Solar Response and Long‐Term Trend of Midlatitude Mesopause Region Temperature Based on 28 Years (1990–2017) of Na Lidar Observations
Solar Response and Long‐Term Trend of Midlatitude Mesopause Region Temperature Based on 28 Years (1990–2017) of Na Lidar Observations
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DOI：
10.1029/2019ja026759
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发表时间：
2019-08
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通讯作者：
C. She;U. Berger;Zhaoai Yan;T. Yuan;F. Lübken;D. Krueger;Xiong Hu
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作者：
C. She;U. Berger;Zhaoai Yan;T. Yuan;F. Lübken;D. Krueger;Xiong Hu
我们介绍了1990年至2017年期间科罗拉多州立大学/犹他州州立大学Na激光雷达夜间温度观测的中纬度太阳响应和线性趋势。沿着夜间平均温度（_Ngt），我们还使用了相应的以午夜为中心的2小时平均值（_2MN），得到了与先前公布的形状相似的垂直趋势剖面。来自_Ngt（_2MN）数据集的28年趋势从85 km处的小幅变暖开始，到87（88）km处的冷却，在92（93）km处达到最大值1.85 ± 0.53（1.09 ± 0.74），并在102（100）km处再次转为正值。6个月的冬季趋势比4个月的夏季趋势要冷得多，在整个剖面（85-105 km）中，太阳响应变化约为5 ± 1 K/100 SFU，夏季值更高。我们探讨了观测到的夏季/冬季趋势差异，在附近的站观测到的重力波热通量加热率和长期趋势的重力波方差在中纬度。在89到100公里之间，激光雷达趋势在莱布尼茨中层大气（LIMA）夏季趋势（1979-2013）的误差范围内，这与激光雷达-Ngt趋势几乎相同。我们解决了长期数据集的需要，可靠的趋势分析，由于可能的潮汐偏差的趋势不确定性的程度，皮纳图博/情节功能的影响，以及平流层臭氧恢复的影响。
We present midlatitude solar response and linear trend from Colorado State University/Utah State University Na lidar nocturnal temperature observations between 1990 and 2017. Along with the nightly mean temperatures (_Ngt), we also use the corresponding 2‐hr means centered at midnight (_2MN), resulting in vertical trend profiles similar in shapes as those previously published. The 28‐year trend from _Ngt (_2MN) data set starts from a small warming at 85 km, to cooling at 87 (88) km, reaching a maximum of 1.85 ± 0.53 (1.09 ± 0.74) at 92 (93) km and turns positive again at 102 (100) km. The 6‐month winter trend is much cooler than the 4‐month summer trend with comparable solar response varying around 5 ± 1 K/100 SFU throughout the profile (85–105 km) with higher summer values. We explore the observed summer/winter trend difference in terms of observed gravity wave heat flux heating rate at a nearby station and the long‐term trend of gravity wave variance at a midlatitude. Between 89 and 100 km, the lidar trends are within the error bars of the Leibniz Middle Atmosphere (LIMA) summer trends (1979–2013), which are nearly identical to the lidar‐Ngt trend. We address the need of long data set for reliable analysis on trend, the extent of trend uncertainty due to possible tidal bias, the effect of a Pinatubo/episodic function, and the impact of stratospheric ozone recovery.