Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

Drizzle is frequently observed in marine stratocumulus clouds and plays a crucial role in cloud lifetime and the radiation budget. Most drizzling stratocumulus clouds form drizzle virga below cloud base, where subcloud scavenging and evaporative cooling are important. We use unique ground‐based cloud radar observations (1) to examine the statistical properties of drizzle frequency and virga depth and (2) to test a simple analytical relationship derived between drizzle virga thickness (Hv) and cloud thickness (Hc). Observations show that 83% of marine stratocumulus clouds are drizzling although only 31% generate surface precipitation. The analytical expression for Hv is derived as a function of Hc and subcloud relative humidity considering in‐cloud accretion and subcloud evaporation of drizzle drops. The derived third‐order power law relationship,, shows good agreement with long‐term observational data. Our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in models

Managing water through change and uncertainty: comparing lessons from the adaptive co-management literature to recent policy developments in England

Water management is set to become increasingly variable and unpredictable, in particular because of climate change. This paper investigates the extent to which water policy in England provides an enabling environment for ‘adaptive co-management’, which its proponents claim can achieve the dual objective of ecosystem protection and livelihood sustainability under conditions of change and uncertainty. Five policy categories are derived from a literature review, and are used to conduct a directed content analysis of seven key water policy documents. The findings reveal that although, in part, English water policy serves as an enabling environment for adaptive co-management, there is a level of discrepancy between substantive aspects of the five policy categories and water policy in England. Addressing these discrepancies will be important if English water policy is to allow for the emergence of processes, like adaptive co-management, that are capable of coping with the challenges that lie ahead

On Secure Workflow Decentralisation on the Internet

Decentralised workflow management systems are a new research area, where most work to-date has focused on the system's overall architecture. As little attention has been given to the security aspects in such systems, we follow a security driven approach, and consider, from the perspective of available security building blocks, how security can be implemented and what new opportunities are presented when empowering the decentralised environment with modern distributed security protocols. Our research is motivated by a more general question of how to combine the positive enablers that email exchange enjoys, with the general benefits of workflow systems, and more specifically with the benefits that can be introduced in a decentralised environment. This aims to equip email users with a set of tools to manage the semantics of a message exchange, contents, participants and their roles in the exchange in an environment that provides inherent assurances of security and privacy. This work is based on a survey of contemporary distributed security protocols, and considers how these protocols could be used in implementing a distributed workflow management system with decentralised control . We review a set of these protocols, focusing on the required message sequences in reviewing the protocols, and discuss how these security protocols provide the foundations for implementing core control-flow, data, and resource patterns in a distributed workflow environment

Lung Toxicity of Ambient Particulate Matter from Southeastern U.S. Sites with Different Contributing Sources: Relationships between Composition and Effects

BACKGROUND: Exposure to air pollution and, more specifically, particulate matter (PM) is associated with adverse health effects. However, the specific PM characteristics responsible for biological effects have not been defined. OBJECTIVES: In this project we examined the composition, sources, and relative toxicity of samples of PM with aerodynamic diameter ≥2.5 μm (PM(2.5)) collected from sites within the Southeastern Aerosol Research and Characterization (SEARCH) air monitoring network during two seasons. These sites represent four areas with differing sources of PM(2.5), including local urban versus regional sources, urban areas with different contributions of transportation and industrial sources, and a site influenced by Gulf of Mexico weather patterns. METHODS: We collected samples from each site during the winter and summer of 2004 for toxicity testing and for chemical analysis and chemical mass balance–based source apportionment. We also collected PM(2.5) downwind of a series of prescribed forest burns. We assessed the toxicity of the samples by instillation into rat lungs and assessed general toxicity, acute cytotoxicity, and inflammation. Statistical dose–response modeling techniques were used to rank the relative toxicity and compare the seasonal differences at each site. Projection-to-latent-surfaces (PLS) techniques examined the relationships among sources, chemical composition, and toxicologic end points. RESULTS AND CONCLUSIONS: Urban sites with high contributions from vehicles and industry were most toxic

Advances in the Projective Dynamics Method: A Procedure of Discretizing the Space applied to Markovian Processes

AbstractThe projection of a continuous space process to a discrete space process via the transition rates between neighboring bins allows us to relate a master equation to a solution of a stochastic differential equation. The presented method is formulated in its general form for the first time and tested with the Brownian Diffusion process of noninteracting particles with white noise in simple one-dimensional potentials. The comparison of the first passage time obtained with Projective Dynamics, Brownian motion simulations and analytical solutions show the accuracy of this method as well as a wide independence of the particular choice of the binning process

Deep Extragalactic VIsible Legacy Survey (DEVILS): SED fitting in the D10-COSMOS field and the evolution of the stellar mass function and SFR–M⋆ relation

We present catalogues of stellar masses, star formation rates (SFRs), and ancillary stellar population parameters for galaxies spanning 0 \u3c z \u3c 9 from the Deep Extragalactic VIsible Legacy Survey (DEVILS). DEVILS is a deep spectroscopic redshift survey with very high completeness, covering several premier deep fields including COSMOS (D10). Our stellar mass and SFR estimates are self-consistently derived using the spectral energy distribution (SED) modelling code PROSPECT, using well-motivated parametrizations for dust attenuation, star formation histories, and metallicity evolution. We show how these improvements, and especially our physically motivated assumptions about metallicity evolution, have an appreciable systematic effect on the inferred stellar masses, at the level of ∼0.2 dex. To illustrate the scientific value of these data, we map the evolving galaxy stellar mass function (SMF) and the SFR–M⋆ relation for 0 \u3c z \u3c 4.25. In agreement with past studies, we find that most of the evolution in the SMF is driven by the characteristic density parameter, with little evolution in the characteristic mass and low-mass slopes. Where the SFR–M⋆ relation is indistinguishable from a power law at z \u3e 2.6, we see evidence of a bend in the relation at low redshifts (z \u3c 0.45). This suggests evolution in both the normalization and shape of the SFR–M⋆ relation since cosmic noon. It is significant that we only clearly see this bend when combining our new DEVILS measurements with consistently derived values for lower redshift galaxies from the Galaxy And Mass Assembly (GAMA) survey: this shows the power of having consistent treatment for galaxies at all redshifts

Deep Extragalactic VIsible Legacy Survey (DEVILS): SED Fitting in the D10-COSMOS Field and the Evolution of the Stellar Mass Function and SFR-M⋆M_\star relation

We present catalogues of stellar masses, star formation rates, and ancillary stellar population parameters for galaxies spanning $0<z<9$ from the Deep Extragalactic VIsible Legacy Survey (DEVILS). DEVILS is a deep spectroscopic redshift survey with very high completeness, covering several premier deep fields including COSMOS (D10). Our stellar mass and star formation rate estimates are self-consistently derived using the spectral energy distribution (SED) modeling code ProSpect, using well-motivated parameterisations for dust attenuation, star formation histories, and metallicity evolution. We show how these improvements, and especially our physically motivated assumptions about metallicity evolution, have an appreciable systematic effect on the inferred stellar masses, at the level of $\sim$0.2 dex. To illustrate the scientific value of these data, we map the evolving galaxy stellar mass function (SMF) for $0<z<5$ and the SFR-$M_\star$ relation for $0<z<9$. In agreement with past studies, we find that most of the evolution in the SMF is driven by the characteristic density parameter, with little evolution in the characteristic mass and low-mass slopes. Where the SFR-$M_\star$ relation is indistinguishable from a power-law at $z>2.6$, we see evidence of a bend in the relation at low redshifts ($z<0.45$). This suggests evolution in both the normalisation and shape of the SFR-$M_\star$ relation since cosmic noon. It is significant that we only clearly see this bend when combining our new DEVILS measurements with consistently derived values for lower redshift galaxies from the Galaxy And Mass Assembly (GAMA) survey: this shows the power of having consistent treatment for galaxies at all redshifts.Comment: Submitted for publication in MNRA

The metabolic regimes of 356 rivers in the United States

A national-scale quantification of metabolic energy flow in streams and rivers can improve understanding of the temporal dynamics of in-stream activity, links between energy cycling and ecosystem services, and the effects of human activities on aquatic metabolism. The two dominant terms in aquatic metabolism, gross primary production (GPP) and aerobic respiration (ER), have recently become practical to estimate for many sites due to improved modeling approaches and the availability of requisite model inputs in public datasets. We assembled inputs from the U.S. Geological Survey and National Aeronautics and Space Administration for October 2007 to January 2017. We then ran models to estimate daily GPP, ER, and the gas exchange rate coefficient for 356 streams and rivers across the continental United States. We also gathered potential explanatory variables and spatial information for cross-referencing this dataset with other datasets of watershed characteristics. This dataset offers a first national assessment of many-day time series of metabolic rates for up to 9 years per site, with a total of 490,907 site-days of estimates.We thank Jill Baron and the USGS Powell Center for financial support for this collaborative effort (Powell Center Working Group title: "Continental-scale overview of stream primary productivity, its links to water quality, and consequences for aquatic carbon biogeochemistry"). Additional financial support came from the USGS NAWQA program and Office of Water Information. NSF grants DEB-1146283 and EF1442501 partially supported ROH. A post-doctoral grant from the Basque Government partially supported MA. NAG was supported by the U.S. Department of Energy's Office of Science, Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. Leah Colasuonno provided expert logistical support of our working group meetings. The developers of USGS ScienceBase were very helpful both in hosting this dataset and in responding to our requests. Randy Hunt and Mike Fienen of the USGS Wisconsin Modeling Center graciously provided access to their HTCondor cluster. Mike Vlah provided detailed and insightful reviews of the data and metadata