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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]

To evaluate numerical weather predictions (NWP) using observations, the horizontal, vertical and temporal resolution characteristics need to be considered to ensure consistency. Here, large‐aperture scintillometry (LAS) is used to derive turbulent sensible heat fluxes (QH), as the source area extents are comparable to NWP with horizontal grid box resolutions of order 1 km. We demonstrate our methodology using LAS observations undertaken in central London and the Met Office's operational forecast model for the United Kingdom (UKV). In the horizontal, we ensure consistency between the LAS source area locations and extent, as they vary with wind direction and stability, and therefore the NWP grid boxes that should be selected for comparison. In the vertical, the appropriate model level needs to be selected relative to the changing effective measurement height (zf) of the observations. The LAS fluxes time and space averaging allows QH to be obtained for time periods similar to the model timestep (e.g., 1 min) but the UKV does not explicitly represent higher‐frequency turbulent motions. During two spring days, three to five UKV grid boxes (1.5 km resolution) fall within the LAS source area (60%). However, with the model land cover data lacking realistic spatial variability, modelled effective surface QH spatial variability is small, leaving a central grid box on the LAS path representative. Larger differences occur between modelled QH at the surface and closest to zf, despite both theoretically being within the inertial sublayer. The modelled QH has better agreement with observed fluxes when averaged over long periods (10+ min cf. 1 min). As LAS‐derived QH has larger source areas than eddy covariance (EC) measurements, there are benefits to assessing NWP model performance with LAS. With multiple paths, spatial variability in response to changes in surface cover could be assessed at shorter times scales than possible with EC. [ABSTRACT FROM AUTHOR]

The UK Met Office has a 300‐m grid length numerical weather prediction (NWP) model running routinely over London and, in research mode, city‐scale hectometric grid length NWP has become commonplace. It is important to understand how moving from kilometre‐ to hectometre‐scale grid length NWP influences boundary‐layer vertical mixing. For a clear‐sky convective boundary layer (CBL) case study, using 55‐ and 100‐m grid length NWP, we demonstrate that CBL vertical mixing of passive scalar is almost fully resolved. Passive scalar converges near the surface after emission from an idealised pollution ground source representing city‐scale emissions, and is transported in updrafts preferentially into the upper boundary layer. Approximately 8 km downstream of the source edge, this causes 34%$$ 34\% $$ lower near‐surface concentrations compared with 1.5‐km grid length NWP, where vertical mixing is fully parameterised. This demonstrates that resolving ballistic‐type dispersion, which is not typically represented in NWP vertical mixing parameterisations, can have a leading‐order influence on city‐scale near‐surface pollution concentration. We present a simple analytical model that is able to capture diffusive and ballistic dispersion behaviour in terms of effective timescales. The timescale controlling how long it takes passive scalar to become well mixed in the CBL is ≈3$$ \approx 3 $$ times longer for 1.5‐km compared with 100‐ and 55‐m grid length NWP. [ABSTRACT FROM AUTHOR]

The existing medium-resolution land cover time series produced under the European Space Agency's Climate Change Initiative provides 29 years (1992-2020) of annual land cover maps at 300-m resolution, allowing for a detailed study of land change dynamics over the contemporary era. Because models need 2D parameters rather than 2D land cover information, the land cover classes must be converted into model-appropriate plant functional types (PFTs) to apply this time series to Earth system and land surface models. The first generation cross-walking table that was presented with the land cover product prescribed pixel-level PFT fractional compositions that varied by land cover class but lacked spatial variability. Here we describe a new ready-to-use data product for climate modelling: spatially explicit annual maps of PFT fractional composition at 300 m resolution for 1992-2020, created by fusing the 300 m medium-resolution land cover product with several existing high-resolution datasets using a globally consistent method. In the resulting data product, which has 14 layers for each of the 29 years, pixel values at 300-m resolution indicate the percentage cover (0-100 %) for each of 14 PFTs, with pixel-level PFT composition exhibiting significant intra-class spatial variability at the global scale. We additionally present an updated version of the user tool that allows users to modify the baseline product (e.g., re-mapping, re-projection, PFT conversion, and spatial sub-setting) to meet individual needs. Finally, these new PFT maps have been used in two land surface models - ORCHIDEE and JULES - to demonstrate their benefit over the conventional maps based on a generic cross-walking table. Regional changes in the fractions of trees, short vegetation, and bare soil cover induce changes in surface properties, such as the albedo, leading to significant changes in surface turbulent fluxes, temperature, and vegetation carbon stocks. [ABSTRACT FROM AUTHOR]