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

• Published in: Remote sensing of environment 2015-11, Vol.169, p.102-112
• Main Author: Westerhoff, R.S.
• Format: Article
• Language: English
• Subjects: Climate; Estimates; Evapotranspiration; Ground-based estimates; Mathematical analysis; MOD16; Monte-Carlo fitting; PET; Random variables; Reference ET; Satellites; Sensitivity analysis; Uncertainty
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2015.07.021

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. •Satellite PET data are used to interpolate ground-based ET0 estimates.•Sensitivity analyses of ground-based ETo lead to dynamic error characterisation.•Uncertainty of ground-based ETo leads to better estimates in data-sparse areas.•Global satellite products can be used while still abiding to regional standards.•A national dataset of 1km×1km monthly reference crop ET