Engineering topics
Publications and source records attributed to Emery, William.
Background (what): SI (International System of Units)-traceable Microwave Radiometer calibration; Motivation (why): NWP (Numerical Weather Prediction), FCDR (Fundamental Climate Data Record); Technology (how): NIST (National Inst. of Standards and Technology) blackbody target for ; Standards: Status & Future Plans. Development of a National Standard for Microwave Brightness Temperature (TB) at NIST.
The study of rice agriculture is necessary for both the importance of rice as a vital food source and because of the fact that cultivating it has an unfortunate byproduct, namely methane gas. As a food source, rice is a staple for a large majority of the world's population, especially in Asia. Because the populations of many Asian nations are increasing at rapid rates, the production of rice will need to similarly increase. In 1989, it was estimated that the demand for rice would increase by 65% by the year 2019. Rice crops are considered to be one of the primary anthropogenic sources of methane gas. A reason for concern is that this gas is a so-called "greenhouse" trace gas and given its increasing levels in the atmosphere, is thought to contribute to the suspected global warming phenomenon. Some estimate that methane may contribute up to 20% to the global warming effect. Trace gas emissions from anthropogenic sources is an issue that generates great worldwide interest because of the fact that mankind is very likely affecting the current and future climate in potentially negative ways. In an effort to better understand these effects, scientists and engineers are conducting research on all of the varied fronts which relate to climate change and biosphere/atmosphere interactions. The study of global warming through increasing concentrations of greenhouse gases is one area which has received much media and scientific attention. Research fueled by debates on this topic is being conducted on numerous, interrelated fronts in an effort to better understand the complex relationship between human activities and the earth's climate. The research ranges from attempting to verify if the observed data even supports the existence of an anthropogenically generated global-warming phenomenon, to identification of sources and sinks of the trace gases, to measuring the source strengths, to studies which focus on modeling the processes which generate the gases, and finally, to trying to project their impact on the global climatic system. Some of the more commonly known sources of greenhouse gases are related to industry and transportation. Carbon dioxide, CO2, from automobile emissions is one such example. Lesser known are sources from natural and cultivated vegetation, such as the methane, CH4, resulting from rice cropping. While the concentration of atmospheric methane is significantly less than that of carbon dioxide, CH4 has been estimated to have up to 32 times the insulating capability of carbon dioxide, making it an important gas to monitor. The remainder of this chapter will provide some additional background information on the effects of atmospheric methane, and the role that rice agriculture plays as a source in the methane budget. This will be followed by a brief description of efforts to model this source of atmospheric methane. Finally, this chapter will end with a statement of the hypotheses of this thesis, at which time a description of the information contained in the rest of this document will be provided.
The Advanced Very High Resolution Radiometer (AVHRR)-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and cloud mask, all composited into twice-per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 latitude. Our general goals under this grant: (1) Quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements; (2) Determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output; (3) Investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program; and (4) Compare and annual cycle of the APP products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period.
The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.
Study of the environment has historically been done with observations and measurements in relatively few local areas. While some of these have been done over long time spans, most have not. The NOAA/NASA Pathfinder project was initiated to complement these data sets with satellite data that can provide information over larger spatial areas and longer time spans. The AVHRR Polar Pathfinder (APR) program was part of this project. The APR was to supply data from the NOAA AVHRR instruments that was consistently generated in a format usable to a wide range of scientific investigators. A grant was obtained from the NASA Research Announcement 97-MTPE-03 to evaluate the APP products, to provide any enhancements, and to compare with products from the new MODIS instrument. There was about a two year overlap between the projects, and this validation effort had several impacts on the APP products. The APP products are derived from the instruments aboard 4 NOAA satellites, NOAA-7, 9, 11, and 14. Initial validation efforts compared the thermal calibrations of these instruments, and differences are found. Calibration has undergone many revisions and techniques have changed since the satellites were launched. The first calibration methods were optimized for global ocean temperatures, as this was one of the primary and important uses of the AVHRR instruments. As the APP program started, newer methods that provided more accurate temperature retrievals over a wider range of temperatures were being developed. The calibration of a wider range of temperatures were necessary because of the extremely low values in the polar regions. These methods were also designed so that calibrated data was also consistent between all the NOAA satellites. These newer calibration methods were then adopted primarily because of the initial finding of this validation effort.
Characterization and diagnosis of sea ice/atmosphere/ocean interactions require a synthesis of observations and modeling to identify the key mechanisms controlling the ice/climate system. In this project, we combined product generation, observational analyses, and modeling to define and interpret variability in ice motion in conjunction with thermodynamic factors such as surface temperature and albedo. The goals of this work were twofold: (1) to develop and test procedures to produce an integrated set of polar products from remotely-sensed and supporting data; and (2) to apply these data to understand processes at work in controlling sea ice distribution.
This project was a continuation of the project entitled "Resolution Earth Surface Features from Repeat Moderate Resolution Satellite Imagery". In the previous study, a Bayesian Maximum Posterior Estimate (BMPE) algorithm was used to obtain a composite series of repeat imagery from the Advanced Very High Resolution Radiometer (AVHRR). The spatial resolution of the resulting composite was significantly greater than the 1 km resolution of the individual AVHRR images. The BMPE algorithm utilized a simple, no-atmosphere geometrical model for the short-wave radiation budget at the Earth's surface. A necessary assumption of the algorithm is that all non geometrical parameters remain static over the compositing period. This assumption is of course violated by temporal variations in both the surface albedo and the atmospheric medium. The effect of the albedo variations is expected to be minimal since the variations are on a fairly long time scale compared to the compositing period, however, the atmospheric variability occurs on a relatively short time scale and can be expected to cause significant errors in the surface reconstruction. The current project proposed to incorporate an atmospheric correction into the BMPE algorithm for the purpose of investigating the effects of a variable atmosphere on the surface reconstructions. Once the atmospheric effects were determined, the investigation could be extended to include corrections various cloud effects, including short wave radiation through thin cirrus clouds. The original proposal was written for a three year project, funded one year at a time. The first year of the project focused on developing an understanding of atmospheric corrections and choosing an appropriate correction model. Several models were considered and the list was narrowed to the two best suited. These were the 5S and 6S shortwave radiation models developed at NASA/GODDARD and tested extensively with data from the AVHRR instrument. Although the 6S model was a successor to the 5S and slightly more advanced, the 5S was selected because outputs from the individual components comprising the short-wave radiation budget were more easily separated. The separation was necessary since both the 5S and 6S did not include geometrical corrections for terrain, a fundamental constituent of the BMPE algorithm. The 5S correction code was incorporated into the BMPE algorithm and many sensitivity studies were performed.
Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is currently limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoys data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Principal objectives of this project were to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions. Each of these main objectives was addressed. We conclude that AVHRR data, particularly when blended with other available observations, provide a valuable data set for studying sea ice processes. In a follow-on project, we are now extending this work to cover larger areas and to address science questions in more detail.
The main objective of the Testbed project was to deliver satellite images via the Internet to scientific and educational users free of charge. The main method of operations was to store satellite images on a low cost tape library system, visually browse the raw satellite data, access the raw data filed, navigate the imagery through 'C' programming and X-Windows interface software, and deliver the finished image to the end user over the Internet by means of file transfer protocol methods. The conclusion is that the distribution of satellite imagery by means of the Internet is feasible, and the archiving of large data sets can be accomplished with low cost storage systems allowing multiple users.
Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.
We propose to develop an on-line data distribution and interactive display system for the collection, archival, distribution and analysis of operational weather satellite data for applications in land surface studies. A 1,000 square km scene of the western U.S. (centered on the Colorado Rockies) will be extracted from Advanced Very High Resolution Radiometer (AVHRR) imagery collected from morning and afternoon passes of the NOAA polar-orbiters at the direct readout stations operated by CU/CCAR. All five channels of these AVHRR data will be navigated and map registered at CU/CCAR and then be transferred to NCAR for storage in an on-line data system. Software will also be available at NCAR to process and navigate the raw AVHRR data as needed. A display workstation software, based on a Macintosh II computer, will be developed that will display and further process the AVHRR data for studies of vegetation monitoring and snowpack assessment. Various options of presently used techniques for both vegetation and snowpack monitoring will be implemented in the workstation software to provide the individual investigator with the freedom to interact with the satellite image data. The display software will be freely distrributed online to interested investigators, and the AVHRR data will be made available on-line to anyone interested. In addition, potential users will be sought out and connected to the on-line data archive. This experiment with an active on-line archive and interactive analysis systems will provide experience with a small scale EOSDIS.
We propose to develop an on-line data distribution and interactive display system for the collection, archival, distribution and analysis of operational weather satellite data for applications in land surface studies. A 1,000 sq km scene of the western U.S. (centered on the Colorado Rockies) will be extracted from Advanced Very High Resolution Radiometer (AVHRR) imagery collected from morning and afternoon passes of the NOAA polar-orbiters at the direct readout stations operated by CU/CCAR. All five channels of these AVHRR data will be navigated and map registered at CU/CCAR and then be transferred to NCAR for storage in an on-line data system. Software will also be available at NCAR to process and navigate the raw AVHRR data as needed. A display workstation software, based on a Macintosh II computer, will be developed that will display and further process the AVHRR data for studies of vegetation monitoring and snowpack assessment. Various options of presently used techniques for both vegetation and snowpack monitoring will be implemented in the workstation software to provide the individual investigator with the freedom to interact with the satellite image data. The display software will be freely distributed online to interested investigators and the AVHRR data will be made available on-line to anyone interested. In addition, potential users will be sought out and connected to the on-line data archive. This experiment with an active on-line archive and interactive analysis systems will provide experience with a small scale EOSDIS.
This is the final report describing the work done on the project entitled Automatic AVHRR Image Navigation Software funded through NASA-Washington, award NAGW-3224, Account 153-7529. At the onset of this project, we had developed image navigation software capable of producing geo-registered images from AVHRR data. The registrations were highly accurate but required a priori knowledge of the spacecraft's axes alignment deviations, commonly known as attitude. The three angles needed to describe the attitude are called roll, pitch, and yaw, and are the components of the deviations in the along scan, along track and about center directions. The inclusion of the attitude corrections in the navigation software results in highly accurate georegistrations, however, the computation of the angles is very tedious and involves human interpretation for several steps. The technique also requires easily identifiable ground features which may not be available due to cloud cover or for ocean data. The current project was motivated by the need for a navigation system which was automatic and did not require human intervention or ground control points. The first step in creating such a system must be the ability to parameterize the spacecraft's attitude. The immediate goal of this project was to study the attitude fluctuations and determine if they displayed any systematic behavior which could be modeled or parameterized. We chose a period in 1991-1992 to study the attitude of the NOAA 11 spacecraft using data from the Tiros receiving station at the Colorado Center for Astrodynamic Research (CCAR) at the University of Colorado.
Viewgraphs on the Colorado Center for Astrodynamics Research (CCAR) are presented. Topics covered include: EOSDIS testbed: an Advanced Very High Resolution Radiometer (AVHRR) data system for snowpack and vegetation studies; satellite data processing software; satellite data analysis activities; mass storage systems; wide area network connections; and remote access.