The future of the Portuguese (SW Europe) most vulnerable coastal areas under climate change – Part I: Performance evaluation and shoreline evolution from a downscaled bias corrected wave climate ensemble DOI Creative Commons
Gil Lemos, Ivana Bosnic, Carlos Antunes

и другие.

Ocean Engineering, Год журнала: 2024, Номер 302, С. 117661 - 117661

Опубликована: Апрель 4, 2024

Some of the most disruptive effects climate change are projected to be felt along coastlines. The combined future changes in water levels and wave coastal areas constitute one serious threats their sustainable evolution, compromising critical infrastructures, resources, ecosystems, communities. Understanding long-term remains challenging, however, due multivariate multi-time-and-space-scale nature. In this study, we propose an innovative methodology for a complete vulnerability assessment sandy low-lying areas, based on dynamic, ensemble-based projections from Coupled Model Intercomparison Project phase 5 (CMIP5). current Part I sea level rise (SLR) nearshore shoreline evolution assessed at five key-locations Portuguese coastline. Longshore sediment transport (LST) computed, sedimentary imbalances quantified. Overall, robust retreat up 300 m is projected, especially northern central with continued erosion driven mainly by imbalance SLR. decrease energy responsible slight alleviation trends, 6.33%, whereas increase northerly incoming waves expected lead northward beach rotations western Mainland Portugal. resulting loss 0.786 km2 dry land 2100 14 km analysed coastline, threaten several urban calling implementation adequate management adaptation plans, reduce impacts population, livelihood, ecosystems.

Язык: Английский

Comparison of conventional and machine learning methods for bias correcting CMIP6 rainfall and temperature in Nigeria DOI

Bashir Tanimu,

Al−Amin Danladi Bello,

Sule Argungu Abdullahi

и другие.

Theoretical and Applied Climatology, Год журнала: 2024, Номер 155(6), С. 4423 - 4452

Опубликована: Фев. 27, 2024

Язык: Английский

Процитировано

6
High resolution climate change projections for the Pyrenees region DOI Creative Commons

María Pilar Amblar-Francés,

Petra Ramos‐Calzado,

Jorge Sanchis-Lladó

и другие.

Advances in science and research, Год журнала: 2020, Номер 17, С. 191 - 208

Опубликована: Сен. 30, 2020

Abstract. The Pyrenees, located in the transition zone of Atlantic and Mediterranean climates, constitute a paradigmatic example mountains undergoing rapid changes environmental conditions, with potential impact on availability water resources, mainly for downstream populations. High-resolution probabilistic climate change projections precipitation temperature are crucial element stakeholders to make well-informed decisions adaptation new conditions. In this line, we have generated high–resolution 21st century by applying two statistical downscaling methods (regression max min temperatures, analogue precipitation) over Pyrenees region frame CLIMPY project high-resolution (5 km × 5 km) observational grid using 24 models from CMIP5. application such high resolution instead station data partially circumvent problems associated non-uniform distribution situ data. This database based algorithms complements widely used EUROCORDEX dynamical allows identify features that dependent particular method. our analysis, not only focus maximum minimum temperatures but also some relevant extreme indexes, being 1986–2005 reference period. Although predict general increase extremes end century, exact spatial much more remains uncertain as they strongly model dependent. Besides, precipitation, uncertainty can mask – depending zones- signal change. However, large number downscaled allow us provide differential information at least massif level. RCP becomes significant second half differentiated massifs analysed indexes RCP8.5 century.

Язык: Английский

Процитировано

35
Remaining error sources in bias-corrected climate model outputs DOI
Jie Chen, François Brissette,

D. Caya

и другие.

Climatic Change, Год журнала: 2020, Номер 162(2), С. 563 - 582

Опубликована: Май 26, 2020

Язык: Английский

Процитировано

33
Regional Climate Model Biases, Their Dependence on Synoptic Circulation Biases and the Potential for Bias Adjustment: A Process‐Oriented Evaluation of the Austrian Regional Climate Projections DOI Creative Commons
Douglas Maraun, Heimo Truhetz, Armin Schaffer

и другие.

Journal of Geophysical Research Atmospheres, Год журнала: 2021, Номер 126(6)

Опубликована: Март 10, 2021

Abstract The Austrian regional climate projections are based on an ensemble of bias adjusted model simulations. Bias adjustment (BA) improves the usability for impact studies, but cannot mitigate fundamental errors. This argument holds in particular biases temporal dependence, which is strongly influenced by large‐scale circulation. Global models (GCMs), underlying projections, suffer from substantial circulation We therefore, conduct a process‐based evaluation focusing errors, their imprints and potential BA. First, we define nine synoptic weather types assess how well considered represent occurrence persistence. Second, overall dry hot day probabilities, as conditional type occurrence; duration spells. Third, investigate these depend persistence relevant types. And fourth, study much BA biases. Many GCMs misrepresent These have clear imprint spell durations. many cases helps to greatly reduce even presence biases, may some amplify Persistence especially representation meteorological drought. Biases spells fully be mitigated

Язык: Английский

Процитировано

30
The future of the Portuguese (SW Europe) most vulnerable coastal areas under climate change – Part I: Performance evaluation and shoreline evolution from a downscaled bias corrected wave climate ensemble DOI Creative Commons
Gil Lemos, Ivana Bosnic, Carlos Antunes

и другие.

Ocean Engineering, Год журнала: 2024, Номер 302, С. 117661 - 117661

Опубликована: Апрель 4, 2024

Some of the most disruptive effects climate change are projected to be felt along coastlines. The combined future changes in water levels and wave coastal areas constitute one serious threats their sustainable evolution, compromising critical infrastructures, resources, ecosystems, communities. Understanding long-term remains challenging, however, due multivariate multi-time-and-space-scale nature. In this study, we propose an innovative methodology for a complete vulnerability assessment sandy low-lying areas, based on dynamic, ensemble-based projections from Coupled Model Intercomparison Project phase 5 (CMIP5). current Part I sea level rise (SLR) nearshore shoreline evolution assessed at five key-locations Portuguese coastline. Longshore sediment transport (LST) computed, sedimentary imbalances quantified. Overall, robust retreat up 300 m is projected, especially northern central with continued erosion driven mainly by imbalance SLR. decrease energy responsible slight alleviation trends, 6.33%, whereas increase northerly incoming waves expected lead northward beach rotations western Mainland Portugal. resulting loss 0.786 km2 dry land 2100 14 km analysed coastline, threaten several urban calling implementation adequate management adaptation plans, reduce impacts population, livelihood, ecosystems.

Язык: Английский

Процитировано

5