EAPSI: Assessing the impact of atmospheric observations from Taiwanese aircraft reconnaissance on Typhoon forecasts

准确的热带气旋预报对于保护全世界日益脆弱的沿海人口至关重要。然而，热带气旋预报的准确性依赖于用于初始化天气预报模型的高质量观测，而在这些强烈气旋一生中大部分时间都在那里度过的海洋上，这种观测尤其稀少。为了缓解每年威胁台湾的众多台风的采样不足问题，台湾大学(NTU)的吴俊杰博士建立了一个名为DOTSTAR的飞机侦察项目。虽然DOTSTAR的飞机观测总体上改善了台风预报，但目前尚不清楚哪些类型的飞机观测产生了最显著的改善。在这项与吴博士合作进行的研究中，将使用包含飞机温度、湿度或风速观测的实验预报来评估纳入每种观测类型的相对预报影响。更好地了解不同的飞机观测如何影响台风预报，将有助于优化未来在太平洋和大西洋盆地的观测任务。飞机观测热带气旋的费用很高，因此，通过更好地了解哪些观测对预报的改善最大，对优化这种飞行任务是有益的。这项拟议的研究将使用DOTSTAR投放探空仪观测，以调查热力和动力现场观测对台风结构和强度预报的相对影响。将使用天气研究和预报(WRF)模式和现代数据同化系统进行一系列模拟，以独立同化来自DOTSTAR水滴探测仪的温度、湿度或风的廓线，用于西太平洋台风样本。此外，还将进行无落差探空仪观测的控制模拟。每个模拟都将根据独立观测、全球模型重新分析和最佳跟踪数据集进行验证，以评估同化每个滴漏探空仪观测子集所产生的改进。这项NSF EAPSI奖是与台湾国家科学委员会合作资助的。

Accurate tropical cyclone forecasts are essential for protecting increasingly vulnerable coastal populations worldwide. However, the accuracy of tropical cyclone forecasts relies on high-quality observations used to initialize weather forecast models, and such observations are particularly sparse over the oceans where these intense cyclones spend most of their lives. To alleviate this under-sampling problem for the numerous typhoons threatening Taiwan each year, Dr. Chun-Chieh Wu of National Taiwan University (NTU) established an aircraft reconnaissance program called DOTSTAR. While DOTSTAR aircraft observations have generally improved typhoon forecasts, it remains unclear which types of aircraft observations produce the most significant improvements. In this study conducted in collaboration with Dr. Wu, experimental forecasts incorporating aircraft observations of temperature, humidity, or wind speed will be used to evaluate the relative forecast impact of including each individual type of observation. Better understanding how different aircraft observations affect typhoon forecasts will help optimize future observing missions both in the Pacific and Atlantic basins. Aircraft observations of tropical cyclones are expensive, and it is therefore beneficial to optimize such missions by better understanding which observations improve forecasts the most. The proposed study will use DOTSTAR dropsonde observations to investigate the relative impact of thermodynamic versus dynamic in situ observations on typhoon structure and intensity forecasts. A series of simulations will be performed using the Weather Research and Forecast (WRF) model with a modern data assimilation system to independently assimilate profiles of temperature, moisture, or winds from DOTSTAR dropsondes for a sample of West Pacific typhoons. In addition, a control simulation without dropsonde observations will be performed. Each simulation will be validated against independent observations, global model reanalysis, and best track datasets to evaluate the improvements resulting from assimilating each subset of dropsonde observations. This NSF EAPSI award is funded in collaboration with the National Science Council of Taiwan.