AIRCRAFT FLUX-FILTERED: NRCC (FIFE)

The purpose of this study was to develop alternatives to ground-based measurements in order to obtain information required to predict the effects of soil and land use on the fluxes of greenhouse gases, the surface energy balance, and the water balance. Satellite-based algorithms have been developed via flux measurements from an aircraft to estimate vegetation and soil conditions on a regional scale. The purpose of the Twin Otter FIFE flights was to make measurements in the boundary layer of the fluxes of sensible and latent heat, momentum, and carbon dioxide, plus supporting meteorological parameters such as temperature, humidity, wind speed, and direction. Aircraft position, heading, and altitude were also recorded, as were several radiometric observations for use in interpretation of these data. The Twin Otter aircraft allows steady flight trajectories at low airspeed (50-60 [m][sec^-1]) down to levels less than 10 m above the ground. The aircraft is instrumented to measure the contribution of flux densities of momentum, sensible, and latent heat, and CO2 over a frequency range of 0 to 5 Hz (MacPherson et al., 1981). All the flux measurements were obtained with the eddy-correlation method, wherein the aircraft is equipped with an inertial platform, accelerometers, and a gust probe for measurement of earth-relative gusts in the x, y, and z directions. Gusts in these dimensions are then correlated with each other for momentum fluxes and with fluctuations in other variables to obtain the various scalar fluxes, such as temperature (for sensible heat flux) and water vapor mixing ratio (for latent heat flux). The fluctuations in all variables were calculated with three different methods (the arithmetic means removed, the linear trends removed, or filtered with a high-pass recursive filter) prior to the eddy correlation calculations. This data set contains data that were high-pass filtered with a third order algorithm with a break point set at 0.012 Hz (5 km wavelength). Through this research, it is hoped that techniques can be developed to utilize satellite data for global monitoring of crop health and climate change本研究旨在开发地面观测的替代方案，以获取所需信息，进而预测土壤与土地利用对温室气体通量、地表能量平衡及水平衡的影响。研究人员依托航空器获取的通量观测数据，开发了基于卫星的算法，用于估算区域尺度下的植被与土壤状况。双水獭（Twin Otter）FIFE飞行任务的核心目标，是在大气边界层内开展观测，获取感热通量、潜热通量、动量通量与二氧化碳通量，同时同步采集温度、湿度、风速及风向等配套气象参数。此外还记录了航空器的位置、航向与飞行高度，并开展了多项辐射观测，以辅助上述观测数据的解译工作。双水獭航空器可实现低空低速稳定飞行，最低飞行高度可降至距地面不足10米，飞行速度控制在50~60米每秒。该航空器配备了观测系统，可在0至5赫兹的频率范围内，测量动量、感热、潜热与二氧化碳的通量密度（MacPherson等，1981）。所有通量观测均采用涡动相关法（eddy-correlation method）开展：航空器搭载有惯性平台（inertial platform）、加速度计（accelerometers）与阵风探针（gust probe），用于测量x、y、z三个方向相对于地球坐标系的阵风信号。随后将上述三个方向的阵风信号进行互相关计算以获取动量通量，并将其与其他变量的脉动信号进行关联，从而得到各类标量通量——例如用于感热通量的温度脉动信号，以及用于潜热通量的水汽混合比脉动信号。在开展涡动相关计算前，需通过三种不同方法对所有变量的脉动信号进行预处理：移除算术平均值、移除线性趋势，或采用高通递归滤波器（high-pass recursive filter）进行滤波。本数据集包含经三阶算法高通滤波后的数据，该算法的截止频率设置为0.012赫兹（对应波长5千米）。通过本研究，我们期望能够开发出利用卫星数据开展全球作物健康监测与气候变化监测的技术方法。