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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. Field‐scale observations of soil moisture from cosmic‐ray neutron sensors in the COSMOS‐UK network are compared to soil moisture analyses from the Met Office's operational regional modelling system. Results show that the model did a good job in the dry summer of 2018 at sites across the United Kingdom.

Near‐surface observations can suffer from significant representativeness errors, especially for Numerical Weather Prediction (NWP) at lower resolution in global applications. Therefore, in Data Assimilation (DA), many operational centers have long been reluctant to assimilate them (e.g., the European Center for Medium‐range Weather Forecast, ECMWF, started assimilating all 6‐h screen‐level temperature reports only in 2024). For forecast verification, some studies advocate that we should not rely on them and use only verification against our own near‐surface analyses. At Environment and Climate Change Canada (ECCC), both temperature and humidity observations from SYNOPs have been assimilated in our global NWP system for more than two decades and, in June 2024, METARs have been added following some positive impacts found only when comparing forecasts against near‐surface observations. To shed light on the impact of the assimilation of screen‐level observations, in this study we present an evaluation of the impact of removing the assimilation of all screen‐level temperature and humidity observations using various verification references: the NWP forecasts were evaluated against radiosondes and surface observations, independent (ECMWF) analysis, our own analysis and surface analysis. Results show that, despite the lack of a proper estimation of representativeness errors in the DA approach, the assimilation of screen‐level temperature and humidity leads to forecast improvements that can be detected from the verification against independent measurement sources, here radiosondes and ECMWF upper‐air analyses. Verification against own analyses, for both upper‐air and screen‐level variables, led instead to opposite and misleading conclusions. In fact, the removal of assimilated screen‐level temperature and humidity measurements renders the NWP forecast more similar to the own analysis, therefore leading to better scores but detachment from the observed world. The assimilation of screen‐level temperature and humidity leads to forecast improvements that can be detected from the verification against independent measurement sources (radiosondes, station measurements and ECMWF analyses ‐ top panel). Verification against own analyses leads instead to misleading conclusions near the surface (bottom panel), due to the forecast‐analysis “incestuousness” (aka the dependence of the analysis on the forecast model). These findings lead to strengthening the recommendation of operational verification against several and independent datasets.

With the crisis awareness of global warming and natural disasters, utilization of local wood has drawn increasing attention in achieving the Sustainable Development Goals (SDGs). It is necessary to investigate the deformation and fracture of the structural tissue in wood in order to improve the safety and reliability of wood application. However, deformation and fracture mechanisms of the structural tissue in each annual ring are unknown. The mechanical characteristics of wood are reflected in the properties of earlywood and latewood. In the present study, microstructural observation and tensile tests were conducted to examine the relationship between the mechanical properties and fracture behavior of latewood in the growth direction in Japanese cedar. Brittle fracture behavior of the latewood specimen was confirmed based on the tensile stress–strain curve and features of the fracture surface. Moreover, two fracture modes, tensile fracture and shear fracture, were recognized. Weibull analysis of tensile strength in each fracture mode was performed to evaluate the reliability and utility of brittle latewood. Lastly, two fracture mechanisms were discussed based on the failure observation findings by a scanning electron microscope.

The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a ‘‘best estimate’’ of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.

Understanding of hydroclimatic processes in Africa has been hindered by the lack of in situ precipitation measurements. Satellite-based observations, in particular, the TRMM Multisatellite Precipitation Analysis (TMPA) have been pivotal to filling this void. The recently released Integrated Multisatellite Retrievals for GPM (IMERG) project aims to continue the legacy of its predecessor, TMPA, and provide higher-resolution data. Here, IMERG-V04A precipitation data are validated using in situ observations from the Trans-African Hydro-Meteorological Observatory (TAHMO) project. Various evaluation measures are examined over a select number of stations in West and East Africa. In addition, continent-wide comparisons are made between IMERG and TMPA. The results show that the performance of the satellite-based products varies by season, region, and the evaluation statistics. The precipitation diurnal cycle is relatively better captured by IMERG than TMPA. Both products exhibit a better agreement with gauge data in East Africa and humid West Africa than in the southern Sahel. However, a clear advantage for IMERGis not apparent in detecting the annual cycle. Although all gridded products used here reasonably capture the annual cycle, some differences are evident during the short rains inEast Africa. Direct comparison between IMERG and TMPA over the entire continent reveals that the similarity between the two products is also regionally heterogeneous. Except for Zimbabwe and Madagascar, where both satellite-based observations present a good agreement, the two products generally have their largest differences over mountainous regions. IMERG seems to have achieved a reduction in the positive bias evident in TMPA over Lake Victoria.

Present-day precipitation–temperature scaling relations indicate that hourly precipitation extremes may have a response to warming exceeding the Clausius–Clapeyron (CC) relation; for the Netherlands the dependency on surface dewpoint temperature follows 2 times the CC relation (2CC). The authors’ hypothesis—as supported by a simple physical argument presented here—is that this 2CC behavior arises from the physics of convective clouds. To further investigate this, the large-scale atmospheric conditions accompanying summertime afternoon precipitation events are analyzed using surface observations combined with a regional reanalysis. Events are precipitation measurements clustered in time and space. The hourly peak intensities of these events again reveal a 2CC scaling with the surface dewpoint temperature. The temperature excess of moist updrafts initialized at the surface and the maximum cloud depth are clear functions of surface dewpoint, confirming the key role of surface humidity on convective activity. Almost no differences in relative humidity and the dry temperature lapse rate were found across the dewpoint temperature range, supporting the theory that 2CC scaling is mainly due to the response of convection to increases in near-surface humidity, while other atmospheric conditions remain similar. Additionally, hourly precipitation extremes are on average accompanied by substantial large-scale upward motions and therefore large-scale moisture convergence, which appears to accelerate with surface dewpoint. Consequently, most hourly extremes occur in precipitation events with considerable spatial extent. Importantly, this event size appears to increase rapidly at the highest dewpoint temperature range, suggesting potentially strong impacts of climatic warming.

Targeted observations of submesoscale currents are necessary to improve science’s understanding of oceanic mixing, but these dynamics occur at spatiotemporal scales that are currently challenging to detect. Prior studies have recently shown that the submesoscale surface velocity field can be measured by tracking hundreds of surface drifters released in tight arrays. This strategy requires drifter positioning to be accurate, frequent, and to last for several weeks. However, because of the large numbers involved, drifters must be low-cost, compact, easy to handle, and also made of materials harmless to the environment. Therefore, the novel Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) drifter was designed following these criteria to facilitate massive sampling of near-surface currents during the Lagrangian Submesoscale Experiment (LASER). The drifting characteristics were determined under a wide range of currents, waves, and wind conditions in laboratory settings. Results showed that the drifter accurately follows the currents in the upper 0.60 m, that it presents minimal wave rectification issues, and that its wind-induced slip velocity is less than 0.5% of the neutral wind speed at 10 m. In experiments conducted in both coastal and deep ocean conditions under wind speeds up to 10 m s −1 , the trajectories of the traditional Coastal Ocean Dynamics Experiment (CODE) and the CARTHE drifters were nearly identical. Following these tests, 1100 units were produced and deployed during the LASER campaign, successfully tracking submesoscale and mesoscale features in the Gulf of Mexico. It is hoped that this drifter will enable high-density sampling near metropolitan areas subject to stress by the overpopulation, such as lakes, rivers, estuaries, and environmentally sensitive areas, such as the Arctic.

The far infrared region plays a critical role in the Earth's greenhouse effect. Measurements across this range are limited and previous studies have found it challenging to achieve radiative closure between different instruments across the mid‐far infrared. This study compares high‐resolution downwelling spectra measured from the surface in the Arctic to radiative transfer simulations run with atmospheric profiles from a radiosonde, microwave radiometer, and the 5th ECMWF atmospheric reanalysis. The radiosonde‐driven simulation generates the closest agreement to the radiance observations. The HATPRO‐driven simulation matches within its uncertainty across the entire range. However, it has a larger uncertainty envelope than the other sources. There is a bias in all three simulations associated with underestimated humidity. Our results reiterate the sensitivity of the far infrared to the humidity profile. This suggests that the wider deployment of spectrometers capable of measuring across this region, in parallel with efforts to improve knowledge of far infrared water vapour spectroscopy, could markedly improve our ability to routinely characterise polar environments. A clear‐sky infrared spectrum extending into the far‐infrared is compared to radiative transfer simulations. The radiosonde‐driven simulation generates the closest agreement to the radiance observations. The HATPRO‐driven simulation matches within its uncertainty across the entire range; however, it has a larger uncertainty envelope than the other sources. There is a bias in all three simulations associated with underestimated humidity.

On 30 September 2021, a saildrone uncrewed surface vehicle (USV) was steered into category 4 Hurricane Sam, the most intense storm of the 2021 Atlantic hurricane season. It measured significant wave heights up to 14 m (maximum wave height = 27 m) and near-surface winds exceeding 55 m s−1. This was the first time in more than seven decades of hurricane observations that in real time a USV transmitted scientific data, images, and videos of the dynamic ocean surface near a hurricane’s eyewall. The saildrone was part of a five-saildrone deployment of the NOAA 2021 Atlantic Hurricane Observations Mission. These saildrones observed the atmospheric and oceanic near-surface conditions of five other tropical storms, of which two became hurricanes. Such observations inside tropical cyclones help to advance the understanding and prediction of hurricanes, with the ultimate goal of saving lives and protecting property. The 2021 deployment pioneered a new practice of coordinating measurements by saildrones, underwater gliders, and airborne dropsondes to make simultaneous and near-collocated observations of the air–sea interface, the ocean immediately below, and the atmosphere immediately above. This experimental deployment opened the door to a new era of using remotely piloted uncrewed systems to observe one of the most extreme phenomena on Earth in a way previously impossible. This article provides an overview of this saildrone hurricane observations mission, describes how the saildrones were coordinated with other observing platforms, presents preliminary scientific results from these observations to demonstrate their potential utility and motivate further data analysis, and offers a vision of future hurricane observations using combined uncrewed platforms.