WCRP Task Team for the Intercomparison of ReAnalyses (TIRA): Motivation and Progress

Reanalyses have proven to be an important resource for weather and climate related research, as well as societal applications at large. New atmospheric reanalyses in various forms are produced every few years. In addition, land and ocean communities are producing disciplinary uncoupled reanalyses, and regional reanalyses are emerging in addition to global reanalyses. Systems of data information are being developed to facilitate the intercomparison of reanalyses among themselves and with observations and climate change experiments (e.g. CREATE-IP and WRIT). Current research and development in reanalysis is directed at (1) extending the length of reanalyzed period and (2) use of coupled Earth system models for climate reanalysis. While the World Climate Research Programme (WCRP) involvement in the reanalyses communities through its Data Advisory Council (WDAC) has been substantial, for example in organizing international conferences on reanalyses. However, these efforts have previously not included an analysis of the differences among reanalyses and their inherent uncertainties which are important questions for both users and developers of reanalyses. Therefore, the WCRP Task Team for the Intercomparison of ReAnalyses (TIRA) task team has been formed as collaborative effort to address reanalyses role in WCRP. This constitutes a logical progression that fills the needs of the community and contributes to the WCRP mission. The primary charge to TIRA is to develop a reanalysis intercomparison project plan that will attain the following objectives.1)To foster understanding and estimation of uncertainties in reanalysis data by intercomparison and other means)To communicate new developments and best practices among the reanalyses producing centers3)To enhance the understanding of data and assimilation issues and their impact on uncertainties, leading to improved reanalyses for climate assessment4)To communicate the strengths and weaknesses of reanalyses, their fitness for purpose, and best practices in the use of reanalysis datasets by the scientific communityThis contribution outlines the need for a task team on reanalyses, their intercomparison, the objectives of the team and progress thus far. Results for some pilot intercomparisons will also be discussed

Predicted chance that global warming will temporarily exceed 1.5 °C

The Paris Agreement calls for efforts to limit anthropogenic global warming to less than 1.5 °C above preindustrial levels. However, natural internal variability may exacerbate anthropogenic warming to produce temporary excursions above 1.5 °C. Such excursions would not necessarily exceed the Paris Agreement, but would provide a warning that the threshold is being approached. Here we develop a new capability to predict the probability that global temperature will exceed 1.5 °C above preindustrial levels in the coming 5 years. For the period 2017 to 2021 we predict a 38% and 10% chance, respectively, of monthly or yearly temperatures exceeding 1.5 °C, with virtually no chance of the 5‐year mean being above the threshold. Our forecasts will be updated annually to provide policy makers with advanced warning of the evolving probability and duration of future warming events

A multi-decade record of high quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID

Advancing global & regional reanalyses

This report outlines the structure of and summarizes the recommendations made at the 5th International Conference on Reanalysis (ICR5), attended by 259 participants from 37 countries, in Rome (Italy), on 13-17 November 2017. It first summarizes the conference structure. Then, the key recommendations of ICR5 are given for the five main conference topics: production; observations (data rescue and preparation); data assimilation methods; quality assurance of reanalysis; and applications in science, services, and policymaking. Lastly, five high-level recommendations are proposed to managing agencies on how best to advance the field of reanalyses, which serves tens of thousands of users, via enhanced research, development, and operations

DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management

Abstract Background Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma. Methods DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts. Results The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03–0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8–7.2, P &lt; 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22–0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3–11.1, P &lt; 0.001) with clinical implications. Conclusions The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone. </jats:sec

Current and emerging developments in subseasonal to decadal prediction

Weather and climate variations of subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus remains broadly similar (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correct, calibration and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Prograame (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis