The Application of a Successful Research-based Laboratory Model to Atmospheric Science

大气科学（41）对能够作为天气和气候现象权威并解释相关数据的专业人员的需求越来越大。然而，本科阶段的大气科学家教育一般不强调大气科学研究是如何进行的，或其结果的演变性质。因此，这类课程的毕业生不会对当前科学信息的优势和局限性有所了解，因此不太能够将这些信息的不确定性传达给彼此、决策者、媒体和公众。该项目正在开发一个新的大气科学实验室课程，以调查在大气科学课程的早期阶段，以研究为基础的学习经验，可以提高学生的：1）科学理解; 2）沟通科学的能力;和3）保留在程序中。该课程是基于一个既定的，成功的模式，将研究纳入介绍化学实验室课程（从中心为真正的科学实践教育，“CASPiE”）。目前正在设计三个研究模块-预报核实、区域气候变化对降水的潜在影响以及雷暴识别和地理空间分布。这些模块考虑到学生在课程早期阶段的理解深度，同时通过使用最先进的分析软件和在这些领域进行新颖研究所需的数值建模来挑战他们。这些模块要求学生分析初步结果，修改他们的实验设计以进行进一步的探究，并综合和展示他们的最终结果。这些结果应该为大气科学界提供有价值的反馈，以改进数值天气预报模型，为农业和政府机构提供有关美国降水可能极易受区域气候变化影响的地区的信息，并提供可用于改进极端天气气候模型预测的初始数据。该项目有助于推进我们对CASPiE模型如何适用于大气科学，地球科学和其他学科的理解。

Atmospheric Sciences (41) There is an increasing demand for professionals who can serve as authorities on weather and climate phenomena, and interpret associated data. However, the education of atmospheric scientists at the undergraduate level generally does not emphasize how atmospheric science research is performed, or the evolutionary nature of its results. Thus, graduates of such programs do not develop an appreciation of the strengths and limitations of current scientific information, and thereby are less able to communicate the uncertainty of this information to each other, policymakers, the media, and the general public. This project is developing a new atmospheric science laboratory course to investigate if a research-based learning experience in the early stages of an atmospheric science curriculum can enhance students': 1) scientific understanding; 2) ability to communicate science; and 3) retention in the program. The course is based on an established, successful model of incorporating research into introductory chemistry laboratory courses (from the Center for Authentic Science Practice in Education, "CASPiE"). Three research modules - forecast verification, potential influences of regional climate change on precipitation, and thunderstorm identification and geospatial distribution - are being designed. The modules take into account the depth of understanding that students have at this early stage in their coursework, while still challenging them by using state-of-the-art analysis software and numerical modeling necessary to perform novel research in these areas. The modules require students to analyze preliminary results, revise their experimental design to conduct further inquiry, and synthesize and present their final results. The results should provide valuable feedback for the atmospheric science community in improving numerical weather prediction models, provide information to agriculture and government agencies regarding the regions where precipitation in the U.S. may be highly susceptible to regional climate change, and provide initial data that can be used to improve climate model predictions of weather extremes. This project serves to advance our understanding of how the CASPiE model can be adapted to programs in atmospheric science, the geosciences, and other disciplines.