ALBERT

Description: Transports across the continental shelf edge enhance shelf-sea production, remove atmospheric carbon and imply an active boundary to ocean circulation. Overall transports across the varied shelf edge from south-west of Britain to north of Scotland are estimated (from a variety of measurements and models) as several m〈sup〉2〈/sup〉s〈sup〉−1〈/sup〉. This large value results from variable strong wind-forced and tidal currents and along-slope flow.Even a globally typical 1 m〈sup〉2〈/sup〉s〈sup〉−1〈/sup〉 across an estimated 5x10〈sup〉5〈/sup〉 km of shelf edge amounts to 500 Sv; large compared with oceanic transports and potentially important to shelf-sea and adjacent oceanic budgets. However, exchanges with periods ∼ one day or less may be effective only for water properties that evolve on such short time-scales. Thus transports’ significance depends on distinctive properties of the water, or its contents, and on internal shelf-sea circulation affecting further transport. Transports across the NW European shelf edge enable its disproportionately strong CO〈sub〉2〈/sub〉 “pump”.The complex context, and small scales of numerous processes enabling cross-slope transports, imply a need for models. Measurements remain limited in extent and duration, but widely varied contexts, particular conditions, events, processes and behaviours are now available for model validation. Variability still renders observations insufficient for stable estimates of transports and exchanges, especially if partitioned by sector and season; indeed, there may be significant inter-annual differences. Validated fine-resolution models give the best prospect of spatial and temporal coverage and of estimating shelf-sea sensitivities to the adjacent ocean.

Description: Macroseismology plays a crucial role in earthquake hazard and risk analyses, tying earthquake occurrences and impacts from the past with those of the present and future. The use of macroseismic intensity has grown as the hazard layer within essential USGS and others’ real-time information products and even in presenting hazard maps in a form friendlier to nontechnical users. However, even with best practices, there are limitations to modern macroseismic data collection approaches. Whereas crowd-sourced intensities are robust for lower levels, they are poorly defined above intensity VII, where damage assessment requires knowledge of each building’s structural system. Likewise, the United States, New Zealand, and others employ the Modified Mercalli Intensity (MMI) scale, which is consistent with—yet inferior to—the more recently developed European Macroseismic Scale (EMS-98). We report on an IMS Working Group meeting held in October 2022 at the USGS Powell Center to address these and other issues and to work towards an IMS. Workshop goals were, first, to harmonize the MMI scale with EMS-98 for the US and NZ—which share several similar building types—by considering those structures and associated damage grades not well represented in the current EMS-98 building vulnerability table. Second, formalize the process of augmenting EMS-98 with vulnerability classes appropriate for building types in other countries, thus promoting a scale that can be employed globally. Such efforts require expanding the EMS-98 explanatory documents. Lastly, we discuss how standardized earthquake-damage data collection worldwide—as part of an IMS—could facilitate hazard and risk analyses.

Description: The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchmarked against a large number of experimental data, including different locations, growing season temperatures, atmospheric CO2 concentration, heat stress scenarios, and their interactions. In this paper, we describe the main characteristics of this global simulation dataset. Detailed cultivar, crop management, and soil datasets were compiled for all locations to drive 32 wheat growth models. The dataset consists of 30-year simulated data including 25 output variables for nine climate scenarios, including Baseline (1980-2010) with 360 or 550 ppm CO2, Baseline +2oC or +4oC with 360 or 550 ppm CO2, a mid-century climate change scenario (RCP8.5, 571 ppm CO2), and 1.5°C (423 ppm CO2) and 2.0oC (487 ppm CO2) warming above the pre-industrial period (HAPPI). This global simulation dataset can be used as a benchmark from a well-tested multi-model ensemble in future analyses of global wheat. Also, resource use efficiency (e.g., for radiation, water, and nitrogen use) and uncertainty analyses under different climate scenarios can be explored at different scales. The DOI for the dataset is 10.5281/zenodo.4027033 (AgMIP-Wheat, 2020), and all the data are available on the data repository of Zenodo (doi: 10.5281/zenodo.4027033). Two scientific publications have been published based on some of these data here.