Conserving Land-Atmosphere Synthesis Suite (CLASS) v1.1

This dataset includes 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:

combine a range of existing global estimates,

are observationally constrained with in-situ observations,

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

This dataset was created by Dr Sanaa Hobeichi as part of her PhD with the ARC Centre of Excellence for Climate Systems Sciences, and as part of the ARCCSS research program - The role of land surface forcing and feedbacks for regional climate.