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Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH‐MS is a specific variant of data‐independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH‐MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH‐MS data, a strategy based on peptide‐centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH‐MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH‐MS data using peptide‐centric scoring. Furthermore, concepts on how to improve SWATH‐MS data acquisition, potential trade‐offs of parameter settings and alternative data analysis strategies are discussed. Graphical Abstract SWATH‐MS combines deep proteome coverage with quantitative consistency and accuracy and is often the method of choice for personalized medicine, drug screens or systems biology. This tutorial provides guidelines on how to set up SWATH‐MS experiments, perform the mass spectrometric measurements and analyse the data.

Plants are expected to generate more global-scale runoff under increasing atmospheric carbon dioxide concentrations through their influence on surface resistance to evapotranspiration. Recent studies using Earth System Models from phase 5 of the Coupled Model Intercomparison Project ostensibly reaffirm this result, further suggesting that plants will ameliorate the dire reductions in water availability projected by other studies that use aridity metrics. Here we complicate this narrative by analysing the change in precipitation partitioning to plants, runoff and storage in multiple Earth system models under both high carbon dioxide concentrations and warming. We show that projected plant responses directly reduce future runoff across vast swaths of North America, Europe and Asia because bulk canopy water demands increase with additional vegetation growth and longer and warmer growing seasons. These runoff declines occur despite increased surface resistance to evapotranspiration and vegetation total water use efficiency, even in regions with increasing or unchanging precipitation. We demonstrate that constraining the large uncertainty in the multimodel ensemble with regional-scale observations of evapotranspiration partitioning strengthens these results. We conclude that terrestrial vegetation plays a large and unresolved role in shaping future regional freshwater availability, one that will not ubiquitously ameliorate future warming-driven surface drying.

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis‐ SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood‐based biomarker studies. Synopsis The degree and origins of the abundance variability of 342 human plasma proteins are analyzed by a longitudinal twin design and SWATH mass spectrometry. The results suggest genetic control and longitudinal variation affect protein levels and biological processes to different degrees. We used the highly accurate and reproducible SWATH mass spectrometry technique to quantify 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years. The observed total quantitative variability of human plasma proteome is dissected to its root causes, genes, environment and longitudinal factors. The roles of the heritable, environmental and longitudinal determinants in controlling plasma protein levels are different for different proteins and functional clusters, strongly suggesting that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. We further identified 13 cis ‐SNPs significantly influencing the level of specific plasma proteins as protein quantitative trait loci (pQTLs), and five of them are associated with gene expression QTLs (eQTLs) in human tissues. Graphical Abstract The degree and origins of the abundance variability of 342 human plasma proteins are analyzed by a longitudinal twin design and SWATH mass spectrometry. The results suggest genetic control and longitudinal variation affect protein levels and biological processes to different degrees.

Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction, and the computational framework CCprofiler to detect and quantify protein complexes by error‐controlled, complex‐centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2,127 protein subunits. The technique identifies novel sub‐complexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible and provide a web platform, SECexplorer , for custom exploration of the HEK293 proteome modularity. Synopsis The study presents an integrated framework for targeted, complex‐centric analysis based on size exclusion chromatography (SEC) and SWATH/DIA mass spectrometry. The workflow facilitates the parallel detection of hundreds of protein complexes and their variants at high selectivity and under error‐control. The presented workflow is based on the concept of complex‐centric proteome profiling and combines size exclusion chromatography (SEC) with SWATH/DIA mass spectrometry. The implementation of the complex‐centric data analysis is supported by the computational framework CCprofiler . Application of the SEC‐SWATH‐MS workflow to HEK293 cells led the detection and quantification of subunit distribution of 462 distinct protein complexes containing 2,127 proteins and identified novel complex variants such as assembly intermediates. The interactive platform, SECexplorer is presented to support custom complex‐centric exploration of SEC‐SWATH‐MS datasets. Graphical Abstract The study presents an integrated framework for targeted, complex‐centric analysis based on size exclusion chromatography (SEC) and SWATH/DIA mass spectrometry. The workflow facilitates the parallel detection of hundreds of protein complexes and their variants at high selectivity and under error‐control.

This study provides an overview of the drought situation in Northeast Brazil for the past, present, and future. Droughts affect more people than any other natural hazard owing to their large scale and long-lasting nature. They are recurrent in the region and while some measures have been taken by the governments to mitigate their impacts, there is still a perception that residents, mainly in rural areas, are not yet adapted to these hazards. The drought affecting the Northeast from 2012 to 2015, however, has had an intensity and impact not seen in several decades and has already destroyed large swaths of cropland, affecting hundreds of cities and towns across the region, and leaving ranchers struggling to feed and water cattle. Future climate projections for the area show large temperature increases and rainfall reductions, which, together with a tendency for longer periods with consecutive dry days, suggest the occurrence of more frequent/intense dry spells and droughts and a tendency toward aridification in the region. All these conditions lead to an increase in evaporation from reservoirs and lakes, affecting irrigation and agriculture as well as key water uses including hydropower and industry, and thus, the welfare of the residents. Integrating drought monitoring and seasonal forecasting provides efficient means of assessing impacts of climate variability and change, identifying vulnerabilities, and allowing for better adaptation measures not only for medium- and long-term climate change but also for extremes of the interannual climate variability, particularly droughts.

Derechos are extensive swaths of damaging winds produced by some long-lived, widespread mesoscale convective systems. Little research has been conducted concerning how derecho mechanisms might change in a future, warmer climate. In this study, the pseudo–global warming method is utilized to evaluate how the 10 August 2020 midwestern U.S. derecho, the costliest thunderstorm event in U.S. history to date, might differ if it instead occurred in a warmer climate at the end of this century. The 10 August derecho event is first simulated in its observed environment, and then resimulated in environments altered according to projections from different climate models using a high-emissions climate change scenario. Results suggest that near the end of this century, a similar derecho event may not necessarily have more intense winds but could possibly impact a geographical area 50% to 100% larger. The physical chain of events leading to this greater geographical impact result from the derecho winds beginning earlier in the storm lifetime, due to increased precipitation combined with decreased relative humidity right above the ground, and derecho winds extending northward due to a strengthening of the parent storm from increased instability there. All these factors enhance the area of evaporative cooling and thus the cold pool, which in turn extends the area covered by the rear-inflow jet within the storm, the likely main mechanism for most of the damaging winds at the ground in the historical event. More study of other cases is required to evaluate the generality of this result.

Failed rifts are widely assumed to enter post‐rift tectonic quiescence after termination of intracontinental rifting, but a comprehensive understanding of their regional morphotectonics is lacking. Our quantitative, rift‐scale geomorphic analyses in the Suez Rift, an archetypal failed rift in Egypt, reveals widespread rifting after presumed rift “failure.” Stacked topographic swaths document normal fault offsets in Plio‐Quaternary rocks and fluvial metrics show steep gradients consistent with active faulting along the entire rift length. Quaternary shorelines uplifted along both margins constrain footwall uplift rates of up to 0.13 ± 0.04 mm/yr on normal faults with down‐dip heights of 10–15 km that were active by 3.12 ± 0.23 and 4.44 ± 0.2 Ma or earlier times. Pleistocene‐Recent extension rates of 0.26–0.55 mm/yr are lower than rates characterising preceding rift phases, albeit compatible with those of modestly active intracontinental rifts (e.g., Basin and Range). Our evidence of active extension after rift “abandonment” supports continued but decelerated rifting, not failure, in the Suez Rift.

Soon after the launch of Aeolus on 22 August 2018, the first ever wind lidar in space developed by the European Space Agency (ESA) has been providing profiles of the component of the wind vector along the instrument's line of sight (LOS) on a global scale. In order to validate the quality of Aeolus wind observations, the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) recently performed two airborne campaigns over central Europe deploying two different Doppler wind lidars (DWLs) on board the DLR Falcon aircraft. The first campaign – WindVal III – was conducted from 5 November 2018 until 5 December 2018 and thus still within the commissioning phase of the Aeolus mission. The second campaign – AVATARE (Aeolus Validation Through Airborne Lidars in Europe) – was performed from 6 May 2019 until 6 June 2019. Both campaigns were flown out of the DLR site in Oberpfaffenhofen, Germany, during the evening hours for probing the ascending orbits. All together, 10 satellite underflights with 19 flight legs covering more than 7500 km of Aeolus swaths were performed and used to validate the early-stage wind data product of Aeolus by means of collocated airborne wind lidar observations for the first time. For both campaign data sets, the statistical comparison of Aeolus horizontal line-of-sight (HLOS) observations and the corresponding wind observations of the reference lidar (2 µm DWL) on board the Falcon aircraft shows enhanced systematic and random errors compared with the bias and precision requirements defined for Aeolus. In particular, the systematic errors are determined to be 2.1 m s−1 (Rayleigh) and 2.3 m s−1 (Mie) for WindVal III and −4.6 m s−1 (Rayleigh) and −0.2 m s−1 (Mie) for AVATARE. The corresponding random errors are determined to be 3.9 m s−1 (Rayleigh) and 2.0 m s−1 (Mie) for WindVal III and 4.3 m s−1 (Rayleigh) and 2.0 m s−1 (Mie) for AVATARE. The Aeolus observations used here were acquired in an altitude range up to 10 km and have mainly a vertical resolution of 1 km (Rayleigh) and 0.5 to 1.0 km (Mie) and a horizontal resolution of 90 km (Rayleigh) and down to 10 km (Mie). Potential reasons for those errors are analyzed and discussed.

An object-based verification methodology for the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e) has been developed and applied to 32 cases between December 2015 and June 2017. NEWS-e forecast objects of composite reflectivity and 30-min updraft helicity swaths are matched to corresponding reflectivity and rotation track objects in Multi-Radar Multi-Sensor system data on space and time scales typical of a National Weather Service warning. Object matching allows contingency-table-based verification statistics to be used to establish baseline performance metrics for NEWS-e thunderstorm and mesocyclone forecasts. NEWS-e critical success index (CSI) scores of reflectivity (updraft helicity) forecasts decrease from approximately 0.7 (0.4) to 0.4 (0.2) over 3 h of forecast time. CSI scores decrease through the forecast period, indicating that errors do not saturate during the 3-h forecast. Lower verification scores for rotation track forecasts are primarily a result of a high-frequency bias. Comparison of different system configurations used in 2016 and 2017 shows an increase in skill for 2017 reflectivity forecasts, attributable mainly to improvements in the forecast initial conditions. A small decrease in skill in 2017 rotation track forecasts is likely a result of sample differences between 2016 and 2017. Although large case-to-case variation is present, evidence is found that NEWS-e forecast skill improves with increasing object size and intensity.

A new instrument has been proposed for measuring surface air pressure over the marine surface with a combined active/passive scanning multi-channel differential absorption radar (DAR) to provide an estimate of the total atmospheric column oxygen content. A demonstrator instrument, the Microwave Barometric Radar and Sounder (MBARS), has been funded by the National Aeronautics and Space Administration (NASA) for airborne test missions. Here, a proof-of-concept study to evaluate the potential impact of spaceborne surface pressure data on numerical weather prediction is performed using the Goddard Modeling and Assimilation Office global observing system simulation experiment (OSSE) framework. This OSSE framework employs the Goddard Earth Observing System model and the hybrid 4D ensemble variational Gridpoint Statistical Interpolation data assimilation system. Multiple flight and scanning configurations of potential spaceborne orbits are examined. Swath width and observation spacing for the surface pressure data are varied to explore a range of sampling strategies. For wider swaths, the addition of surface pressures reduces the root mean square surface pressure analysis error by as much as 20% over some ocean regions. The forecast sensitivity observation impact tool estimates impacts on the Pacific Ocean basin boundary layer 24-hour forecast temperatures for spaceborne surface pressures on par with rawinsondes and aircraft, and greater impacts than the current network of ships and buoys. The largest forecast impacts are found in the southern hemisphere extratropics.