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The COP9 signalosome (CSN) is a central component of the activation and remodelling cycle of cullin-RING E3 ubiquitin ligases (CRLs), the largest enzyme family of the ubiquitin–proteasome system in humans. CRLs are implicated in the regulation of numerous cellular processes, including cell cycle progression and apoptosis, and aberrant CRL activity is frequently associated with cancer. Remodelling of CRLs is initiated by CSN-catalysed cleavage of the ubiquitin-like activator NEDD8 from CRLs. Here we describe CSN5i-3, a potent, selective and orally available inhibitor of CSN5, the proteolytic subunit of CSN. The compound traps CRLs in the neddylated state, which leads to inactivation of a subset of CRLs by inducing degradation of their substrate recognition module. CSN5i-3 differentially affects the viability of tumour cell lines and suppresses growth of a human xenograft in mice. Our results provide insights into how CSN regulates CRLs and suggest that CSN5 inhibition has potential for anti-tumour therapy. Dysregulation of protein degradation by the ubiquitin-proteasome system is a feature commonly associated with cancer. Here, the authors develop an orally available small molecule that inhibits CSN5, the proteolytic subunit of the COP9 signalosome, and blocks tumour growth in a xenograft model.

In maritime mountainous regions, the phase of winter precipitation is elevation dependent, and in watersheds receiving both rain and snow, hydrologic impacts of climate change are less straightforward than in snowmelt‐dominated systems. Here, 29 Pacific Northwest watersheds illustrate how distribution of seasonal snow, transient snow, and winter rain mediates sensitivity to 20th century warming. Watersheds with >50% of their area in the seasonal snow zone had significant (α ≤ 0.1) trends towards greater winter and lower summer discharge, while lower elevations had no consistent trends. In seasonal snow‐dominated watersheds, runoff occurs 22–27 days earlier and minimum flows are 5–9% lower than in 1962, based on Sen's slope over the period. Trends in peak streamflow depend on whether watershed area susceptible to rain‐on‐snow events is increasing or decreasing. Delineation of elevation‐dependent snow zones identifies climate sensitivity of maritime mountainous watersheds and enables planning for water and ecosystem impacts of climate change. Key Points Hydrologic response to warming depends on area in the seasonal snow zone Shifts in transient snow zone and rain‐on‐snow drive trends in peak streamflows SNOTEL and PRISM methods equivalently identify climate sensitive watersheds

The forensic application of stable oxygen isotope data from human tissues depends on naturally occurring isotopic variation in drinking water across geographic areas. One factor which complicates interpretation of forensic data is local variability: if a wide range of drinking water values is in a small geographic region it may be difficult to identify or rule out that region as a location of origin. We examine data from community collection programs documenting tap water isotope variation within 30 cities areas throughout the United States. Isotopic variation within individual developed areas ranged widely, from essentially nil to greater than 9‰ (δ 18 O interdecile range). Many (14/30) of the study areas exhibited multi-modal isotope distributions, even in cases where the isotopic range was very small (e.g., <2.0‰), suggesting that the use of multiple, isotopically different sources was common. Most variation was attributed to differences in the source-region altitude or degree of evaporation for different water sources, and we observe limited variation in areas where contrasts in these variables are small. Variation tended to be largest in cities across the western USA. We explored correlations between the magnitude of local isotopic variation and climatic, environmental, and socioeconomic variables. We found that higher levels of variation occurred at sites where local water resources were likely to be more isotopically heterogeneous and in lower supply, consistent with the development of supply systems in these areas that access diverse and isotopically heterogeneous water resources. We also found that variation was positively correlated with larger developed areas, suggesting that pressures related to city growth may affect the degree to which infrastructure tapping diverse water resources is developed. Collectively, our results suggest that the influence of local tap water isotope heterogeneity on the precision of forensic geolocation is systematic and somewhat predictable, information to be factored into future applications.

Given the sensitivity of the Arctic climate to short-lived climate forcers, long-term in situ surface measurements of aerosol parameters are useful in gaining insight into the magnitude and variability of these climate forcings. Seasonality of aerosol optical properties – including the aerosol light-scattering coefficient, absorption coefficient, single-scattering albedo, scattering Ångström exponent, and asymmetry parameter – are presented for six monitoring sites throughout the Arctic: Alert, Canada; Barrow, USA; Pallas, Finland; Summit, Greenland; Tiksi, Russia; and Zeppelin Mountain, Ny-Ålesund, Svalbard, Norway. Results show annual variability in all parameters, though the seasonality of each aerosol optical property varies from site to site. There is a large diversity in magnitude and variability of scattering coefficient at all sites, reflecting differences in aerosol source, transport, and removal at different locations throughout the Arctic. Of the Arctic sites, the highest annual mean scattering coefficient is measured at Tiksi (12.47Mm−1), and the lowest annual mean scattering coefficient is measured at Summit (1.74Mm−1). At most sites, aerosol absorption peaks in the winter and spring, and has a minimum throughout the Arctic in the summer, indicative of the Arctic haze phenomenon; however, nuanced variations in seasonalities suggest that this phenomenon is not identically observed in all regions of the Arctic. The highest annual mean absorption coefficient is measured at Pallas (0.48Mm−1), and Summit has the lowest annual mean absorption coefficient (0.12Mm−1). At the Arctic monitoring stations analyzed here, mean annual single-scattering albedo ranges from 0.909 (at Pallas) to 0.960 (at Barrow), the mean annual scattering Ångström exponent ranges from 1.04 (at Barrow) to 1.80 (at Summit), and the mean asymmetry parameter ranges from 0.57 (at Alert) to 0.75 (at Summit). Systematic variability of aerosol optical properties in the Arctic supports the notion that the sites presented here measure a variety of aerosol populations, which also experience different removal mechanisms. A robust conclusion from the seasonal cycles presented is that the Arctic cannot be treated as one common and uniform environment but rather is a region with ample spatiotemporal variability in aerosols. This notion is important in considering the design or aerosol monitoring networks in the region and is important for informing climate models to better represent short-lived aerosol climate forcers in order to yield more accurate climate predictions for the Arctic.

Knowledge of aerosol size and composition is important for determining radiative forcing effects of aerosols, identifying aerosol sources and improving aerosol satellite retrieval algorithms. The ability to extrapolate aerosol size and composition, or type, from intensive aerosol optical properties can help expand the current knowledge of spatiotemporal variability in aerosol type globally, particularly where chemical composition measurements do not exist concurrently with optical property measurements. This study uses medians of the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE) and single scattering albedo (SSA) from 24 stations within the NOAA/ESRL Federated Aerosol Monitoring Network to infer aerosol type using previously published aerosol classification schemes. Three methods are implemented to obtain a best estimate of dominant aerosol type at each station using aerosol optical properties. The first method plots station medians into an AAE vs. SAE plot space, so that a unique combination of intensive properties corresponds with an aerosol type. The second typing method expands on the first by introducing a multivariate cluster analysis, which aims to group stations with similar optical characteristics and thus similar dominant aerosol type. The third and final classification method pairs 3-day backward air mass trajectories with median aerosol optical properties to explore the relationship between trajectory origin (proxy for likely aerosol type) and aerosol intensive parameters, while allowing for multiple dominant aerosol types at each station. The three aerosol classification methods have some common, and thus robust, results. In general, estimating dominant aerosol type using optical properties is best suited for site locations with a stable and homogenous aerosol population, particularly continental polluted (carbonaceous aerosol), marine polluted (carbonaceous aerosol mixed with sea salt) and continental dust/biomass sites (dust and carbonaceous aerosol); however, current classification schemes perform poorly when predicting dominant aerosol type at remote marine and Arctic sites and at stations with more complex locations and topography where variable aerosol populations are not well represented by median optical properties. Although the aerosol classification methods presented here provide new ways to reduce ambiguity in typing schemes, there is more work needed to find aerosol typing methods that are useful for a larger range of geographic locations and aerosol populations

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb ). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb ), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day.

To estimate global aerosol radiative forcing, measurements of aerosol optical properties are made by the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL)’s Global Monitoring Division (GMD) and their collaborators at 30 monitoring locations around the world. Many of the sites are located in regions influenced by specific aerosol types (Asian and Saharan desert dust, Asian pollution, biomass burning, etc.). This network of monitoring stations is a shared endeavor of NOAA and many collaborating organizations, including the World Meteorological Organization (WMO)’s Global Atmosphere Watch (GAW) program, the U.S. Department of Energy (DOE), several U.S. and foreign universities, and foreign science organizations. The result is a long-term cooperative program making atmospheric measurements that are directly comparable with those from all the other network stations and with shared data access. The protocols and software developed to support the program facilitate participation in GAW’s atmospheric observation strategy, and the sites in the NOAA/ESRL network make up a substantial subset of the GAW aerosol observations. This paper describes the history of the NOAA/ESRL Federated Aerosol Network, details about measurements and operations, and some recent findings from the network measurements.

Several types of filter-based instruments are used to estimate aerosol light absorption coefficients. Two significant results are presented based on Aethalometer measurements at six Arctic stations from 2012 to 2014. First, an alternative method of post-processing the Aethalometer data is presented, which reduces measurement noise and lowers the detection limit of the instrument more effectively than boxcar averaging. The biggest benefit of this approach can be achieved if instrument drift is minimised. Moreover, by using an attenuation threshold criterion for data post-processing, the relative uncertainty from the electronic noise of the instrument is kept constant. This approach results in a time series with a variable collection time (Δt) but with a constant relative uncertainty with regard to electronic noise in the instrument. An additional advantage of this method is that the detection limit of the instrument will be lowered at small aerosol concentrations at the expense of temporal resolution, whereas there is little to no loss in temporal resolution at high aerosol concentrations ( >  2.1–6.7 Mm−1 as measured by the Aethalometers). At high aerosol concentrations, minimising the detection limit of the instrument is less critical. Additionally, utilising co-located filter-based absorption photometers, a correction factor is presented for the Arctic that can be used in Aethalometer corrections available in literature. The correction factor of 3.45 was calculated for low-elevation Arctic stations. This correction factor harmonises Aethalometer attenuation coefficients with light absorption coefficients as measured by the co-located light absorption photometers. Using one correction factor for Arctic Aethalometers has the advantage that measurements between stations become more inter-comparable.

The uptake of water by atmospheric aerosols has a pronounced effect on particle light scattering properties, which in turn are strongly dependent on the ambient relative humidity (RH). Earth system models need to account for the aerosol water uptake and its influence on light scattering in order to properly capture the overall radiative effects of aerosols. Here we present a comprehensive model–measurement evaluation of the particle light scattering enhancement factor f(RH), defined as the particle light scattering coefficient at elevated RH (here set to 85 %) divided by its dry value. The comparison uses simulations from 10 Earth system models and a global dataset of surface-based in situ measurements. In general, we find a large diversity in the magnitude of predicted f(RH) amongst the different models, which can not be explained by the site types. Based on our evaluation of sea salt scattering enhancement and simulated organic mass fraction, there is a strong indication that differences in the model parameterizations of hygroscopicity and model chemistry are driving at least some of the observed diversity in simulated f(RH). Additionally, a key point is that defining dry conditions is difficult from an observational point of view and, depending on the aerosol, may influence the measured f(RH). The definition of dry also impacts our model evaluation, because several models exhibit significant water uptake between RH = 0 % and 40 %. The multisite average ratio between model outputs and measurements is 1.64 when RH = 0 % is assumed as the model dry RH and 1.16 when RH = 40 % is the model dry RH value. The overestimation by the models is believed to originate from the hygroscopicity parameterizations at the lower RH range which may not implement all phenomena taking place (i.e., not fully dried particles and hysteresis effects). This will be particularly relevant when a location is dominated by a deliquescent aerosol such as sea salt. Our results emphasize the need to consider the measurement conditions in such comparisons and recognize that measurements referred to as dry may not be dry in model terms. Recommendations for future model–measurement evaluation and model improvements are provided.