Global Changes in Drought Conditions Under Different Levels of Warming

Geophysical Research Letters, Год журнала: 2018, Номер 45(7), С. 3285 - 3296

Опубликована: Март 26, 2018

Higher evaporative demands and more frequent persistent dry spells associated with rising temperatures suggest that drought conditions could worsen in many regions of the world. In this study, we assess how may develop across globe for 1.5, 2, 3°C warming compared to preindustrial temperatures. Results show two thirds global population will experience a progressive increase warming. For drying areas, durations are projected rise at rapidly increasing rates warming, averaged globally from 2.0 month/°C below 1.5°C 4.2 when approaching 3°C. Drought magnitudes double 30% landmass under stringent mitigation. If contemporary continue, water supply-demand deficits become fivefold size most Africa, Australia, southern Europe, central states United States, Central America, Caribbean, north-west China, parts Southern America. approximately 20% land surface, magnitude halve higher levels, mainly areas north latitude 55°N, but also South America Eastern South-eastern Asia. A significant frequency droughts is Mediterranean basin, West Asia, Oceania, where happen 5 10 times even ambitious mitigation targets current 100-year events occur every five years

Язык: Английский

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Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Climate Dynamics, Год журнала: 2017, Номер 50(1-2), С. 31 - 49

Опубликована: Март 25, 2017

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed transfer colour information from one another—the N-dimensional probability density function transform—is adapted use a algorithm (MBCn) climate model projections/predictions multiple MBCn is generalization mapping transfers all aspects observed continuous distribution corresponding variables model. When projections, changes quantiles each variable historical and projection period also preserved. The demonstrated on three case studies. First, method with characteristics mimic problem. Second, suite 3-hourly surface meteorological Canadian Centre Climate Modelling Analysis Regional Model (CanRCM4) across North American domain. Components Forest Fire Weather Index (FWI) System, complicated set indices characterizes risk wildfire, then calculated verified against values. Third, biases spatial structure CanRCM4 precipitation fields. Results compared algorithm, which neglects variables, two algorithms, corrects form inter-variable correlation structure. outperforms these alternatives, by large margin, particularly annual maxima FWI spatiotemporal autocorrelation

Язык: Английский

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Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0)

Geoscientific model development, Год журнала: 2019, Номер 12(7), С. 3055 - 3070

Опубликована: Июль 17, 2019

Abstract. In this paper I present new methods for bias adjustment and statistical downscaling that are tailored to the requirements of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). comparison their predecessors, allow a more robust extreme values, preserve trends accurately across quantiles, facilitate clearer separation downscaling. The method is stochastic better at adjusting spatial variability than old interpolation method. Improvements in trend preservation demonstrated cross-validation framework.

Язык: Английский

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Recent increases in tropical cyclone intensification rates

Nature Communications, Год журнала: 2019, Номер 10(1)

Опубликована: Фев. 7, 2019

Abstract Tropical cyclones that rapidly intensify are typically associated with the highest forecast errors and cause a disproportionate amount of human financial losses. Therefore, it is crucial to understand if, why, there observed upward trends in tropical cyclone intensification rates. Here, we utilize two observational datasets calculate 24-hour wind speed changes over period 1982–2009. We compare natural variability bias-corrected, high-resolution, global coupled model experiments accurately simulate climatological distribution intensification. Both show significant increases rates Atlantic basin highly unusual compared model-based estimates internal climate variations. Our results suggest detectable increase positive contribution from anthropogenic forcing reveal need for more reliable data before detecting robust trend at scale.

Язык: Английский

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Assessment of the European Climate Projections as Simulated by the Large EURO‐CORDEX Regional and Global Climate Model Ensemble

Journal of Geophysical Research Atmospheres, Год журнала: 2020, Номер 126(4)

Опубликована: Ноя. 21, 2020

Abstract This paper analyzes the ensemble of regional climate model (RCM) projections for Europe completed within EURO‐CORDEX project. Projections are available two greenhouse gas concentration scenarios RCP2.6 (22 members) and RCP8.5 (55 at 0.11° resolution from 11 RCMs driven by eight global models (GCMs). The RCM results compared with driving CMIP5 but also a subset last generation CMIP6 projections. Maximum warming is projected all ensembles in Northern winter, along maximum precipitation increase there; summer, occurs Mediterranean Southern European regions associated decrease. shows largest signals, both temperature precipitation, inter‐model spread. There high consensus across on an extreme drought frequency region. Extreme indices show heat extremes decrease cold extremes, showing highest values finest spatial details. data set unprecedented size quality will provide basis impact assessment service activities

Язык: Английский

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Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level

Climatic Change, Год журнала: 2017, Номер 143(1-2), С. 13 - 26

Опубликована: Май 16, 2017

Impacts of climate change at 1.5, 2 and 3 °C mean global warming above preindustrial level are investigated compared for runoff, discharge snowpack in Europe. Ensembles projections representing each the levels were assembled to describe hydro-meteorological °C. These ensembles then used force an ensemble five hydrological models changes indicators calculated. It is seen that there clear local impacts on evapotranspiration, mean, low high runoff snow water equivalent between a degree warmer world. In world, more intense spatially extensive. Robust increases affect Scandinavian mountains 1.5 °C, but extend over most Norway, Sweden northern Poland. At Norway affected by robust all indicators. Decreases annual only Portugal warming, decreases around entire Iberian coast, Balkan Coast parts French coast. Europe, distinct increase strengthening case mitigation lower warming. Between continue increase, less clear. Changes Europe's larger rivers due lack homogenous across river catchments, with exception Scandinavia where discharges level.

Язык: Английский

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Climate change threatens terrestrial water storage over the Tibetan Plateau

Nature Climate Change, Год журнала: 2022, Номер 12(9), С. 801 - 807

Опубликована: Авг. 15, 2022

Язык: Английский

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Increased likelihood of heat-induced large wildfires in the Mediterranean Basin

Scientific Reports, Год журнала: 2020, Номер 10(1)

Опубликована: Авг. 14, 2020

Abstract Wildfire activity is expected to increase across the Mediterranean Basin because of climate change. However, effects future change on combinations atmospheric conditions that promote wildfire remain largely unknown. Using a fire-weather based classification wildfires, we show scenarios point an in frequency two heat-induced types have been related largest wildfires recent years. Heat-induced are characterized by compound dry and warm occurring during summer heatwaves, either under moderate ( heatwave type) or intense hot drought drought. The projected 14% end century (2071–2100) RCP4.5 scenario, 30% RCP8.5, suggesting extent large will throughout Basin.

Язык: Английский

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Multivariate Bias Correction of Climate Model Output: Matching Marginal Distributions and Intervariable Dependence Structure

Journal of Climate, Год журнала: 2016, Номер 29(19), С. 7045 - 7064

Опубликована: Май 6, 2016

Abstract Univariate bias correction algorithms, such as quantile mapping, are used to address systematic biases in climate model output. Intervariable dependence structure (e.g., between different quantities like temperature and precipitation or sites) is typically ignored, which can have an impact on subsequent calculations that depend multiple variables. A novel multivariate (MBC) algorithm introduced a multidimensional analog of univariate mapping. Two variants presented. MBCp MBCr respectively correct Pearson correlation Spearman rank structure, with marginal distributions both constrained match observed via MBC demonstrated two case studies: 1) bivariate monthly output from large ensemble models 2) vertical humidity wind profiles, including calculation vertically integrated water vapor transport detection atmospheric rivers. The energy distance recommended omnibus measure performance for selection. As expected, substantial improvements relative mapping found each case. For reference, characteristics the compared against existing techniques. performs competitively fills role flexible, general purpose algorithm.

Язык: Английский

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Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes

Hydrology and earth system sciences, Год журнала: 2017, Номер 21(6), С. 2649 - 2666

Опубликована: Июнь 6, 2017

Abstract. Commonly used bias correction methods such as quantile mapping (QM) assume the function of error values between modeled and observed distributions are stationary or time invariant. This article finds that this cannot be assumed to stationary. As a result, QM lacks justification inflate/deflate various moments climate change signal. Previous adaptations QM, most notably delta (QDM), have been developed do not rely on assumption stationarity. Here, we outline methodology called scaled distribution (SDM), which is conceptually similar QDM, but more explicitly accounts for frequency rain days likelihood individual events. The SDM method found outperform detrended in its ability better preserve raw model projected changes meteorological variables temperature precipitation.

Язык: Английский

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