4.7 Article

Complementary Relationship for evaporation performance at different spatial and temporal scales

期刊

JOURNAL OF HYDROLOGY
卷 608, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.jhydrol.2022.127575

关键词

Evaporation; Scaling; Potential evaporation; Complementary relationship

资金

  1. BME Water Sciences & Disaster Prevention [TKP2020 IE]
  2. NKFIH Hungary [BME IE-VIZ TKP2020]
  3. NIFA (USGS) [IDA01584]

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This study aims to compare multiple versions of the Complementary Relationship (CR) between actual regional evaporation and apparent potential evaporation, and investigate their response to changes in spatial and temporal scaling. By using data from seven eddy-covariance flux stations in Australia and global ERA5 reanalysis data, the performance and parameter values of these versions were assessed.
Several versions of the Complementary Relationship (CR) between actual regional evaporation and apparent potential evaporation have recently been proposed. Few studies have compared multiple CR versions side-by-side using datasets spanning various climates and land surfaces. Filling this lack is one purpose of this project. It also investigates how various CR versions respond to changes in spatial and temporal averaging. This study uses multiple years of data from seven eddy-covariance flux stations in Australia, representing a wide range of biomes, along with global ERA5 reanalysis data products. Daily and monthly averages were used for both datasets, and the Australian observations also used weekly and yearly averages. The ERA5 data represent a scale of about 30 km, much larger than the scale represented by the flux station data. A set of five questions regarding the impact of spatial and temporal scaling on CR parameter values and performance are asked and assessed using the two datasets. Four recent CR versions are considered in answering the questions. Due to important differences between FLUXNET and ERA5 data, questions regarding temporal scaling were answered with greater confidence than those regarding spatial scaling. With these data, rescaled versions of the CR performed best overall.

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