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Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites. Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models. In all but two cases, latent heat flux and net ecosystem exchange of CO2 are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can know that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development. [ABSTRACT FROM AUTHOR]

The third version of the Regional Atmosphere and Land (RAL3) science configuration is documented. Developed through international partnership, RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator when applied across timescales with kilometre and sub-km scale model grids. The RAL3 configuration represents a major advance compared to previous versions by delivering a common science definition suitable for application to tropical and mid-latitude regions. Developments within RAL3 include the introduction of a double-moment microphysics scheme and a bi-modal cloud scheme, replacing use of a single-moment scheme and different cloud schemes for mid-latitudes and tropics in previous versions. Updates have been implemented to the boundary layer scheme and a consolidation of land model settings to be more consistent with Global Atmosphere and Land (GAL) science configurations. Physics developments aimed to address priorities for model performance improvement identified by users. This paper documents the RAL3 science configuration, including a series of iterative revisions delivered since its first release, and their characteristics. Evidence is provided from the variety of assessments of RAL3, relative to the previous version (RAL2). Collaborative development and evaluation across organisations has enabled evaluation across a range of domains, grid-spacing and timescales. The analysis indicates more realistic precipitation distributions; improved representation of clouds and of visibility; a continued trend to more realistic representation of convection; and reduced near-surface wind speeds, but a persistent cold temperature bias. Overall the convective-scale verification scores and climatological model distributions relative to observations improve for the majority of variables. Ensemble results show improvements to the spread-error relationship. User feedback from subjective assessment activities has also been positive. Differences between RAL3 revisions and RAL2 are further illustrated through process-based analysis of a convective system over the UK. The latest RAL3 configuration (RAL3.3) is therefore recommended for research, operational numerical weather prediction and climate production at km and sub-km scales. [ABSTRACT FROM AUTHOR]

Given difficulties with modelling radiation fog and the similarity of meteorological conditions linked to dewfall and frost we investigated the formation of dew, frost and fog. For a site in the UK seven years of data were analysed representing high‐resolution atmospheric profiles and dew meter measurements for radiation nights with stable conditions. Classical dewfall occurs by condensation when the surface is below the dew point and cooler than the air above. However, the profiles show that, in the absence of fog, typically dew and frost form with the surface warmer than the immediately overlying air due to lifted temperature minima (LTMs) at about 0.15 m. Observations of aerosol number density and average hydrated radii show that aerosol optical extinction (and hence their radiative effect) is weakly but significantly correlated with the intensity of LTMs. Low wind speed on stable nights allows settling of aerosols which radiatively cool the air near the ground more quickly than the surface cools – thus creating LTMs. In the presence of LTMs typically dew and frost form not by condensation, but by occult deposition of water droplets onto the canopy and ground. Among radiation fog observations, 91% are associated with light near‐surface winds and LTMs. When the rate of removal of suspended water droplets by occult deposition generating dew or frost is too slow, then build‐up of droplets in the air just above the surface leads to the formation of radiation fog. Future modelling should allow for the accumulation of near‐surface aerosols and their radiative effects during stable nights to represent the formation of LTMs. Modelling of typical dew and frost will require representation of occult deposition. Assessing rates of occult deposition compared to rates of generation of suspended water droplets is needed to forecast the onset of radiation fog formed near the ground. [ABSTRACT FROM AUTHOR]

The interactions between the land surface and the atmosphere can impact weather and climate through the exchanges of water, energy, carbon and momentum. The properties of the land surface are important when modelling these exchanges correctly especially with models being used at increasingly higher resolution. The Joint UK Land Environment Simulator (JULES) currently uses a tiled representation of land cover but can only model a single dominant soil type within a grid box. Hence, there is no representation of sub-grid scale soil heterogeneity. This paper introduces and evaluates a new flexible surface-soil tiling scheme in JULES. Several different soil tiling approaches are presented for a synthetic case study. The changes to model performance have been compared to the current single soil scheme and a high resolution 'Truth' scenario. Results have shown that the different soil tiling strategies do have an impact on the water and energy exchanges due to the way vegetation accesses the soil moisture. Tiling the soil according to the surface type, with the soil properties set to the dominant soil type under each surface is the best performing configuration. The results from this setup simulate water and energy fluxes that are the closest to the high resolution 'Truth' scenario but require much less information on the soil type than the high resolution soil configuration. [ABSTRACT FROM AUTHOR]