The CMIP6 Data Request (DREQ, version 01.00.31)

The data request of the Coupled Model Intercomparison Project Phase 6 (CMIP6) defines all the quantities from CMIP6 simulations that should be archived. This includes both quantities of general interest needed from most of the CMIP6-endorsed model intercomparison projects (MIPs) and quantities that are more specialized and only of interest to a single endorsed MIP. The complexity of the data request has increased from the early days of model intercomparisons, as has the data volume. In contrast with CMIP5, CMIP6 requires distinct sets of highly tailored variables to be saved from each of the more than 200 experiments. This places new demands on the data request information base and leads to a new requirement for development of software that facilitates automated interrogation of the request and retrieval of its technical specifications. The building blocks and structure of the CMIP6 Data Request (DREQ), which have been constructed to meet these challenges, are described in this paper

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Eosinophils in glioblastoma biology

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. The development of this malignant glial lesion involves a multi-faceted process that results in a loss of genetic or epigenetic gene control, un-regulated cell growth, and immune tolerance. Of interest, atopic diseases are characterized by a lack of immune tolerance and are inversely associated with glioma risk. One cell type that is an established effector cell in the pathobiology of atopic disease is the eosinophil. In response to various stimuli, the eosinophil is able to produce cytotoxic granules, neuromediators, and pro-inflammatory cytokines as well as pro-fibrotic and angiogenic factors involved in pathogen clearance and tissue remodeling and repair. These various biological properties reveal that the eosinophil is a key immunoregulatory cell capable of influencing the activity of both innate and adaptive immune responses. Of central importance to this report is the observation that eosinophil migration to the brain occurs in response to traumatic brain injury and following certain immunotherapeutic treatments for GBM. Although eosinophils have been identified in various central nervous system pathologies, and are known to operate in wound/repair and tumorstatic models, the potential roles of eosinophils in GBM development and the tumor immunological response are only beginning to be recognized and are therefore the subject of the present review

durolib 1.0.0

First release available through anaconda/durack

Long-term sea-level change revisited: the role of salinity

Of the many processes contributing to long-term sea-level change, little attention has been paid to the large-scale contributions of salinity-driven halosteric changes. We evaluate observed and simulated estimates of long-term (1950-present) halosteric patterns and compare these to corresponding thermosteric changes. Spatially coherent halosteric patterns are visible in the historical record, and are consistent with estimates of long-term water cycle amplification. Our results suggest that long-term basin-scale halosteric changes in the Pacific and Atlantic are substantially larger than previously assumed, with observed estimates and coupled climate models suggesting magnitudes of ∼25% of the corresponding thermosteric changes. In both observations and simulations, Pacific basin-scale freshening leads to a density reduction that augments coincident thermosteric expansion, whereas in the Atlantic halosteric changes partially compensate strong thermosteric expansion via a basin-scale enhanced salinity density increase. Although regional differences are apparent, at basin-scales consistency is found between the observed and simulated partitioning of halosteric and thermosteric changes, and suggests that models are simulating the processes driving observed long-term basin-scale steric changes. Further analysis demonstrates that the observed halosteric changes and their basin partitioning are consistent with CMIP5 simulations that include anthropogenic CO _2 forcings ( Historical ), but are found to be inconsistent with simulations that exclude anthropogenic forcings ( HistoricalNat )

pcmdi_metrics: Version 1.1.1

Self contained packages to run PCMDI Metric