind transportation for catalyst, the effect of artificial stimulation of precipitation on the ground. The preliminary result: (1) After the course about 1 hour 23 minutes, the maximum random movement diffusion width is 11km, the catalyst’s random movement diffusion area is about 2505km², and there has a sunk area about 1505 km³ on the top of the cloud. (2) According to the analysis of satellite data, the effected area by wind transportation is about 7500 km², it is 3 times to the random movement diffusion area. And this is the key factor of catalyst diffusion.

MODIS measurements contain the striping signals in the longwave infrared bands because MODIS is a multi-detector sensor. We describe a wavelet method for recovery of MODIS data from its stripe signals. Our work is organized into four broad sections. Section 1 will introduce wavelet shrinkage method for de-noising noisy data, compare the character of the wavelet method and the FFT method in de-noising processing. The objective of section 2 is to find out the scale of MODIS stripe by the wavelet analysis for MODIS stripe data using continuous wavelet transforms. Section 3 analyses Stripe data pattern for the MODIS level 1B stripe data, present the wavelet shrinkage method for MODIS level 1B data. Section 4 will provide a comparing for MODIS cloud product and atmospheric profile product between the original data and de-striped data. We can find that there’s been an improvement in MODIS cloud product and atmospheric profile product after de-striping. And we can get more understanding for the stripe regular pattern.

Based on discrete-ordinate-method radiative transfer in multiple scattered theory, the solar direct and scattering radiation with observation band (0.29~3.0 µm) on 5 layers have been computed using the retrievals of Tiros Operational Vertical Sounder (TOVS) in clear/cloud sky over southeast China. The errors between the computed values of solar direct and scattered radiation derived from TOVS and that from radiosond data are then given. The purpose of this research is to show if the satellite measurements (TOVS DATA) can be directly used to estimate spatial distribution of solar radiation with observation band.

It is essential to have qualitative information of a satellite instrument, images observed by the instrument, etc. The purpose of this presentation is to verify the degree of infrared (IR) detectors deterioration of the Visible Infrared Spin Scan Radiometer (VISSR) on the fifth Geostationary Meteorological Satellite (GMS-5). The International Satellite Cloud Climatology Project (ISCCP) calibration results and GMS-5 VISSR/IR raw counts of infrared channels were statistically studied. The degradation and uncertainty (noise level) were estimated from 1995 to 2001. As the result, the three GMS-5 infrared channels show no significant trend over the study period except the unstable conditions of the first year. In the end, a comparison between SST observations and brightness levels at cloud-free points is suggested as a possible verification technique.

n order to studying long-term climate variability and globe environment change, Solar Total Irradiance Monitor (STIM) is constructed planed to aboard on FY-3 sun-synchronous polar orbit weather satellites. STIM is made up of three same absolute radiometers, which are similar with Solar Irradiance Absolute Radiometers (SIAR). We designate one radiometer as revising radiometer. It works only one day once one or two months to demarcate the drift of the other two radiometers. Solar irradiance is measured when the sun scans over the field of view of the absolute radiometers, respectively. The irradiance measurement is carried on at the position near the North Polar after the satellite move out the shade of the earth. SIAR is electro-calibrated cavity absolute radiometer. SIAR-1 had completed The Ninth International Pyrheliometer Comparisons (IPC-IX) with World Radiometric Reference (WRR) in Physikalisch-Meteorologisches Observatorium Davos /World Radiation Center (PMOD/WRC), Switzerland from 25 September to 13 October 2000, the comparison results showed that SIAR-1 is 0.078% higher than WRR. So SIAR-1 was given a WRR calibration factor 0.99922. Where after, we compared STIM with SIAR-1, and draw a conclusion: that the absolute accuracy of STIM is better than 0.2%.

Meteorological satellite are widely used to monitor forest and grassland fire in China and other developing countries in recent years as its AVHRR sensor with middle infrared channel are very sensitive to hot spot. However, some new issues recently in this application need be considered: the forest department want more information from satellite remote sensing, like the condition of a fire, not only location of fire spot; from NOAA-K, the mid-infrared channel (3.7µm) closed at daytime, that give much difficulty to detect forest fire by using meteorological satellite; EOS/MODIS sensor has more channel and higher resolution in ground surface monitoring. This paper introduces some improved method for detecting and evaluating the conditions of forest and grassland fire by using multiple channel data from meteorological and environment satellite data, These methods includes: a, Evaluating the sub-pixel size and temperature of fire spot by using multiple channel data of AVHRR in polar meteorological satellite in various condition, including. The way of multiple channel combination are: mid- infrared (3.7µm) and thermal infrared (11µm) channel; near infrared (1.6µm) and thermal infrared (11µm) channel; two long infrared (11µm and 12µm) channel. And also introduce the means of presentation for evaluation result. b. Detecting the hot spot in the condition without mid- infrared channel data, includes: using two thermal infrared (11µm and 12µm)channel data from AVHRR; using near infrared (1.6µm) and thermal infrared (11µm) channel data from AVHRR. c. Some features in fire monitoring by using multiple channel data of EOS/MODIS.

The 36 channel Moderate Resolution Imaging Spectroradiometer (MODIS) offers the opportunity for multispectral approaches to cloud detection. The MODIS cloud mask developed at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) uses several cloud detection tests to indicate a level of confidence that the MODIS is observing clear skies. The MODIS cloud mask algorithm identifies several conceptual domains according to surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. The updated cloud mask has many improvements, such as improved cloud/surface discrimination over desert regions, sun glint processing and thin cirrus detection. For non-snow-covered land areas, a clear sky confidence of 0.96 (probably clear) will be assigned if thresholds are met for three tests: 3.9-11 μm and 3.75-3.9 μm brightness temperature differences and a 1.24/0.55 μm reflectance ratio test. Values of these must be <15K, <11K and >2.0, respectively. A change has been made to the NIR (band 2) reflectance test for sun glint processing. The updated method is to calculate a cloud threshold as a linear function of sun-glint angle in three separate ranges. A new clear-sky restoral test was added where the ratio of band 17/18 reflectance is utilized to discriminate between low clouds and water surfaces. The thin cirrus thresholds using corrected band 26 (1.38 μm) reflectances were also modified.