scholarly journals Future Projection of Precipitation Changes in the Júcar and Segura River Basins (Iberian Peninsula) by CMIP5 GCMs Local Downscaling

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 879
Author(s):  
Juan Javier Miró ◽  
María José Estrela ◽  
Jorge Olcina-Cantos ◽  
Javier Martin-Vide
Keyword(s):  
Iberian Peninsula ◽  
Climate Modeling ◽  
Mediterranean Coast ◽  
Small Scale ◽  
Climate Projections ◽  
Global Models ◽  
Historical Series ◽  
Precipitation Variable ◽  
Torrential Rainfall ◽  
Precipitation Changes

The basins of the Júcar and Segura rivers, on the Mediterranean coast of the Iberian Peninsula, present a special water problem and are of particular interest regarding climate change. These basins are very vulnerable to a possible scenario of decreasing water resources. Recent studies on historic rainfall since 1955 have indicated an ongoing loss of precipitation in their headwaters, especially in the case of the Júcar river. The aim of the present study is to perform climate projections for the precipitation variable for several future periods (2021–2040, 2051–2070, 2081–2100) and emission scenarios (RCPs 4.5, 8.5) within the Júcar and Segura River Basin authorities. For this purpose, a set of CMIP5 global models have been used, as well as the CDRD-HR-EIP-1955-2016 database, as a source of local observed information. This database comprises nearly 900 precipitation series in both basins and has been used in recent studies to determine historic trends of change in these basins. A statistical downscaling of the global models for all available observed series has been applied using the LARS-WG method. The results, although variable according to the CMIP5 model used, show the continuation of the patterns of precipitation change in the future, as already observed in the historical series. The results also predict a clear reduction in precipitation in the long term. However, torrential rainfall tends to increase in the coastal areas in relation to that observed in the short-term predictions. These results, due to their high spatial resolution, are of great interest for their use in small-scale hydrological and spatial planning (regional and local), which is one of the current challenges of climate modeling.

scholarly journals A Scale-Selective Data Assimilation Approach to Improving Tropical Cyclone Track and Intensity Forecasts in a Limited-Area Model: A Case Study of Hurricane Felix (2007)

2012 ◽  
Vol 27 (1) ◽  
pp. 124-140 ◽  
Author(s):  
Bin Liu ◽  
Lian Xie
Keyword(s):  
Data Assimilation ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Weather Forecasting ◽  
Forecast Error ◽  
Regional Model ◽  
Small Scale ◽  
Limited Area ◽  
Track Forecast ◽  
Global Models

Abstract Accurately forecasting a tropical cyclone’s (TC) track and intensity remains one of the top priorities in weather forecasting. A dynamical downscaling approach based on the scale-selective data assimilation (SSDA) method is applied to demonstrate its effectiveness in TC track and intensity forecasting. The SSDA approach retains the merits of global models in representing large-scale environmental flows and regional models in describing small-scale characteristics. The regional model is driven from the model domain interior by assimilating large-scale flows from global models, as well as from the model lateral boundaries by the conventional sponge zone relaxation. By using Hurricane Felix (2007) as a demonstration case, it is shown that, by assimilating large-scale flows from the Global Forecast System (GFS) forecasts into the regional model, the SSDA experiments perform better than both the original GFS forecasts and the control experiments, in which the regional model is only driven by lateral boundary conditions. The overall mean track forecast error for the SSDA experiments is reduced by over 40% relative to the control experiments, and by about 30% relative to the GFS forecasts, respectively. In terms of TC intensity, benefiting from higher grid resolution that better represents regional and small-scale processes, both the control and SSDA runs outperform the GFS forecasts. The SSDA runs show approximately 14% less overall mean intensity forecast error than do the control runs. It should be noted that, for the Felix case, the advantage of SSDA becomes more evident for forecasts with a lead time longer than 48 h.

scholarly journals S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales

2021 ◽  
Vol 14 (10) ◽  
pp. 6177-6195
Author(s):  
Paul R. Halloran ◽  
Jennifer K. McWhorter ◽  
Beatriz Arellano Nava ◽  
Robert Marsh ◽  
William Skirving
Keyword(s):  
Climate Change ◽  
Computational Efficiency ◽  
Dynamical Downscaling ◽  
Climate Projections ◽  
Grid Cells ◽  
Computationally Efficient ◽  
Global Models ◽  
Shelf Seas ◽  
Shelf Sea ◽  
Set Up

Abstract. The marine impacts of climate change on our societies will be largely felt through coastal waters and shelf seas. These impacts involve sectors as diverse as tourism, fisheries and energy production. Projections of future marine climate change come from global models. Modelling at the global scale is required to capture the feedbacks and large-scale transport of physical properties such as heat, which occur within the climate system, but global models currently cannot provide detail in the shelf seas. Version 2 of the regional implementation of the Shelf Sea Physics and Primary Production (S2P3-R v2.0) model bridges the gap between global projections and local shelf-sea impacts. S2P3-R v2.0 is a highly simplified coastal shelf model, computationally efficient enough to be run across the shelf seas of the whole globe. Despite the simplified nature of the model, it can display regional skill comparable to state-of-the-art models, and at the scale of the global (excluding high latitudes) shelf seas it can explain >50 % of the interannual sea surface temperature (SST) variability in ∼60 % of grid cells and >80 % of interannual variability in ∼20 % of grid cells. The model can be run at any resolution for which the input data can be supplied, without expert technical knowledge, and using a modest off-the-shelf computer. The accessibility of S2P3-R v2.0 places it within reach of an array of coastal managers and policy makers, allowing it to be run routinely once set up and evaluated for a region under expert guidance. The computational efficiency and relative scientific simplicity of the tool make it ideally suited to educational applications. S2P3-R v2.0 is set up to be driven directly with output from reanalysis products or daily atmospheric output from climate models such as those which contribute to the sixth phase of the Climate Model Intercomparison Project, making it a valuable tool for semi-dynamical downscaling of climate projections. The updates introduced into version 2.0 of this model are primarily focused around the ability to geographical relocate the model, model usability and speed but also scientific improvements. The value of this model comes from its computational efficiency, which necessitates simplicity. This simplicity leads to several limitations, which are discussed in the context of evaluation at regional and global scales.

scholarly journals State and Perspectives of the Concept of Large‐Scale Conditioning of Regional Climate Modelling

2018 ◽  
Author(s):  
Hans von Storch ◽  
Leone Cavicchia ◽  
Frauke Feser ◽  
Delei Li
Keyword(s):  
Large Scale ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Ocean Dynamics ◽  
Small Scale ◽  
Climate Modelling ◽  
Coastal Regions ◽  
Global Models ◽  
Atmospheric Disturbances ◽  
Low Level Jets

We review the state of dynamical downscaling with scale-constrained regional and global models. The methodology, in particular spectral nudging, has become a routine and well-researched tool for hindcasting climatologies of sub-synoptic atmospheric disturbances in coastal regions. At present, the spectrum of applications is expanding to other phenomena, but also to ocean dynamics and to extended forecasting. Also new diagnostic challenges are appearing such as spatial characteristics of small-scale phenomena such as Low Level Jets.

First record of the Levantine species Scoloplos haasi (Orbiniidae: Scolecida: Annelida) from the Mediterranean coast of Spain

2009 ◽  
Vol 90 (5) ◽  
pp. 1051-1054 ◽  
Author(s):  
Eduardo López
Keyword(s):  
Natural History ◽  
Iberian Peninsula ◽  
British Museum ◽  
First Record ◽  
Western Mediterranean ◽  
Mediterranean Coast ◽  
Geographical Range ◽  
Polychaete Species ◽  
The Mediterranean

During an investigation devoted to characterize all the Orbiniidae polychaete species present in the Iberian Peninsula, several individuals previously identified as Scoloplos armiger showed to actually belong to Scoloplos haasi, a species to date considered endemic from Israel. The comparison with the holotype deposited in the British Museum of Natural History confirmed the identification. This record of S. haasi is not only a new one for the western Mediterranean but also the first one out of its original locality, extending largely westwards the geographical range of the species.

scholarly journals CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica

2020 ◽  
Vol 14 (3) ◽  
pp. 855-879 ◽  
Author(s):  
Alice Barthel ◽  
Cécile Agosta ◽  
Christopher M. Little ◽  
Tore Hattermann ◽  
Nicolas C. Jourdain ◽  
...  
Keyword(s):  
Model Selection ◽  
Climate Models ◽  
Climate Modeling ◽  
Global Climate ◽  
Ice Sheet ◽  
Global Climate Models ◽  
Historical Period ◽  
Climate Projections ◽  
Subsurface Ocean ◽  
Spatial Domains

Abstract. The ice sheet model intercomparison project for CMIP6 (ISMIP6) effort brings together the ice sheet and climate modeling communities to gain understanding of the ice sheet contribution to sea level rise. ISMIP6 conducts stand-alone ice sheet experiments that use space- and time-varying forcing derived from atmosphere–ocean coupled global climate models (AOGCMs) to reflect plausible trajectories for climate projections. The goal of this study is to recommend a subset of CMIP5 AOGCMs (three core and three targeted) to produce forcing for ISMIP6 stand-alone ice sheet simulations, based on (i) their representation of current climate near Antarctica and Greenland relative to observations and (ii) their ability to sample a diversity of projected atmosphere and ocean changes over the 21st century. The selection is performed separately for Greenland and Antarctica. Model evaluation over the historical period focuses on variables used to generate ice sheet forcing. For stage (i), we combine metrics of atmosphere and surface ocean state (annual- and seasonal-mean variables over large spatial domains) with metrics of time-mean subsurface ocean temperature biases averaged over sectors of the continental shelf. For stage (ii), we maximize the diversity of climate projections among the best-performing models. Model selection is also constrained by technical limitations, such as availability of required data from RCP2.6 and RCP8.5 projections. The selected top three CMIP5 climate models are CCSM4, MIROC-ESM-CHEM, and NorESM1-M for Antarctica and HadGEM2-ES, MIROC5, and NorESM1-M for Greenland. This model selection was designed specifically for ISMIP6 but can be adapted for other applications.

scholarly journals Dry and moist dynamics shape regional patterns of extreme precipitation sensitivity

2020 ◽  
Vol 117 (16) ◽  
pp. 8757-8763 ◽  
Author(s):  
Ji Nie ◽  
Panxi Dai ◽  
Adam H. Sobel
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Regional Scale ◽  
Vertical Motion ◽  
Precipitable Water ◽  
Small Scale ◽  
Climate Projections ◽  
Regional Patterns

Responses of extreme precipitation to global warming are of great importance to society and ecosystems. Although observations and climate projections indicate a general intensification of extreme precipitation with warming on global scale, there are significant variations on the regional scale, mainly due to changes in the vertical motion associated with extreme precipitation. Here, we apply quasigeostrophic diagnostics on climate-model simulations to understand the changes in vertical motion, quantifying the roles of dry (large-scale adiabatic flow) and moist (small-scale convection) dynamics in shaping the regional patterns of extreme precipitation sensitivity (EPS). The dry component weakens in the subtropics but strengthens in the middle and high latitudes; the moist component accounts for the positive centers of EPS in the low latitudes and also contributes to the negative centers in the subtropics. A theoretical model depicts a nonlinear relationship between the diabatic heating feedback (α) and precipitable water, indicating high sensitivity of α (thus, EPS) over climatological moist regions. The model also captures the change of α due to competing effects of increases in precipitable water and dry static stability under global warming. Thus, the dry/moist decomposition provides a quantitive and intuitive explanation of the main regional features of EPS.

scholarly journals Laplacian Eigenfunctions for Climate Analysis

2015 ◽  
Vol 28 (18) ◽  
pp. 7420-7436 ◽  
Author(s):  
Timothy DelSole ◽  
Michael K. Tippett
Keyword(s):  
Laplace Operator ◽  
Climate Models ◽  
Climate Modeling ◽  
Global Scale ◽  
Small Sample ◽  
Training Data ◽  
Basis Set ◽  
Small Scale ◽  
Climate Analysis ◽  
The Laplace Operator

Abstract This paper proposes a new method for representing data in a general domain on a sphere. The method is based on the eigenfunctions of the Laplace operator, which form an orthogonal basis set that can be ordered by a measure of length scale. Representing data with Laplacian eigenfunctions is attractive if one wants to reduce the dimension of a dataset by filtering out small-scale variability. Although Laplacian eigenfunctions are ubiquitous in climate modeling, their use in arbitrary domains, such as over continents, is not common because of the numerical difficulties associated with irregular boundaries. Recent advances in machine learning and computational sciences are exploited to derive eigenfunctions of the Laplace operator over an arbitrary domain on a sphere. The eigenfunctions depend only on the geometry of the domain and hence require no training data from models or observations, a feature that is especially useful in small sample sizes. Another novel feature is that the method produces reasonable eigenfunctions even if the domain is disconnected, such as a land domain comprising isolated continents and islands. The eigenfunctions are illustrated by quantifying variability of monthly mean temperature and precipitation in climate models and observations. This analysis extends previous studies by showing that climate models have significant biases not only in global-scale spatial averages but also in global-scale dipoles and other physically important structures. MATLAB and R codes for deriving Laplacian eigenfunctions are available upon request.

scholarly journals Who Cares About Ouacil? The Postmortem Itinerary of a Young Border Crosser

2019 ◽  
Vol 64 (4) ◽  
pp. 525-539 ◽  
Author(s):  
Carolina Kobelinsky
Keyword(s):  
Civil Society ◽  
Iberian Peninsula ◽  
Young Women ◽  
Mediterranean Coast ◽  
Judicial System ◽  
The Real ◽  
Final Destination ◽  
Multiple Dimensions ◽  
Tuesday Afternoon ◽  
The Dead

On a sunny Tuesday afternoon in May 2015, two young women walking by a lighthouse in Melilla, a Spanish enclave on the northern shores of Morocco’s Mediterranean coast, found the lifeless body of a young man. As the police quickly soon confirmed, the boy had died while trying to jump on a ferry that would take him “to the real Europe” (i.e., the Iberian Peninsula). Using ethnography, this article aims at mapping the afterlives of this dead young man, in their multiple dimensions. It traces the body’s trajectory through the judicial system and bureaucratic registration; it investigates attempts made by various agencies at identifying the corpse and carrying it to its final destination; finally, it analyzes the efforts made to pay him tribute. By tracing the dead boy’s itinerary, this article sheds light on the conflictual interactions between different actors (state and municipal institutions, civil society groups, and migrants themselves) involved in the treatment of deaths at the borders.

Recurrence of historical drought events over the Iberian Peninsula in different observational datasets and reanalyses

2020 ◽  
Author(s):  
Julia Moemken ◽  
Joaquim G. Pinto
Keyword(s):  
Iberian Peninsula ◽  
Standardized Precipitation Index ◽  
Small Scale ◽  
Special Focus ◽  
Severe Drought ◽  
Topographic Effects ◽  
Physical Mechanisms ◽  
Invading Species ◽  
Expert Team ◽  
Oak Ecosystem

<p>Extreme climate events such as droughts can have very strong impacts both for society and the environment. In particular, the occurrence of severe droughts can endanger the balance of an ecosystem. While intact woodlands, e.g. the Iberian cork-oak ecosystem, are well adapted to withstand single severe drought events, both competition with invading species and recurrent droughts (i.e. droughts in consecutive years) may drive these systems towards critical limits. This is of crucial importance considering that the frequency, intensity and duration of extreme droughts are projected to increase in future decades in various regions all over the world, including the Mediterranean region. <br>We evaluate the occurrence and intensity of historical extreme drought events over the Iberian Peninsula for the past decades. Special focus is given to consecutive/recurrent drought events. Our study compares various indices for the identification of droughts, e.g. the SPEI (Standardized Precipitation Evapotranspiration Index), the SPI (Standardized Precipitation Index) or indices from the “Expert Team on Climate Change Detection and Indices” (ETCCDI). All indices are based on precipitation and/or temperature. We analyse different observational (E-OBS V17, V20, IBERIA01) and reanalysis datasets (ERA-Interim, ERA5) at several spatial resolutions, ranging roughly between 10 km and 25 km. The high resolution of the datasets enables the consideration of small-scale processes and local topographic effects which are relevant for extreme droughts, thus enabling a deeper insight on the physical mechanisms associated with droughts in the study area.</p>

Coordinated Global and Regional Climate Modeling*

2015 ◽  
Vol 29 (1) ◽  
pp. 17-35 ◽  
Author(s):  
J. F. Scinocca ◽  
V. V. Kharin ◽  
Y. Jiao ◽  
M. W. Qian ◽  
M. Lazare ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Climate Modeling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Value Added ◽  
Regional Climate Modeling ◽  
Climate Projections ◽  
Climate Modelling

Abstract A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.

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