利用区域气候模式CCLM估算MOSAiC期间垂直廓线和大气边界层结构

G. Heinemann, Lukas Schefczyk, Rolf Zentek, I. Brooks, S. Dahlke, A. Walbröl
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摘要

区域气候模式是研究极地气候过程和气候变化的重要工具,但模式的性能必须用实验数据来评价。采用区域气候模式CCLM模拟马赛克期,水平分辨率为14 km(整个北极)。CCLM在预测模式(嵌套在ERA5中)中使用,并使用了一个热力学海冰模型。海冰浓度来自AMSR2数据(C15运行)和MODIS数据(C15MOD0运行)的高分辨率数据集(1公里)。利用探空数据和不同剖面系统的数据对该模型进行了评估,重点关注了冬季(11月至4月)。与无线电探空数据的比较显示温度、湿度和风的一致性非常好。11月和12月ABL存在冷偏,C15MOD0运行时偏小。相比之下,3月和4月有较低水平的暖偏,C15周期的低偏偏较小。不同海冰参数化的影响仅限于300 m以下的高度。高分辨率激光雷达和雷达风廓线以及来自微波辐射计的温度和综合水汽(IWV)数据被用于与CCLM进行案例研究的比较,其中包括低空射流。激光雷达风廓线有许多空白,但为模型评估提供了有价值的数据集。与微波辐射计测得的IWV和温度数据比较,结果吻合较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Vertical Profiles and Atmospheric Boundary Layer Structure Using the Regional Climate Model CCLM during MOSAiC
Regional climate models are a valuable tool for the study of the climate processes and climate change in polar regions, but the performance of the models has to be evaluated using experimental data. The regional climate model CCLM was used for simulations for the MOSAiC period with a horizontal resolution of 14 km (whole Arctic). CCLM was used in a forecast mode (nested in ERA5) and used a thermodynamic sea ice model. Sea ice concentration was taken from AMSR2 data (C15 run) and from a high-resolution data set (1 km) derived from MODIS data (C15MOD0 run). The model was evaluated using radiosonde data and data of different profiling systems with a focus on the winter period (November–April). The comparison with radiosonde data showed very good agreement for temperature, humidity, and wind. A cold bias was present in the ABL for November and December, which was smaller for the C15MOD0 run. In contrast, there was a warm bias for lower levels in March and April, which was smaller for the C15 run. The effects of different sea ice parameterizations were limited to heights below 300 m. High-resolution lidar and radar wind profiles as well as temperature and integrated water vapor (IWV) data from microwave radiometers were used for the comparison with CCLM for case studies, which included low-level jets. LIDAR wind profiles have many gaps, but represent a valuable data set for model evaluation. Comparisons with IWV and temperature data of microwave radiometers show very good agreement.
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