Conserving Land-Atmosphere Synthesis Suite (CLASS) v 1.0

IMPORTANT: This version of CLASS has been withdrawn because an error in the calculations used has been found by the dataset producer. A new corrected version has been published as v1-1 https://researchdata.ands.org.au/conserving-land-atmosphere-v-11/1425145 The errors were caused by entering the ori...

Full description

Bibliographic Details
Other Authors: Sanaa Hobeichi (hasCollector), ARC Centre of Excellence for Climate System Science Data Manager (isManagedBy), ARC Centre of Excellence for Climate System Science (Owner of)
Format: Dataset
Language:unknown
Published: ARC Centre of Excellence for Climate System Science
Subjects:
Online Access:https://researchdata.ands.org.au/conserving-land-atmosphere-v-10/1360835
https://doi.org/10.25914/5c3bcd55afd26
Description
Summary:IMPORTANT: This version of CLASS has been withdrawn because an error in the calculations used has been found by the dataset producer. A new corrected version has been published as v1-1 https://researchdata.ands.org.au/conserving-land-atmosphere-v-11/1425145 The errors were caused by entering the original Ground Heat flux data with the right magnitude but wrong sign. All variables are affected. --- In this work, we develop a Conserving Land-Atmosphere Synthesis Suite (CLASS) of estimates of simultaneously balanced surface water and energy budget components over 2003-2009 that are coherent by being able to solve the water and energy budgets simultaneously at 0.5-degree grid scale. The individual budget variables, where possible: 1) combine a range of existing global estimates, 2) are observationally constrained with in-situ observations, 3) have uncertainty estimates that reflect their agreement with in-situ measurements. To derive the hybrid estimates of the individual budget terms we merged available datasets by implementing a weighting approach that accounts for both the performance of the datasets against in-situ measurements as well as their error dependance. Then, we adjusted all the budget terms simultaneously based on their relative errors by applying an objective variational data assimilation technique that enforces the physical constraints of the surface water and energy budgets linked through the equivalence of evapotranspiration and latent heat. The final output is a monthly, 0.5-degree, global dataset of the water and energy budget variables over 2003-2009 and include estimates for: Net radiation flux (Rn) and its associated uncertainty, Sensible heat flux (H) and its associated uncertainty, Latent heat flux (LH) and its associated uncertainty, Ground heat flux (G) and its associated uncertainty, Precipitation (P) and its associated uncertainty Total runoff (Q) and its associated uncertainty Change in water storage (deltaS) and its associated uncertainty When all the energy budget variables are changed to positive when upward, they satisfy Rn=H+LH+G When the latent heat flux (LH) is converted to the same unit as the water budget terms, the hydrologic variables satisfy: P=LH + Q + deltaS The uncertainty of each flux is computed from its discrepancy with in-situ observations