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Global Positioning System (GPS) Precipitable Water in Forecasting Lightning at Spaceport Canaveral

机译:全球定位系统(GPS)可降水量预报卡纳维拉尔太空港的闪电

摘要

Using meteorology data, focusing on precipitable water (PW), obtained during the 2000-2003 thunderstorm seasons in Central Florida, this paper will, one, assess the skill and accuracy measurements of the current Mazany forecasting tool and, two, provide additional forecasting tools that can be used in predicting lightning. Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) are located in east Central Florida. KSC and CCAFS process and launch manned (NASA Space Shuttle) and unmanned (NASA and Air Force Expendable Launch Vehicles) space vehicles. One of the biggest cost impacts is unplanned launch scrubs due to inclement weather conditions such as thunderstorms. Each launch delay/scrub costs over a quarter million dollars, and the need to land the Shuttle at another landing site and return to KSC costs approximately $ 1M. Given the amount of time lost and costs incurred, the ability to accurately forecast (predict) when lightning will occur can result in significant cost and time savings. All lightning prediction models were developed using binary logistic regression. Lightning is the dependent variable and is binary. The independent variables are the Precipitable Water (PW) value for a given time of the day, the change in PW up to 12 hours, the electric field mill value, and the K-index value. In comparing the Mazany model results for the 1999 period B against actual observations for the 2000-2003 thunderstorm seasons, differences were found in the False Alarm Rate (FAR), Probability of Detection (POD) and Hit Rate (H). On average, the False Alarm Rate (FAR) increased by 58%, the Probability of Detection (POD) decreased by 31% and the Hit Rate decreased by 20%. In comparing the performance of the 6 hour forecast period to the performance of the 1.5 hour forecast period for the Mazany model, the FAR was lower by 15% and the Hit Rate was higher by 7%. However, the POD for the 6 hour forecast period was lower by 16% as compared to the POD of the 1.5 hour forecast period. Neither forecast period performed at the accuracy measures expected. A 2-Hr Forecasting Tool was developed to support a Phase I Lightning Advisory, which requires a 30-minute lead time for predicting lightning.
机译:利用气象数据,重点研究佛罗里达州中部2000-2003年雷暴季节期间的可降水量(PW),本文将评估当前Mazany预报工具的技能和准确性测量,其二将提供其他预报工具可用于预测闪电。肯尼迪航天中心(KSC)和卡纳维拉尔角空军基地(CCAFS)位于佛罗里达州中部东部。 KSC和CCAFS处理和运载有人(NASA航天飞机)和无人(NASA和空军消耗性运载火箭)航天器。最大的成本影响之一是由于恶劣的天气条件(例如雷暴)而导致的计划外发射擦洗。每次发射延迟/清理费用超过25万美元,而将航天飞机降落在另一个着陆点并返回KSC的费用约为100万美元。考虑到损失的时间和产生的成本,准确预测(预测)雷电发生时间的能力可以节省大量成本和时间。所有闪电预测模型都是使用二元逻辑回归开发的。闪电是因变量,是二进制的。自变量是一天中给定时间的可沉淀水(PW)值,长达12小时的PW变化,电场强度值和K指数值。通过比较1999年B期的Mazany模型结果与2000-2003年雷暴季节的实际观测值,发现误报率(FAR),检测概率(POD)和命中率(H)有所不同。平均而言,错误警报率(FAR)增加了58%,检测概率(POD)减少了31%,命中率减少了20%。将Mazany模型的6小时预测期的性能与1.5小时预测期的性能进行比较,FAR降低了15%,命中率提高了7%。但是,预测时间为6小时的POD与预测时间为1.5小时的POD相比降低了16%。这两个预测期均未达到预期的准确性。开发了2小时预报工具来支持I期闪电咨询,这需要30分钟的交货时间来预报闪电。

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