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The UK Met Office state‐of‐the‐art, deterministic, convection‐permitting, coupled land‐atmosphere, regional weather forecasting system, known as the UKV or UK Variable resolution model (Tang et al. Meteorological Applications, 2013; 20:417–426), has been operational since 2015. Science updates are regularly made to the UKV land surface data assimilation scheme when those updates improve predictions of screen temperature and humidity, since these quantities have a direct impact on atmospheric states and weather forecasts. Less attention has been paid to whether UKV soil moisture analyses are close to independent, in‐situ soil moisture observations, partly because it is difficult to make meaningful comparisons between 1.5 km2 gridded model outputs and traditional point sensor measurements. Soil moisture is recognized to be important when hydrological forecasts for runoff and rivers are required. This is because soil moisture controls the extent to which rainfall can infiltrate the soil, and the amount of surface runoff affects the timing of peak river flows (Ward & Robinson, Principles of Hydrology. McGraw‐Hill Publishing Company; 2000; Singh et al. Water Resources Research, 2021, 57, e2020WR028827). Gómez et al. (Remote Sensing, 2020; 12:3691) report benefits to river flow forecasts when using soil moisture data assimilation in the UKV system instead of a daily downscaled product from the Met Office global model. The Met Office measures soil temperature and soil moisture at Cardington (Osborne & Weedon, Journal of Hydrometeorology, 2021, 22:279–295); there is no other UK Met Office site at which soil moisture is measured. In this study, we use field‐scale (~200 m radius) soil moisture measurements from the UK Centre for Ecology and Hydrology's (UKCEH's) COSMOS‐UK network to provide independent verification and analysis of UKV soil moisture during summer 2018, an unusually dry period in the United Kingdom. We find that the match to COSMOS‐UK soil moisture observations is generally good, and that changes made to the land data assimilation approach during a recent operational upgrade had a generally beneficial impact on UKV soil moisture analyses under very dry conditions. [ABSTRACT FROM AUTHOR]

We document the development of the first version of the U.K. Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane, and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land, and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall, the model performs well, with a stable pre‐industrial state and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealized simulations show a high climate sensitivity relative to previous generations of models: Equilibrium climate sensitivity is 5.4 K, transient climate response ranges from 2.68 to 2.85 K, and transient climate response to cumulative emissions is 2.49 to 2.66 K TtC−1. Plain Language Summary: We describe the development and behavior of UKESM1, a novel climate model that includes improved representations of processes in the atmosphere, ocean, and on land. These processes are inter‐related: For example, dust is produced on the land and blown up into the atmosphere where it affects the amount of sunlight falling on Earth. Dust can also be dissolved in the ocean, where it affects marine life. This in turn changes both the amount of carbon dioxide absorbed by the ocean and the material emitted from the surface into the atmosphere, which has an affect on the formation of clouds. UKESM1 includes many processes and interactions such as these, giving it a high level of complexity. Ensuring realistic process behavior is a major challenge in the development of our model, and we have carefully tested this. UKESM1 performs well, correctly exhibiting stable results from a continuous pre‐industrial simulation (used to provide a reference for future experiments) and showing good agreement with observations toward the end of its historical simulations. Results for some properties—including the degree to which average surface temperature changes with increased amounts of carbon dioxide in the atmosphere—are examined in detail. Key Points: UKESM1 represents a major advance over its predecessor HadGEM2‐ES, both in the complexity of its components and its internal couplingThe complex coupling presents challenges to the model development; we document the tuning process employed to obtain acceptable performanceUKESM1 performs well, having a stable pre‐industrial state and showing good agreement with observations in a wide variety of contexts [ABSTRACT FROM AUTHOR]

This article describes how The MathWorks Inc. approaches usability testing of documentation and incorporates usability testing into its writing process through a Documentation Usability Team. The MathWorks Inc. produces over 65 software packages that scientists, engineers and students use for technical computing. Cross-functional teams carry out software development at The MathWorks Inc. The MathWorks Inc. has shifted its emphasis for customer documentation from printed to online. Users view the documentation through a customized help browser that provides navigation with a table of contents, index and full-text search. The Documentation Usability Team's permanent members include a usability specialist and writers representing the company's different product areas. The Documentation Usability Team uses a testing process that focuses on two major aspects of documentation: the content and the presentation of technical information. The team uses documentation to determine how successful customers can perform realistic tasks with the products, while relying on the documentation to provide direction. When writers sign up to perform their first documentation usability test, the Documentation Usability Team guides them through the process.

Soil moisture is an important component of the Earth system and plays a key role in land-atmosphere interactions. Remote sensing of soil moisture is of great scientific interest and the scientific community has made significant progress in soil moisture estimation using Earth observations. Currently, several satellite-based coarse spatial resolution soil moisture datasets have been produced and widely used for various applications in climate science, hydrology, ecosystem research and agriculture. Owing to the strong demand for soil moisture data with high spatial resolution for regional applications, much effort has recently been devoted to the generation of high spatial resolution soil moisture data from either high-resolution satellite observations or by downscaling existing coarse-resolution satellite-based soil moisture datasets. In addition, land surface models provide an alternative way to obtain consistent high-resolution soil moisture information when forced with high-resolution inputs. The aim of this study is to create and evaluate high-resolution soil moisture products derived from multiple sources including satellite observations and land surface model simulations. The JULES-CHESS simulated soil moisture and satellite-based soil moisture datasets including SMAP L3E, SMAP L4, SMOS L4, Sentinel 1, ASCAT, and Sentinel 1/SMAP combined products were first validated against observed soil moisture from COSMOS-UK, a network of in-situ cosmic-ray based sensors. Second, an approach based on triple collocation was applied to compare these satellite products in the absence of a known reference dataset. Third, a combined soil moisture product was generated to integrate the better-performing soil moisture estimates based on triple collocation error estimation and a least-squares merging scheme. From further evaluation, it is found that the merged soil moisture integrates the characteristics of model simulation and satellite observations and particularly improves the limited temporal variability of the JULES-CHESS simulation. Therefore, we conclude that the triple collocation merging scheme is a simple and reliable way to combine satellite-based soil moisture products with outputs from the JULES-CHESS simulation for estimating model-data fused high-resolution soil moisture for the British mainland. • Evaluation of satellite and JULES-CHESS soil moisture against 38 COSMOS-UK sites. • SMAP L3E and JULES-CHESS show better performance compared to other products. • All products show high errors over surface with organic soils. • Blended soil moisture integrates both model and satellite characteristics. [ABSTRACT FROM AUTHOR]

The decreasing trend in global burnt area, attributed to increased human impact in tropical savannas, has received a lot of recent attention. However, less attention has been directed at burnt area trends and it's drivers in fire deficient forested ecosystems where even small changes in fire could have a major impact on local biogeochemistry. We map the sensitivity of burnt area to relevant controls using a simple framework whereby limitations are imposed on fire by fuel continuity; fuel moisture; natural and human ignitions; and land use suppression. These controls are described from remotely sensed and meteorological observations and optimized against the Global Fire Emissions Database (GFED4s) burnt area observations. We use a Bayesian inference technique to optimize our framework which allows us to constrain and quantify the uncertainty of our fire controls. Fuel continuity and fuel moisture are shown to be the main controls over much of the world, decreasing burnt area by 60±2% and 41±10% respectively. This is followed by land use suppression at 29±13%, where cropland in particular is shown to affect burnt area beyond its own extent suggesting significant fragmentation effects. Ignitions only reduce burnt area by 21±19%. We use our framework to evaluate the drivers behind recent trends in burnt areas across all ecosystems. Areas with trends in more than one control, often with opposite effects on burnt area, were identified as key hotspots of fire regime change. Trends in controls have a much larger impact on burnt area outside of tropical savannas, with the biggest shifts found in tropical and boreal forest ecosystems driven by changes in climate conditions affecting fuel continuity and moisture content. We also compared the impact of fire on tree cover relative to other climate and human controls, and show that fire has a much smaller influence on tree cover in savanna ecosystem than normally assumed - reducing cover by only 1.71±0.44%. Forested areas however, are much more sensitive and therefore vulnerable to small increases in fire-induced stress. These studies have a number of implications for fire modelling. Land use has a larger impact on both fire and tree cover than fire enabled global vegetation models currently simulate. Whereas fire itself seems to have very little impact on tree cover in areas which already experience regular burning such as tropical savannas, but has the potential to impact cover under environmental change in more humid forests. This gives added impetus to understanding the impacts of fire regime trends on local ecosystem function and services in forested areas, as well as their feedback to the wider Earth System. [ABSTRACT FROM AUTHOR]