Impact of Ground Based GPS Data on Numerical Weather Prediction
Impact of Ground Based GPS Data on Numerical Weather Prediction
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DOI：
10.2151/jmsj.2004.459
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发表时间：
2004-03
影响因子：
3.1
通讯作者：
H. Vedel;Xiangyu Huang
中科院分区：
文献类型：
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作者：
H. Vedel;Xiangyu Huang
提出了一项关于从欧洲地面全球定位系统 (GPS) 接收器观测获得的天顶总延迟 (ZTD) 对数值天气预报 (NWP) 技能影响的研究。 ZTD主要取决于GPS站点的当地压力和上方柱中的综合水蒸气。压力和湿度信息对于 NWP 模型都至关重要，但 ZTD 主要作为湿度信息来源，预计对 NWP 模型具有重要意义。鉴于目前湿度观测的数量很少，将 ZTD 纳入数据同化中，确定 NWP 预报的起始状态，预计将提高预报技能。欧洲、美国和日本的团体正在开展影响力和其他研究，以评估这些期望是否能够实现。我们在这里展示了 2002 年 2 月期间并行运行的结果，数据同化中有或没有 ZTD 数据，使用的是 COST Action 716 数据样本中的欧洲 ZTD 数据。同化中包含来自 117 个 GPS 站的数据。这些运行是使用 HIRLAM 局域 NWP 模型的光谱版本及其变分数据同化系统 HIRVDA 在 3DVar 模式下执行的。模拟以 0.45 度和 0.15 度分辨率进行。结果发现，对 EWGLAM 列表中站点的观测结果（高度、风、温度、湿度）进行统计验证表明，这一时期 GPS ZTD 的影响主要是中性的，但位势高度方面出现了系统性改进。 NWP 降水预报与 12 小时雨量计观测结果进行了详细比较。列联表和特别是降水图的详细比较（通过肉眼）表明，在此期间包含基于地面的 GPS ZTD 观测可以改善强降水的预测。结合我们之前的结果（Vedel 和 Huang，2003）以及其他小组报告的结果，这巩固了 GPS ZTD 数据将提高 NWP 降水预报技巧的结论。在数值天气预报模型中以最佳方式使用地面 GPS 数据之前，仍有待解决的问题。其中包括更好地了解 ZTD 观测值和 NWP 首次猜测场的误差和误差相关性，以及比较模型和观测降水的更好方法。新的欧洲项目 TOUGH（以气象学中 GPS 湿度观测的最佳使用为目标）将解决其中一些问题。
A study on the impact of zenith total delays (ZTD's) obtained from observations by ground based Global Positioning System (GPS) receivers in Europe on the skill of numerical weather prediction (NWP) is presented. The ZTD depends mainly on the local pressure at the GPS site and the integrated water vapour in the column above. Both pressure and humidity information are vital to NWP models, but it is mainly as a source of humidity information the ZTD's are expected to be significant to NWP models. Given the currently meagre amount of humidity observations the inclusion of ZTD's in the data assimilation, determining the starting states for NWP forecasts, is expected to improve forecast skill. Groups in Europe, the US, and Japan are carrying out impact and other studies to assess whether such expectations can be fulfilled. We here present results from parallel runs, with and without ZTD data in the data assimilation, for the period of February 2002, using European ZTD data from the COST Action 716 data sample. Data from 117 GPS stations are included in the assimilations. The runs are performed using the spectral version of the HIRLAM local area NWP model and its variational data assimilation system, HIRVDA, in 3DVar mode. The simulations have been carried out at both 0.45 and 0.15 degree resolution. It is found that statistical verification against observations (heights, winds, temperatures, humidities) from stations on the EWGLAM list indicates mainly neutral impact of GPS ZTD's in this period, with the exception that systematic improvements are seen in the geopotential heights. A detailed comparison of NWP forecasts of precipitation is performed against 12 hour rain gauge observations. Both contingency tables and in particular detailed comparisons (by eye) of precipitation maps show that for this period inclusion of ground based GPS ZTD observations improve the prediction of strong precipitation. In combination with our previous results, (Vedel and Huang 2003), and those reported by other groups, this solidifies the conclusion that GPS ZTD data will improve NWP forecast skill of precipitation. Questions remain to be solved before ground based GPS data can be used in an optimal way in NWP models. These include better knowledge of the errors and error correlations of both the ZTD observations and of the NWP first guess field, as well as better ways of comparing model and observed precipitation. The new European project TOUGH (Targeting Optimal Use of GPS Humidity Observations in Meteorology) will address some of these issues.