Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 3 de 3
Filtrar
Más filtros











Base de datos
Intervalo de año de publicación
1.
Sci Data ; 11(1): 578, 2024 Jun 04.
Artículo en Inglés | MEDLINE | ID: mdl-38834583

RESUMEN

Large ensembles of global temperature are provided for three climate scenarios: historical (2006-16), 1.5 °C and 2.0 °C above pre-industrial levels. Each scenario has 700 members (70 simulations per year for ten years) of 6-hourly mean temperatures at a resolution of 0.833° ´ 0.556° (longitude ´ latitude) over the land surface. The data was generated using the climateprediction.net (CPDN) climate simulation environment, to run HadAM4 Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre. Biases in simulated temperature were identified and corrected using quantile mapping with reference temperature data from ERA5. The data is stored within the UK Natural and Environmental Research Council Centre for Environmental Data Analysis repository as NetCDF V4 files.

2.
Nature ; 603(7903): 841-845, 2022 03.
Artículo en Inglés | MEDLINE | ID: mdl-35355000

RESUMEN

Coastal communities across the world are already feeling the disastrous impacts of climate change through variations in extreme sea levels1. These variations reflect the combined effect of sea-level rise and changes in storm surge activity. Understanding the relative importance of these two factors in altering the likelihood of extreme events is crucial to the success of coastal adaptation measures. Existing analyses of tide gauge records2-10 agree that sea-level rise has been a considerable driver of trends in sea-level extremes since at least 1960. However, the contribution from changes in storminess remains unclear, owing to the difficulty of inferring this contribution from sparse data and the consequent inconclusive results that have accumulated in the literature11,12. Here we analyse tide gauge observations using spatial Bayesian methods13 to show that, contrary to current thought, trends in surge extremes and sea-level rise both made comparable contributions to the overall change in extreme sea levels in Europe since 1960 . We determine that the trend pattern of surge extremes reflects the contributions from a dominant north-south dipole associated with internal climate variability and a single-sign positive pattern related to anthropogenic forcing. Our results demonstrate that both external and internal influences can considerably affect the likelihood of surge extremes over periods as long as 60 years, suggesting that the current coastal planning practice of assuming stationary surge extremes1,14 might be inadequate.


Asunto(s)
Desastres , Elevación del Nivel del Mar , Teorema de Bayes , Cambio Climático , Europa (Continente)
3.
Sci Data ; 5: 180057, 2018 04 10.
Artículo en Inglés | MEDLINE | ID: mdl-29633985

RESUMEN

Large data sets used to study the impact of anthropogenic climate change on the 2013/14 floods in the UK are provided. The data consist of perturbed initial conditions simulations using the Weather@Home regional climate modelling framework. Two different base conditions, Actual, including atmospheric conditions (anthropogenic greenhouse gases and human induced aerosols) as at present and Natural, with these forcings all removed are available. The data set is made up of 13 different ensembles (2 actual and 11 natural) with each having more than 7500 members. The data is available as NetCDF V3 files representing monthly data within the period of interest (1st Dec 2013 to 15th February 2014) for both a specified European region at a 50 km horizontal resolution and globally at N96 resolution. The data is stored within the UK Natural and Environmental Research Council Centre for Environmental Data Analysis repository.

SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA