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Recovering additional historical weather observations from known archival sources will improve the understanding of how the climate is changing and enable detailed examination of unusual events within the historical record. The UK National Meteorological Archive recently scanned more than 66,000 paper sheets containing 5.28 million hand‐written monthly rainfall observations taken across the UK and Ireland between 1677 and 1960. Only a small fraction of these observations were previously digitally available for climate scientists to analyse. More than 16,000 volunteer citizen scientists completed the transcription of these sheets of observations during early 2020 using the RainfallRescue.org website, built using the Zooniverse platform. A total of 3.34 million observations from more than 6000 locations have so far been quality controlled and made openly available. This has increased the total number of monthly rainfall observations that are available for this time period and region by a factor of six. The newly rescued observations will enable longer and much improved reconstructions of past variations in rainfall across the British and Irish Isles, including for periods of significant flooding and drought. Specifically, this data should allow the official gridded monthly rainfall reconstructions for the UK to be extended back to 1836, and even earlier for some regions. [ABSTRACT FROM AUTHOR]

Over recent years, several visualization tools that offer advanced threedimensional (3D) rendering techniques, while still showing good performance for large data sets, have been developed. However, how to provide an intuitive way to combine traditional two-dimensional (2D) methods essential in operational weather forecasting and new 3D techniques welcomed in atmospheric research is not fully investigated, if not overlooked, in these tools. The paper presents MeteoExplorer: a software tool designed to analyse and visualize atmospheric and geoscience data. It consists of a developer-orientedcrossplatform foundation framework and several applications built upon the framework. The framework is developed with C++ on the central processing unit side and shader languages on the graphics processing unit (GPU) side. Modules in the framework are loosely coupled with minimum interdependencies to facilitate code reuse and improve code efficiency. Compared with other software tools, the framework provides distinctive features, including a unified framework that integrates both 2D and 3D rendering context, comprehensive support of popular data formats and computing platforms, decent rendition quality via the export of vector graphics and page layout customization, and interactive composition of synoptic charts. Based on the foundation libraries, the software can develop web, desktop and mobile applications for meteorological purposes. These applications support the analysis and visualization of numerous data set types, as well as the interactive content creation. MeteoExplorer is an exploratory project that provides forecasters with new techniques for climate diagnosis and forecasts. [ABSTRACT FROM AUTHOR]

High‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over‐entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present‐day climate, limiting their scientific utility. We report new results showing that this over‐entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small‐scale momentum fluctuations associated with the formulation of the momentum solver of the embedded large eddy simulation. By considering the sedimentation process adjacent to default one‐moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that can produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub‐cloud eddy spectrum are observed. We report these sensitivities in multi‐week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5° exterior resolution. The result is a new HR having desired improvements in the baseline present‐day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation. Plain Language Summary: Stratocumulus clouds cover a large fraction of the globe but are very challenging to reproduce in computer simulations of Earth's atmosphere because of their unique complexity. Previous studies find the model produces too few Stratocumulus clouds as we increase the model resolution, which, in theory, should improve the simulation of important motions for the clouds. This is because the clouds are exposed to more conditions that make them evaporate away. On Earth, stratocumulus clouds reflect a lot of sunlight. In the computer model of Earth, too much sunlight reaches the surface because of too few stratocumulus clouds, which makes it warmer. This study tests two methods to thicken Stratocumulus clouds in the computer model Earth. The first method smooths out some winds, which helps reduce the exposure of clouds to the conditions that make them evaporate. The second method moves water droplets in the cloud away from the conditions that would otherwise make them evaporate. In long simulations, combining these methods helps the model produce thicker stratocumulus clouds with more water. Key Points: We improve a long‐standing stratocumulus (Sc) dim bias in a high‐resolution Multiscale Modeling FrameworkIncorporating intra‐CRM hyperviscosity hedges against the numerics of its momentum solver, reducing entrainment vicinityFurther adding sedimentation boosts Sc brightness close to observed, opening path to more faithful low cloud feedback analysis [ABSTRACT FROM AUTHOR]

We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources. Plain Language Summary: The atmospheric physics parameterizations of traditional climate models do not spend radically different amounts of computational power and time across different parts of the globe. However, there are some physical processes, such as low cloud formation, that require much higher resolution than we currently use to model climate change. Using the traditional framework, this becomes too expensive because of computational limitations. In this work, we develop a way to efficiently enhance the interior resolution of a multi‐scale climate model over only parts of the world. Specifically, we develop a way for a supercomputer to best split up the work of simulating the cloud physics over the parts of the world with coarser versus higher resolution so that it runs much faster. We also show that this task of using coarse resolution in some places and high resolution in others doesn't produce unwanted side effects. Key Points: We adapt Energy Exascale Earth Model (E3SM)/Community Earth System Model so most of a processor pool can operate on just a subset of demanding physics columnsLoad balancing theory finds optimal computational scale for regionalized high intensity physics workMulti‐Domain cloud resolving model tests with Large‐Eddy Simulation resolution embedded in 30% of the superparameterized E3SM succeed with few artifacts [ABSTRACT FROM AUTHOR]

The 2085 km2 Jordan River Basin, and its seven sub‐catchments draining the Central Wasatch Range immediately east of Salt Lake City, UT, are home to an array of hydrologic, atmospheric, climatic and chemical research infrastructure that collectively forms the Wasatch Environmental Observatory (WEO). WEO is geographically nested within a wildland to urban land‐use gradient and built upon a strong foundation of over a century of discharge and climate records. A 2200 m gradient in elevation results in variable precipitation, temperature and vegetation patterns. Soil and subsurface structure reflect systematic variation in geology from granitic, intrusive to mixed sedimentary clastic across headwater catchments, all draining to the alluvial or colluvial sediments of the former Lake Bonneville. Winter snowfall and spring snowmelt control annual hydroclimate, rapid population growth dominates geographic change in lower elevations and urban gas and particle emissions contribute to episodes of severe air pollution in this closed‐basin. Long‐term hydroclimate observations across this diverse landscape provide the foundation for an expanding network of infrastructure in both montane and urban landscapes. Current infrastructure supports both basic and applied research in atmospheric chemistry, biogeochemistry, climate, ecology, hydrology, meteorology, resource management and urban redesign that is augmented through strong partnerships with cooperating agencies. These features allow WEO to serve as a unique natural laboratory for addressing research questions facing seasonally snow‐covered, semi‐arid regions in a rapidly changing world and an excellent facility for providing student education and research training. [ABSTRACT FROM AUTHOR]

Weather observations taken every hour during the years 1883–1904 on the summit of Ben Nevis (1345 m above sea level) and in the town of Fort William in the Scottish Highlands have been transcribed from the original publications into digital form. More than 3,500 citizen scientist volunteers completed the digitization in less than 3 months using the WeatherRescue.org website. Over 1.5 million observations of atmospheric pressure, wet‐ and dry‐bulb temperatures, precipitation and wind speed were recovered. These data have been quality controlled and are now made openly available, including hourly values of relative humidity derived from the digitized dry‐ and wet‐bulb temperatures using modern hygrometric algorithms. These observations are one of the most detailed weather data collections available for anywhere in the UK in the Victorian era. In addition, 374 observations of aurora borealis seen by the meteorologists from the summit of Ben Nevis have been catalogued and this has improved the auroral record for studies of space weather. [ABSTRACT FROM AUTHOR]

Abstract: Three Earth System models are used to derive surface temperature responses to removal of U.S. anthropogenic SO2 emissions. Using multicentury perturbation runs with and without U.S. anthropogenic SO2 emissions, the local and remote surface temperature changes are estimated. In spite of a temperature drift in the control and large internal variability, 200 year simulations yield statistically significant regional surface temperature responses to the removal of U.S. SO2 emissions. Both local and remote surface temperature changes occur in all models, and the patterns of changes are similar between models for northern hemisphere land regions. We find a global average temperature sensitivity to U.S. SO2 emissions of 0.0055 K per Tg(SO2) per year with a range of (0.0036, 0.0078). We examine global and regional responses in SO4 burdens, aerosol optical depths (AODs), and effective radiative forcing (ERF). While changes in AOD and ERF are concentrated near the source region (United States), the temperature response is spread over the northern hemisphere with amplification of the temperature increase toward the Arctic. In all models, we find a significant response of dust concentrations, which affects the AOD but has no obvious effect on surface temperature. Temperature sensitivity to the ERF of U.S. SO2 emissions is found to differ from the models' sensitivity to radiative forcing of doubled CO2. [ABSTRACT FROM AUTHOR]

We present the construction of a continuous, daily (09:00 UTC), station-based (Azores-Iceland) North Atlantic Oscillation ( NAO) Index back to 1871 which is extended back to 1850 with additional daily mean data. The constructed index more than doubles the length of previously existing, widely available, daily NAO time series. The index is created using entirely observational sea-level pressure ( SLP) data from Iceland and 73.5% of observational SLP data from the Azores - the remainder being filled in via reanalysis (Twentieth Century Reanalysis Project and European Mean Sea Level Pressure) SLP data. Icelandic data are taken from the Southwest Iceland pressure series. We construct and document a new Ponta Delgada SLP time series based on recently digitized and newly available data that extend back to 1872. The Ponta Delgada time series is created by splicing together several fractured records (from Ponta Delgada, Lajes, and Santa Maria) and filling in the major gaps (pre-1872, 1888-1905, and 1940-1941) and occasional days (145) with reanalysis data. Further homogeneity corrections are applied to the Azores record, and the daily (09:00 UTC) NAO index is then calculated. The resulting index, with its extended temporal length and daily resolution, is the first reconstruction of daily NAO back into the 19th Century and therefore is useful for researchers across multiple disciplines. [ABSTRACT FROM AUTHOR]

ABSTRACT Using output from a high-resolution meteorological simulation, we evaluate the sensitivity of southern California wind energy generation to variations in key characteristics of current wind turbines. These characteristics include hub height, rotor diameter and rated power, and depend on turbine make and model. They shape the turbine's power curve and thus have large implications for the energy generation capacity of wind farms. For each characteristic, we find complex and substantial geographical variations in the sensitivity of energy generation. However, the sensitivity associated with each characteristic can be predicted by a single corresponding climate statistic, greatly simplifying understanding of the relationship between climate and turbine optimization for energy production. In the case of the sensitivity to rotor diameter, the change in energy output per unit change in rotor diameter at any location is directly proportional to the weighted average wind speed between the cut-in speed and the rated speed. The sensitivity to rated power variations is likewise captured by the percent of the wind speed distribution between the turbines rated and cut-out speeds. Finally, the sensitivity to hub height is proportional to lower atmospheric wind shear. Using a wind turbine component cost model, we also evaluate energy output increase per dollar investment in each turbine characteristic. We find that rotor diameter increases typically provide a much larger wind energy boost per dollar invested, although there are some zones where investment in the other two characteristics is competitive. Our study underscores the need for joint analysis of regional climate, turbine engineering and economic modeling to optimize wind energy production. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]