Investigating the propagation mechanism of unmodelled systematic errors on coordinate time series estimated using least squares

The propagation of unmodelled systematic errors into coordinate time series computed using least squares is investigated, to improve the understanding of unexplained signals and apparent noise in geodetic (especially GPS) coordinate time series. Such coordinate time series are invariably based on a functional model linearised using only zero and first-order terms of a (Taylor) series expansion about the approximate coordinates of the unknown point. The effect of such truncation errors is investigated through the derivation of a generalised systematic error model for the simple case of range observations from a single known reference point to a point which is assumed to be at rest by the least squares model but is in fact in motion. The systematic error function for a one pseudo-satellite two-dimensional case, designed to be as simple but as analogous to GPS positioning as possible, is quantified. It is shown that the combination of a moving reference point and unmodelled periodic displacement at the unknown point of interest, due to ocean tide loading, for example, results in an output coordinate time series containing many periodic terms when only zero and first-order expansion terms are used in the linearisation of the functional model. The amplitude, phase and period of these terms is dependent on the input amplitude, the locations of the unknown point and reference point, and the period of the reference point's motion. The dominant output signals that arise due to truncation errors match those found in coordinate time series obtained from both simulated data and real three-dimensional GPS data.     

Characterization and quantification of data voids in the shuttle Radar topography mission data

The goal of this study was to characterize and quantify the occurrence of data voids in data from the Shuttle Radar Topography Mission (SRTM) for the conterminous United States. For this purpose, SRTM data and corresponding data from the national elevation data were downloaded in 21 samples spatially organized to cover the main topography of the U.S. Void locations in SRTM data were compared to terrain attributes and subsequently the area of individual data voids to the same attributes. It was found that data voids amounted to 0.3% of the total dataset. Data voids were found in all topographic settings but more often in slopes steeper than approximately 20/spl deg/ that face south (170/spl deg/), and also in flat areas such as lakes and rivers. It was also found that more than 50% of all data voids were composed of connected pixels in groups less than six pixels. The largest data voids could be attributed to water bodies, while the rest could be explained by terrain-radar interaction characteristics.     

Retrieving cloud fraction in the field-of-view of a high-spectral resolution infrared radiometer

The combination of radiance from both clear and cloudy regions of sky within the instrument's field of view (FOV) adds significant uncertainty to retrievals of atmospheric state profiles and cloud microphysical properties from infrared spectroradiometers. In this letter, we use observations of radiance from both the 8-13 and 3-5 /spl mu/m bands to retrieve estimates of the cloud fraction in the instrument's FOV, as well as microphysical cloud properties, from high-spectral-resolution infrared radiometers. Cloud fraction derived from imagers as well as high-time-resolution observations show good agreement and high correlation with our derived cloud fraction values. This is shown for both ground-based and aircraft-based observations. We also demonstrate that the use of the additional information in the 3-5 /spl mu/m band extends the dynamic range and accuracy of microphysical properties that can be retrieved from infrared radiance data.     

Analysis of geophysical networks derived from multiscale digital elevation models: a morphological approach

We provide a simple and elegant framework based on morphological transformations to generate multiscale digital elevation models (DEMs) and to extract topologically significant multiscale geophysical networks. These terrain features at multiple scales are collectively useful in deriving scaling laws, which exhibit several significant terrain characteristics. We present results derived from a part of Cameron Highlands DEM.     

Annual amphidromes: a common feature in the ocean?

The scientific term "amphidrome" is usually associated with tides in oceanography. The dozen tidal amphidromes observed in the ocean are critical points that determine the fundamental pattern of the global tidal system. Exploration of recently available satellite data with an unprecedented 1-2 decades duration suggests that an amphidrome is not a tide-only phenomenon in the ocean. Analysis of altimeter-derived sea level anomaly (SLA) data and radiometer-derived sea surface temperature (SST) data allows ten amphidromic points to be clearly identified in annual SLA and SST variations. These amphidromes are located in the tropical areas of the Pacific, Atlantic, and Indian oceans. Their existence implies that the annual cycle (in time) of the atmosphere-ocean system is translated into a rotary variation (in space) for many of the geophysical parameters. It can be concluded that annual amphidromes are common, the knowledge of which is of particular interest, given their annually "constant" nature, for the monitoring and understanding of oceanic, climatic, as well as biological variabilities at seasonal to decadal scales, which strongly affect many aspects of the natural and societal activities on the globe.     

Spectral Filtering and Classification of Terrestrial Laser Scanner Point Clouds

A method is presented for filtering and classification of terrestrial laser scanner point clouds. The algorithm exploits the four-channel (blue, green, red and near infrared) multispectral imaging capability of some terrestrial scanners using supervised, parametric classification to assign thematic class labels to all scan cloud points. Its principal advantage is that it is a completely data-driven algorithm and is independent of spatial sampling resolution since the processing is performed in four-dimensional spectral feature space. Its application to two data-sets of different spatial extent and spatial and spectral complexity is reported, for which respective overall classification accuracies of 87·0% and 82·0% were achieved. Analysis of the input data with emphasis on the characteristics pertinent to the anticipated outcomes precedes detailed analysis of the classification results and error sources and their causes. Erroneously classified points are attributed to radiometric errors stemming from both detector hardware and physical effects.     

Comparison of ERS-SAR and spot data for sugar beet crop cover assessment

The present work was aimed to compare the abilities of radar and optical satellite data to estimate crop canopy cover, which is a key component of productivity estimates. Three ERS-1 SAR images were obtained of East Anglia (UK) in 1995 and one ERS-2 SAR image in 1996. The images covered a study area around the IACR Brooms Barn Sugar Beet Research Institute. Field data comprising radiometric and biophysical measurements of the crop canopy were collected in two fields from June 22 to August 3, 1995 to coincide with ERS-1 SAR overpass dates. In 1996, field data were collected in two fields from June 11 to July 29 on a weekly basis. A previously calibrated version of the water cloud model was inverted to estimate Leaf Area Index (LAI) from ERS-1 and ERS-2 SAR backscatter and soil moisture samples. Canopy cover was estimated from the radar-estimated LAI using a standard exponential relationship that has a well-established coefficient for sugar beet. Radio-metrically and atmospherically corrected data from three SPOT images in 1995 and one SPOT image in 1996 were used to calculate the Optimised Soil Adjusted Vegetation Index (OSAVI), from which crop canopy cover was estimated using a relationship determined previously by canopy modelling. The crop cover values estimated by satellite were in good agreement with those measured on ground with the Parkinson radiometer. Radar data may be able to provide useful estimates of canopy cover for crop production modelling, especially in the case of loss of optical data due to cloud.     

斜交型不稳定谱点分布侧半圆定理及其增长率上界的估计

本对斜交型扰动不稳定谱点的分布做了理论分析，得到了该谱点分布的半圆定理一该谱点分布在复一面上以原点为圆心以R0为半径的上半平面上，同时还对该不稳定增长率的上界作了估计。发现水平永度越小，模式顶越高则该估计值越大；垂直风切变的增大和纬度的增高对该增长率的增大有正贡献；当层结稳定度减小时，最大增长率随相对最大增长率得增大而减小。     

一类广义Hamilton系统的辛格式

通过引人泊松括号，分析了无限维Hamilton的性质，并将其推广到广义Hamilton系统，且从理论和实用角度讨论了这类广义Hamilton系统的辛格式构造问题，从而为辛几何算法在一般的时间发展方程的数值求解提供新的具体途径。     

Distribution of seasonal rainfall in the East Asian monsoon region

Summary ?This study deals with the climatological aspect of seasonal rainfall distribution in the East Asian monsoon region, which includes China, Korea and Japan. Rainfall patterns in these three countries have been investigated, but little attention has been paid to the linkages between them. This paper has contributed to the understanding of the inter-linkage of various sub-regions. Three datasets are used. One consists of several hundred gauges from China and South Korea. The second is based on the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP). The two sources of precipitation information are found to be consistent. The third dataset is the NCEP/NCAR reanalysis 850-hPa winds. The CMAP precipitation shows that the seasonal transition over East Asia from the boreal winter to the boreal summer monsoon component occurs abruptly in mid-May. From late March to early May, the spring rainy season usually appears over South China and the East China Sea, but it is not so pronounced in Japan. The summer monsoon rainy season over East Asia commonly begins from mid-May to late May along longitudes of eastern China, the Korean Peninsula, and Japan. A strong quasi-20-day sub-seasonal oscillation in the precipitation appears to be dominant during this rainy season. The end date of the summer monsoon rainy season in eastern China and Japan occurs in late July, while the end date in the Korean Peninsula is around early August. The autumn rainy season in the Korean Peninsula has a major range from mid-August to mid-September. In southern China, the autumn rainy season prevails from late August to mid-October but a short autumn rainy season from late August to early September is noted in the lower part of the Yangtze River. In Japan, the autumn rainy season is relatively longer from mid-September to late October. The sub-seasonal rainfall oscillation in Korea, eastern China and Japan are explained by, and comparable to, the 850-hPa circulation. The strong westerly frontal zone can control the location of the Meiyu, the Changma, and the Baiu in East Asia. The reason that the seasonal sea surface temperature change in the northwestern Pacific plays a critical role in the northward advance of the onset of the summer monsoon rainfall over East Asia is also discussed. Received October 5, 2001; revised April 23, 2002; accepted May 11, 2002