30 research outputs found

    Object storage: how chunky would you like your data?

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    In this study we examine object storage, a cutting-edge cloud-native technology specifically designed for efficiently managing large datasets. While object storage offers significant cost-effectiveness compared to disk storage, it requires data to be appropriately adapted to fully realise its benefits. Data retrieval from object storage is over HTTP in complete "objects," which are either entire files or file chunks. As this is relatively new technology, there is a clear lack of established tools and best-practice for converting various file types for optimal use with object storage, particularly for large gridded and N-dimensional datasets used in environmental and climate science. The performance and speed of object storage are contingent upon the data's structure, chunking, and the specific analysis requirements of the user. Consequently, a better understanding of these interactions is essential before widespread adoption. To address this need, our study conducted a series of experiments using gridded data with different chunking strategies, aiming to identify the most efficient approach for utilizing and accessing data stored in an object store. Our findings highlight the need for comprehensive understanding of object storage before its widespread adoption, and serve as a valuable resource for guiding future users in utilizing object storage effectively

    How will climate change affect the spatial coherence of streamflow and groundwater droughts in Great Britain?

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    How climate change will affect the spatial coherence of droughts is a key question that water managers must answer in order to adopt strategies to mitigate impacts on water resources. Water transfers from regions with excess to those in deficit are fundamental to such strategies, but only possible if both regions are not simultaneously under drought conditions—these relationships could change in a warming world. Here, we use future simulations (under RCP8.5) of streamflow (186 catchments) and groundwater level (41 boreholes) from the Enhanced Future Flows and Groundwater (eFLaG) dataset to analyse the projected change in the spatial coherence of hydrological droughts at a national scale, with Great Britain as an example. Joint and conditional probabilities of two regions being in drought simultaneously are used to characterise the spatial coherence. The results are sensitive to various uncertainties, including the way drought is defined. However, some key findings emerge. In particular, for droughts defined based on current conditions, our results show that the spatial coherence of streamflow droughts for the ‘far future’ (2050–2089) is expected to increase during the summer everywhere in the country. During the winter, however, spatial coherence may only increase in the South-East, where the sharpest rise in winter droughts is likely to occur. The coherence between groundwater and streamflow droughts shows a more mixed picture, dependant on season and region. One important observation is that, in the South-East during the summer, the proportion of streamflow droughts that coincide with groundwater droughts is expected to decrease. These results provide a valuable insight for water managers to help inform their long-term strategy to overcome future impacts of droughts, including the feasibility of inter-region water transfers and conjunctive use (surface and groundwater) schemes. This flexible methodology has the potential to be applied in other parts of the world to help shape strategic regional and national investments to increase resilience to droughts

    Projected changes in the East Asian hydrological cycle for different levels of future global warming

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    Recent decades have shown significant changes to the hydrological cycle over East Asia (EA), and further changes are expected due to future global warming. This study evaluates projected seasonal changes in the EA hydrological cycle using simulations that are 1.5 °C, 2.0 °C and 3.0 ∘C warmer than pre-industrial, from the Met Office Unified Model (MetUM) Global Ocean Mixed Layer model version 2.0 (GOML2.0), compared against present-day conditions. The moisture sources of the warming-induced precipitation changes are identified over five hydrologically unique regions within EA. Precipitation over EA increases with warming (except over southeastern EA in the spring and autumn) due to the intensified hydrological cycle. The projected seasonal changes in the hydrological cycle are usually nonlinear, with the rate of change between 1.5 ∘C and 2.0 ∘C larger than the rate of change between 2.0 ∘C and 3.0 ∘C of warming. The warming-induced precipitation increases are mainly associated with an increase in remote moisture convergence rather than local moisture recycling, except over the Tibetan Plateau. Decomposition of the changes in moisture sources by direction and flux component indicate that changes from the west are dominated by changes to moisture and changes from the north are more circulation driven. The changes from the south are moisture driven over southern EA and driven by moisture and circulation change over northern EA. Our results highlight the regionally and seasonally diverse projected changes to the EA hydrological cycle due to global warming, which will be useful for region-specific climate mitigation policies and the implementation of seasonally varying adaptation methods
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