Early Validation of Vertical Profiles from the Envisat Atmospheric Instruments GOMOS and MIPAS with the University of Bonn Lidar at the Esrange in July and August 2002 (AOID222)
Early Validation of Vertical Profiles from the Envisat Atmospheric Instruments GOMOS and MIPAS with the University of Bonn Lidar at the Esrange in July and August 2002 (AOID222)
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2002 年 7 月和 8 月，波恩大学激光雷达在 Esrange 对 Envisat 大气仪器 GOMOS 和 MIPAS 的垂直剖面进行了早期验证 (AOID222)
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发表时间：
2003
期刊：
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通讯作者：
U. Blum
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作者：
K. Fricke;U. Blum
地球大气的垂直结构由流体静力平衡控制，它与高度、温度和压力（或密度）有关。化学上重要的微量气体的混合比取决于对这一基本大气结构的精确了解。2002年7月中旬至8月底，在瑞典基律纳附近的Esrange（北纬68度，东经21度）上运行了波恩大学的后向散射激光雷达，以获取大气结构数据，即温度和相对密度的高度曲线，供环境卫星验证。我们总共可以用激光雷达进行36次测量，其中34次产生了可用的密度和温度proles，以及对流层和中间层云的几次观测。三个环境卫星大气仪器Gomos，Mipas和Sciamachy测量温度和密度或压力的高度。本验证报告反映了截至2002年11月中旬这三台仪器的操作反演软件的状态。在30 ~ 70 km的高度范围内，将38个Gomos粒子与激光雷达数据进行比较，结果表明密度粒子的形状与温度的平均偏差不超过1.4%或3-4 K，密度粒子的形状与温度的平均偏差不超过2%。Gomos高度记录与激光雷达高度一致，优于300 m。独立地将Envisat仪器探针与斯堪的纳维亚半岛北方上空北极夏季中层大气的经验模型进行了比较，该模型是基于挪威北方Andya火箭靶场十年来的落球测量。将48个Gomos Prole与35 - 93 km高度范围内的落球统计数据进行比较，平均显示出与偏差直方图的模值非常一致，温度为-0.6%（即1.2-1.5 K），密度为-1.8%。在Gomos产品中，还从内部模型中给出了压力和温度值，这些值与Gomos密度和温度的最佳值更好地吻合。相应的比较47 Mipas proles的落球模型显示出良好的协议的温度与模式值的偏差直方图的2%，而Mipas密度平均低20%。利用流体静力平衡，这种平均密度偏差可以解释为米帕斯高度记录向下移动了1.6公里。在Envisat数据处理的早期阶段，Sciamachy的2级Proles还不可用。在Sciamachy目前可获得的少数最低点数据中，我们发现了一个非常接近的巧合，我们可以比较云顶压力：激光雷达在比最低点数据产品le高出3公里的高度检测到云顶。使用Envisat数据产品的工作揭示了早期软件版本GOPR LV 2 5.3、MIPAS/4.53和SCIA/3.51生成的一些数据的几个意想不到的特性。未来的环境卫星2级产品应明确识别环境卫星仪器测量的结果，而不是用于便利数据处理的气候数据或先验模型样本。质量控制应包括与地球大气中出现的物理定律和大气特性值范围界限的一致性检查。
The vertical structure of the terrestrial atmosphere is governed by hydrostatic equilibrium, which relates altitude, temperature, and pressure (or density). The mixing ratios derived for the chemically important trace gases depend on a precise knowledge of this basic atmospheric structure. The Bonn University backscatter lidar on the Esrange (68N, 21E) near Kiruna, Sweden, was operated from mid-July to the end of August 2002 to obtain atmospheric structure data, i.e. altitude proles of temperature and relative density for Envisat validation. In all we could perform 36 measurement runs with the lidar, of which 34 yielded usable density and temperature proles as well as several observations of tropospheric and mesospheric clouds. The three Envisat atmospheric instruments Gomos, Mipas, and Sciamachy measure altitude proles of temperature and density or pressure. This validation report reects the state of the operational inversion software for these three instruments up to mid-November 2002. Comparisons of 38 Gomos proles with lidar data in the altitude range 30 to 70 km show the shape of the density proles to agree to better than 2 % and the mean deviation for temperatures does not exceed 1.4 % or 3-4 K. The Gomos altitude registration agrees with the lidar altitudes to better than 300 m. Independently Envisat instrument proles were compared to an empirical model of the middle atmosphere in Arctic summer above northern Scandinavia, which is based on a decade with falling sphere measurements from the Andya Rocket Range in northern Norway. Comparing 48 Gomos proles to the falling sphere statistics in the altitude range 35 to 93 km shows on average an excellent agreement with mode values of deviation histograms being -0.6 % (i.e. 1.2-1.5 K) for the temperature and -1.8 % for the density. In the Gomos product les are in addition given pressure and temperature values from an internal model, which agree even better with the Gomos optimum proles of density and temperature. The corresponding comparison of 47 Mipas proles to the falling sphere model shows good agreement for the temperatures with a mode value of the deviation histogram of 2 %, whereas the Mipas densities were low on average by 20 %. Using hydrostatic equilibrium this mean density deviation can be interpreted as a downward shift in the Mipas altitude registration by 1.6 km. At this early stage of the Envisat data processing level 2 proles from Sciamachy were not yet available. In the few nadir data presently available for Sciamachy we found one close coincidence for which we could compare cloud top pressure: the lidar detected the cloud top at an altitude 3 km higher than given in the nadir data product le. Working with the Envisat data products revealed several unexpected properties for some of the data generated by the early software versions GOPR LV2 5.3, MIPAS/4.53, and SCIA/3.51. Future Envisat level-2 products should unambigiously identify results from Envisat instruments measurements as opposed to climatological data or a priori model proles which were used to facilitate data processing. The quality control should include consistency checks with physical laws and bounds on the range of values of atmospheric properties as they occur in the terrestrial atmosphere.