The utility of convection-permitting ensembles for the prediction of stationary convective bands

This study examines convection-permitting numerical simulations of four cases of terrain-locked quasi-stationary convective bands over the UK. For each case, a 2.2-km grid-length 12-member ensemble and 1.5-km grid-length deterministic forecast are analyzed, each with two different initialization times. Object-based verification is applied to determine whether the simulations capture the structure, location, timing, intensity and duration of the observed precipitation. These verification diagnostics reveal that the forecast skill varies greatly between the four cases. Although the deterministic and ensemble simulations captured some aspects of the precipitation correctly in each case, they never simultaneously captured all of them satisfactorily. In general, the models predicted banded precipitation accumulations at approximately the correct time and location, but the precipitating structures were more cellular and less persistent than the coherent quasi-stationary bands that were observed. Ensemble simulations from the two different initialization times were not significantly different, which suggests a potential benefit of time-lagging subsequent ensembles to increase ensemble size. The predictive skill of the upstream larger-scale flow conditions and the simulated precipitation on the convection-permitting grids were strongly correlated, which suggests that more accurate forecasts from the parent ensemble should improve the performance of the convection-permitting ensemble nested within it

Climatology of size, shape and intensity of precipitation features over Great Britain and Ireland

A climatology of precipitation features (or objects) from the Great Britain and Ireland radar-derived precipitation mosaic from 2006–2015 is constructed, with features defined as contiguous areas of nonzero precipitation rates. Over the ten years, there are 54,811,747 non-unique precipitating features over 100 km2 in area, with a median precipitation-feature area of 249 km2, median major axis length of 29.2 km, median aspect ratio of 2.0, median feature mean precipitation rate of 0.49 mm h-1, and median feature maximum precipitation rate of 2.4 mm h-1. Small-scale precipitating systems are most common, but larger systems exceeding 10,000 km2 contribute close to 70% of the annual precipitation across the study region. Precipitation feature characteristics are sensitive to changes in annual and diurnal environment, with feature intensities peaking during the afternoon in summer and the largest precipitation features occurring during winter. Precipitation intensities less than 5 mm h-1 comprise 97.3% of all precipitation occurrence and contribute 83.6% of the total precipitation over land. Banded-precipitation features (defined as precipitation features with aspect ratio at least 3:1 and major axis length at least 100 km) comprise 3% of all precipitation features by occurrence, but contribute 23.7% of the total precipitation. Mesoscale banded features (defined as banded-precipitation features with major axis length at least 100 km and total area not exceeding 10,000 km2) and mesoscale convective banded features (defined as banded-precipitation features with at least 100 km2 of precipitation rates exceeding 10 mm h-1) are most prevalent in southwestern England with mesoscale convective banded features contributing up to 2% of precipitation

Climatology of banded precipitation over the contiguous United States

A climatology of banded-precipitation features over the contiguous United States from 2003–2014 is constructed. A band is defined as a precipitation feature with a major axis of 100 km or greater and a ratio of major axis length to minor axis length (hereafter, aspect ratio) of 3:1 or greater. By applying an automated feature-based detection algorithm to composite radar imagery, a database of 48,916,844 precipitation features is created, of which 7,213,505 (14.8%) are bands. This algorithm produces the first climatology of precipitation bands over the contiguous United States. Banded precipitation occurrence is broadly similar to total precipitation occurrence, with a maximum of 175 hours of banded precipitation annually over the Ohio River Valley. In the warm season, there is a strong diurnal signature associated with convective storm development for both precipitation feature area and total area covered by precipitation, but little diurnal signature in aspect ratio. A strong west-east gradient in both precipitation occurrence and banded precipitation occurrence exist, as areas west of the Rockies receive less frequent precipitation, which is much less likely to be banded. East of the Rockies, precipitation features are banded 30% of the time, versus 10–15% west of the Rockies. Areas downwind of the Great Lakes show prominent late autumn and winter maxima in banded precipitation associated with lake-effect snowbands. Local maxima of banded precipitation percentage occur in the Dakotas and east of the Colorado Rockies during winter. Although banded-precipitation features comprise only 14.8% of all precipitation features, they contribute 21.9% of the annual precipitation occurrence over the contiguous United States

A multilaboratory comparison of calibration accuracy and the performance of external references in analytical ultracentrifugation.

Analytical ultracentrifugation (AUC) is a first principles based method to determine absolute sedimentation coefficients and buoyant molar masses of macromolecules and their complexes, reporting on their size and shape in free solution. The purpose of this multi-laboratory study was to establish the precision and accuracy of basic data dimensions in AUC and validate previously proposed calibration techniques. Three kits of AUC cell assemblies containing radial and temperature calibration tools and a bovine serum albumin (BSA) reference sample were shared among 67 laboratories, generating 129 comprehensive data sets. These allowed for an assessment of many parameters of instrument performance, including accuracy of the reported scan time after the start of centrifugation, the accuracy of the temperature calibration, and the accuracy of the radial magnification. The range of sedimentation coefficients obtained for BSA monomer in different instruments and using different optical systems was from 3.655 S to 4.949 S, with a mean and standard deviation of (4.304 ± 0.188) S (4.4%). After the combined application of correction factors derived from the external calibration references for elapsed time, scan velocity, temperature, and radial magnification, the range of s-values was reduced 7-fold with a mean of 4.325 S and a 6-fold reduced standard deviation of ± 0.030 S (0.7%). In addition, the large data set provided an opportunity to determine the instrument-to-instrument variation of the absolute radial positions reported in the scan files, the precision of photometric or refractometric signal magnitudes, and the precision of the calculated apparent molar mass of BSA monomer and the fraction of BSA dimers. These results highlight the necessity and effectiveness of independent calibration of basic AUC data dimensions for reliable quantitative studies

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Build Your Own Earth:A Web-Based Tool for Exploring Climate-Model Output in Teaching and Research

Abstract Build Your Own Earth was designed as a web-based tool for the user to select various characteristics of a planet and see what the climate of that planet would be like. Because of the limitations of computer resources, presimulated Earths were run using the Fast Ocean Atmosphere Model at relatively coarse resolution. The tool provides 50 different Earth configurations in three categories: Recent, Ancient, and Alien Earths. Recent Earths fix the continental configuration at the present day and vary the axial tilt, eccentricity, and greenhouse gas concentrations. Ancient Earths include a series of paleoclimate simulations from the Last Glacial Maximum 21,000 years ago to the Ediacaran 600 million years ago. Alien Earths include an aquaplanet, terraplanet, ice planet, and various idealized continental configurations. Fifty different monthly averaged quantities are available to view in an annual cycle from four different map projections. Build Your Own Earth was built and designed for a massive open online course, but it has also been used in the classroom at the University of Manchester, as well as research projects on paleoclimate and planetary habitability, for example. The tool is freely available online (www.buildyourownearth.com) for anyone to access.</jats:p

<i>A</i>. <i>phagocytophilum</i> HZ proteins that are differentially abundant in the ΔOMT, according to iTRAQ results.

<p>*Average of peptides used for the quantification of the proteins.</p><p><i>**</i>Ratios <1.0 are less abundant in ΔOMT and ratios >1.0 are more abundant in ΔOMT.</p><p><i>A</i>. <i>phagocytophilum</i> HZ proteins that are differentially abundant in the ΔOMT, according to iTRAQ results.</p