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Using uncertainty of Penman and Penman–Monteith methods in combined satellite and ground-based evapotranspiration estimates

Westerhoff, R.S.
Remote sensing of environment 2015 v.169 pp. 102-112
climate, data collection, equations, evapotranspiration, land cover, relative humidity, remote sensing, satellites, solar radiation, temperature, uncertainty, uncertainty analysis, vegetation cover, New Zealand
Satellite data are often used for their ability to fill in temporal and spatial patterns in data-sparse regions. It is also known that global satellite products generally contain more noise than ground-based estimates. Data validation of satellite data often treats ground-based estimates as the ‘gold standard’: without error or uncertainty. In the estimation of evapotranspiration (ET) however, ground-based estimates have considerable uncertainty, caused by the input components of the ET equations. This research presents an analysis of uncertainty of reference ET (ET0) caused by these input components. A dataset of correlated random variables is generated for a country with a diverse climate and diverse density of ground observations: New Zealand. The uncertainty analysis shows that: ET0 is most sensitive to temperature, followed by solar radiation, relative humidity, and cloudiness ratio; and that uncertainty varies between 10% and 40% of ET0, and depends on the ET0 value. Using this uncertainty analysis, a set of correlated random variables, and a Monte-Carlo fitting approach, MOD16 satellite PET data becomes a ‘soft interpolator’ between ground-based ET0 estimates. The resulting 1km×1km monthly nation-wide dataset has the advantage of: taking into account land cover and vegetation characteristics through the use of satellite data; still abiding to local climate diversity and locally used standards through the use of ground-based estimates; and containing an uncertainty estimate. Further comparison suggests that original MOD16 satellite PET could estimate real PET better than using ground-based estimates of ET0. Further research recommends combination with other existing gridded ET estimates, and further validation of real PET estimates.