Click for next page ( 38


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 37
4 Analysis and Forecasting Systems The previous chapter has pointed out that there are many types of observing platforms currently in use at KSC and other launch and landing sites, and that improvements and additional platforms are required. In a real-time operational setting, however, new and im- proved data do not necessarily translate into improved diagnoses and forecasts. If data from each source were considered independently, the correct prognosis might become progressively blurred. This is especially true because of the complexity of the mesoscale weather systems that affect KSC, which may be of such small scale that indi- vidual measurement systems are only able to give a skeletal picture of the phenomenon. In this situation, the key to successful diagno- sis and forecasting lies in the joint use of data from many different sources, each providing a bit of information not treated by the others, to obtain a clear understanding of the weather situation. The skill needed to perform this mental assimilation is not gained quickly or easily. It requires intelligent, experienced, and dedicated personnel; training; practice; and the proper system (hardware and software) with which to examine the data. These topics will be treated in this chapter. 37

OCR for page 37
38 DATA ACQUISITION AND DISPLAY In order to perform timely analyses and diagnoses, the AWS fore- casters servicing KSC and the NWS forecasters at DISC make use of a computerized interactive analysis and display system called MIDDS (Meteorological Interactive Data Display System). This system is capable of displaying large-scale diagnostic and prognostic data, as well as zooming into the observational networks on the local scale surrounding KSC. This powerful system can meet the hardware and software needs of the mesoscale forecaster if it is used optimally. One strength of MIDDS lies in its graphical overlay capability, which fosters the joint use of data in the manner discussed above. This enables a clearer depiction of the structure of the weather systems and an Unproved understanding of the interrelationships be- tween the different scales of motion and different data fields, such as between changes in the electric field and the movement and devel- opment of radar echoes. Another invaluable feature is the looping capability, which facilitates the use of prognoses based on extrapm rating the movement and evolution of the weather systems. To be most effective, however, all types of data must be accessible on the MIDDS system. At the tune of the panel's visit to KSC, electric field malt and other data were not incorporated into the MIDDS data base and had to be examined on a stand-alone display. Future plans call for all data sets to be available on MIDDS; these plans need to be promptly executed. All sources of satellite data, including NOAA and DMSP polar orbiting satellites, as well as all channels (e.g., visible, all infrared and near infrared, and microwave channels) should be received. The Weather Support Office 8~0111d expedite plans to incor- porate aB data sets on MIDDS and promote the joint display of disparate data sets. Improvements in analysis and forecasting procedures can be at- tained almost immediately through better use of existing data: (1) A series of lectures and training sessions should be scheduled to bring the staffs at KSC and dSC up to date regarding the latest tech- niques and procedures in interpreting and using satellite imagery in synoptic-scale diagnosis. Special emphasis should be placed on the use of water vapor imagery. (2) A routine procedure should be estate fished requiring reanalysis of surface and selected upper-air charts at more contour intervals and with less smoothing than those received from the National Meteorological Center. (3) A MIDDS program

OCR for page 37
39 should be written to generate vertical time-sections of upper-air and surface data and, ultimately, profiler data. This too! can help to de- tect moderate-scale weather systems and thereby enhance analyses and prognoses. (4) Trnmediate benefits can be obtained through a program of inviting visiting scientists with operational experience to interact with operational forecasters. Because the types of weather events that cause disasters are rare, it would be valuable to let a computer maintain a continuous lookout for telltale signals of a potentially dangerous phenomenon. Human forecasters cannot watch the LLP display 24 hours per day, 365 days per year, yet a 5-minute delay in detecting the first lightning dis- charge on an otherwise quiet day could cost lives. An alert system that is triggered whenever a critical weather element exceeds a hazard threshold ~ needed. For example, an alert could be triggered when the LLP lightning detection system detects a cloud-t~ground dis- charge occurring within a certain distance of the launch pad or other weather-sensitive area. Other alerts could be triggered by changes in or large values of electric field, by excessive low-level wind shear, by strong low-level moisture convergence, and so on. Critical obeervations or parmnetere derwed Mom analyses should be monitored by computer to allow continuous surveil- lance between periods of human monitoring. LOCAL OBJECTIV1: ANALYSES The abundant and diverse types of data may confuse weather personnel unless steps are taken to assimilate and consistently ana- lyze data from all sources and transform them into high-resolution "ridded fields of understandable variables. Techniques to assimilate and analyze these data should be auto- mated so that the forecaster need only consider fields analyzed from "ridded data, such as the three-dimensional vector wind. Similarly, observations of temperature and moisture from satellites can be com- bined with surface and mesonet observations to provide structure at very fine scales. By using a "ridded format, a number of specific space-flight- oriented products can be generated, and nowcasting can be greatly enhanced. The detailed analyses can also serve as first-guess fields in initialization of mesoscaTe numerical models. With four-dimensional data assimilation techniques, the mode! equations themselves could

OCR for page 37
40 form the framework of the analysis algorithm, further improving the process. There is a need to develop local (ESC) analysis systems that incorporate aB data sources and provide high-resolution ~id- ded field appropriate for forecaster and numerical mode] me. INTERACTIVE FORECAST SYSTEMS There is a need to develop aids to help forecasters avoid be- ing overwhelmed and to help them systematically consider only the data appropriate for use in making various forecast decisions during differing weather situations. One such aid needed is classified as a "decision tree," a stepwise procedure which enables the forecaster to consider all pertinent data when being called on to forecast a given condition or parameter. With the versatility of MIDDS, such decision trees should be developed as dynamic tools that permit interactions with the user. They should be developed to incorporate not only observations and conceptual models, but also output from nested mesoscale numerical prediction models, objective forecast studies, and objective and subjective evaluations of forecasters. The need to understand and forecast cloud electrical develop- ment is particularly urgent. Since existing thunderstorms can be monitored with the field mill, radar, and lightning detection net- works, the three problems that require attention are (1) the onset of lightning in developing thunderstorms, (2) the continuation of lightning in decaying thunderstorms or detached anvils, and (3) the threat of triggered lightning in convective and nonconnective clouds. Although these problems need longer-term applied research with new measurement systems, some gains could be obtained through subjective and statistical studies of available data sets. The exist- ing yes/no data from triggered lightning studies at KSC, for exam- ple, could be used together with parameters such as electric field, cloud base height, height of the freezing level, cloud top infrared temperature (or inferred height), distance from radar echo, surface convergence/divergence values, and so on, to develop decision trees for forecasting triggered lightning. Decision trees should also be de- veloped for each of the other critical weather variables discussed in Chapters 1 and 3. Another approach to developing forecaster aids Is through use of expert systems or "artificial intelligence" (Al) techniques. In some ways these approaches are sirn~lar to decision trees, but with heavier

OCR for page 37
41 emphasis on the computer as opposed to human interaction. This technique also Light be worth applying to available electrified and triggered lightning data and various accompanying data sets. The pane! believes that the artificial intelligence research going on at KSC is addressing forecasting problems in a manner that ~ al- most as if it ~ starting From scratch" and that it is not likely to yield state-othe-science forecasting techniques. The pane} suggests that AT research be focused toward specific problems such as determining how to optimally combine measurements of the types listed above to yield accurate short-term forecasts of the threats from natural and triggered lightning. There ~ an urgent need for the development of interactive `'4ecision treed and computer-aided dec~ion-maimg meth- o~ to help the forecaster make most efficient me of data in reaching decisions, particularly in forecasting thunderstorm formation ant! natural and triggered lightning. M1:SOSCALE FORECAST MODELS Mesosc ale forecast modem offer the potential for dramatic en- hancements in future forecast accuracy. Mesoscale models have suc- cessfully simulated many import ant mesoscale circulations and storm systems. New nested mesoscale models are becoming available that are nonhydrostatic and contain embedded fine mesh grids that pro- vide enhanced resolution where small-scale structures are evolving. With the help of a local analysis system, discussed in the previous section, high-resolution analyses could be used to initialize these fore- cast models. Mode] studies have demonstrated that, in many cases, the forcing influences that generate mesoscale weather systems orig- inate in the larger-scale environment and are therefore predictable from coarser resolution initial data. Further applied research and development will be required to realize the anticipated improvements In forecast accuracy and to adapt these models to an operational environment. Numerous issues, such as data assimilation, mode} initialization, and parameterized physics can be refined to improve the accuracy of mesoscale forecast models. With the installation of a wind profiler network, the KSC environment would be ideally suited as a test bed for mesoscale mode! development and testing. NASA's weather-support should take an active role in encouraging this research and work with the modeling projects to develop products that address KSC forecasting needs.

OCR for page 37
42 The National Aeronautics and Space Administration and other participants m the space program should tales an active role in encouraging development of numerical models de:.llng with weather elements crucial to the space program.