Joint UK Land Environment Simulator (JULES) is a community-developed land surface model (LSM) as used by the Met Office Unified Model for both weather and climate land surface representation.

We have compiled meteorological forcing datasets with a 30-min time step for the Cardington site to drive the JULES standalone LSM as a single point for the same period as the core archived files. JULES requires the following seven atmospheric input variables at every time step for it to able to run using prescribed meteorology: downwelling shortwave irradiance, downwelling longwave irradiance, rainfall, air temperature, mean horizontal wind, surface barometric pressure, and specific humidity. The drive dataset comprises a NetCDF file for each of the four drive heights (2, 10, 25 and 50 m), such that temperature, wind and humidity drive variables are taken from the different mast heights, and the pressure, radiation and rainfall remaining unchanged as they were only available from fixed levels i.e. pressure at 1.2 m, downwelling radiation at 4 m, upwelling radiation at 2 m, and rainfall at the surface. Due to the instrumentation deployed, the 2 m level drive data only available for 2012–2024. Only whole years are supplied in the forcing dataset. Although the NetCDF forcing dataset has been configured to run with JULES, it should be straightforward to apply the data within other LSMs that can be run offline and forced by prescribed meteorology for a single point

The datasets included here were all tested with version 7.4 of standalone JULES. An example use of running JULES using Cardington field data can be found in Osborne and Weedon (2021), wherein can be found soil and canopy properties for configuring JULES based on field data as an alternative to using operational model ancillary data.

JULES is available to anyone for non-commercial use, free of charge. However, please note the JULES licence conditions, the JULES Fair Use and Publication Policy and the MOSRS user terms and conditions. The JULES source code is available from the Met Office Science Repository Service to authenticated users only.

The JULES forcing datasets included here are gap-filled where data are either missing or deemed unreliable to ensure that every time step is populated. Short gaps (≤3 h) were filled via linear interpolation; longer gaps were filled with the long-term (20-yr) mean values calculated from available measurements for each time step. The latter method of gap-filling ensures the preservation of daily and annual cycles. Each driving data variable has a simple flag to indicate whether gap filling has been applied, or not, at each time step. The driving dataset could potentially be used to apply an optional spin-up to the simulations, for example by repeatedly driving the LSM with the first two years of data so that the soil temperature and soil moisture reach stability.