Spectral Downscaling of Integrated Water Vapor Fields From Satellite Infrared Observations
Spectral Downscaling of Integrated Water Vapor Fields From Satellite Infrared Observations
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DOI：
10.1109/tgrs.2011.2161996
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发表时间：
2012-02
影响因子：
8.2
通讯作者：
M. Montopoli;N. Pierdicca;F. Marzano
中科院分区：
文献类型：
--
作者：
M. Montopoli;N. Pierdicca;F. Marzano
大气水汽是影响气候变化和水文循环过程的重要组成部分，另一方面，它对电磁信号传播也有显着影响。由于大气水汽的分布随时间、地点和高度变化很大，因此有必要对其进行高时空分辨率的监测。不幸的是，由于缺乏足够的空间和时间观测尺度的气象仪器，很难绘制其空间分布图。对于许多地球物理应用，也有必要重建的综合可降水量的空间细节，从信息只能在粗空间尺度。空间降尺度方法可以发挥重要作用时，高分辨率水汽检索从相对较新的传感器，如合成孔径雷达，或从传统的传感器，如红外辐射计中分辨率成像光谱仪（MERIS）或中分辨率成像光谱仪（MODIS），协同使用，以提高综合水汽检索的准确性。在这种情况下，本文介绍了一些新的方法方面，提高空间分辨率的综合可降水量观测使用统计降尺度光谱方法。为了突出的潜力和实用性，建议的降尺度估计程序，搭配使用250米MERIS和1公里的中分辨率成像光谱仪收购。结果表明，光谱降尺度的能力，再现相当不错的二阶统计变异的水汽场在小的空间尺度与传统的插值技术的均方根误差。
Atmospheric water vapor is a crucial constituent affecting both climate change and hydrological cycle processes, whereas on the other hand, it has a significant impact on the electromagnetic signal propagation. Since the distribution of atmospheric water vapor strongly varies with time, location, and altitude, it is necessary to monitor it at high spatial and temporal resolution. Unfortunately, mapping its spatial distribution is difficult due to the lack of meteorological instrumentation at an adequate spatial and temporal observation scale. For many geophysical applications, there is also the need to reconstruct spatial details of integrated precipitable water vapor from information available only at coarser spatial scales. Spatial downscaling approaches can play a significant role when high-resolution water vapor retrievals from relatively new sensors, like synthetic aperture radars, or from conventional sensors, like the infrared radiometers MEdium Resolution Imaging Spectrometer (MERIS) or Moderate Resolution Imaging Spectroradiometer (MODIS), are used in synergy to enhance the accuracy of integrated water vapor retrievals. In this context, this paper introduces some new methodological aspects to increase the spatial resolution of integrated precipitable water vapor observations using a statistical downscaling spectral approach. To highlight the potential and the usefulness of the proposed downscaling estimation procedure, collocated 250-m MERIS and 1-km MODIS acquisitions are used. Results reveal the ability of spectral downscaling to reproduce quite well the second-order statistical variability of the water vapor field at small spatial scales with a root-mean-square error comparable with conventional interpolation techniques.