scholarly journals Projections for the Köppen-Geiger climate classification under future climate change for the Iberian Peninsula

2021 ◽  
Author(s):  
Cristina Andrade ◽  
Joana Contente
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Classification ◽  
Dry Climates ◽  
Projected Changes

<p>Projections of the Köppen-Geiger climate classification under future climate change for the Iberian Peninsula (IP) are investigated by using a seven-ensemble mean of regional climate models (RCMs) attained from EURO-CORDEX. Maps with predicted future scenarios for temperature, precipitation and Köppen-Geiger classification are analyzed under RCP4.5 and RCP8.5 in Iberia. Widespread statistically significant shifts in temperature, precipitation and climate regimes are projected between 2041 and 2070, with higher expression under RCP8.5. An overall increase of temperatures and a decrease of precipitation in the south-southeast is predicted. Of the two climate types dry (B) and temperate (C), the dominant one was C in 86% of the Iberian territory for 1961-1990, predicted to decrease by 8.0% towards 2041-2070 under RCP4.5 (9.1% under RCP8.5). The hot-summer Mediterranean climate (CSa) will progressively replaces CSb (warm-summer) type towards north in the northwestern half of Iberia until 2070. This shift, depicted by the SSIM index, is noticeable in Portugal with a projected establishment of the CSa climate by 2041-2070. A predicted retreat of humid subtropical (Cfa) and temperate oceanic (Cfb) areas in the northeast towards Pyrenees region is noteworthy, alongside an increase of desert (BW) and semi-desert (BS) climates (7.8% and 9%) that progressively sets in the southeast (between Granada and Valencia). Climate types BSh and BWh (hot semi-desert and hot-desert, respectively), non-existent in 1961-1990 period, are projected to represent 2.8% of territory in 2041-2070 under RCP4.5 (5% under RCP8.5). The statistically significant projected changes hint at the disappearance of some vegetation species in certain regions of Iberia, with an expected increase of steppe, bush, grassland and wasteland vegetation cover, typical of dry climates in the southeast.</p><p><strong>Funding:</strong> This research was funded by National Funds by FCT - Portuguese Foundation for Science and Technology, under the project <strong>UIDB/04033/2020.</strong></p>

Köppen’s climate classification projections for the Iberian Peninsula

2020 ◽  
Vol 81 ◽  
pp. 71-89
Author(s):  
C Andrade ◽  
J Contente
Keyword(s):  
Iberian Peninsula ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate Change ◽  
Summer Climate ◽  
Dry Climates ◽  
Projected Changes ◽  
Vegetation Species ◽  
Expected Increase

Projections of Köppen-Geiger climate classifications under future climate change for the Iberian Peninsula are investigated using a 7-ensemble mean of regional climate models obtained from EURO-CORDEX. Maps with predicted future scenarios for temperature, precipitation and Köppen-Geiger classification are analyzed for RCP4.5 and RCP8.5 in Iberia. Widespread statistically significant shifts in temperature, precipitation and climate regimes are projected in the 2041-2070 period, with greater shifts occurring under RCP8.5. An overall increase in temperature and a decrease in precipitation in the south-southeast is predicted. Of the two climate types, dry (B) and temperate (C), the dominant one was C in 86% of Iberia for 1961-1990, predicted to decrease by 8.0% by 2041-2070 under RCP4.5 (9.5% under RCP8.5). The hot-summer Mediterranean climate (CSa) will progressively replace CSb (warm-summer climate) in the northwestern half of Iberia until 2070. This shift, depicted by the SSIM index, is particularly noticeable in Portugal, with the projected establishment of the CSa climate by 2041-2070. The predicted retreat of humid subtropical (Cfa) and temperate oceanic (Cfb) areas in the northeast towards the Pyrenees region is noteworthy, as is the increase of desert (BW) and semi-desert (BS) climates (7.8 and 9%) in the southeast (between Granada and Valencia). Climate types BSh and BWh (hot semi-desert and hot desert, respectively), non-existent in the 1961-1990 period, are projected to represent 2.8% of the territory in 2041-2070 under RCP4.5 (5% under RCP8.5). The statistically significant projected changes hint at the disappearance of some vegetation species in certain regions of Iberia, with an expected increase in steppe, bush, grassland and wasteland vegetation cover, typical of dry climates in the southeast.

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

scholarly journals Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

2011 ◽  
Vol 11 (12) ◽  
pp. 3275-3291 ◽  
Author(s):  
M. Ruiz-Ramos ◽  
E. Sánchez ◽  
C. Gallardo ◽  
M. I. Mínguez
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
High Temperatures ◽  
Climate Models ◽  
Cropping Systems ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Grain Filling ◽  
Maximum Temperature ◽  
Climate Change Scenarios

Abstract. Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

scholarly journals Quantification of the Expected Changes in Annual Maximum Daily Precipitation Quantiles under Climate Change in the Iberian Peninsula

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
The Future

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.

scholarly journals An update of IPCC climate reference regions for subcontinental analysis of climate model data: Definition and aggregated datasets

2020 ◽  
Author(s):  
Maialen Iturbide ◽  
José Manuel Gutiérrez ◽  
Lincoln Muniz Alves ◽  
Joaquín Bedia ◽  
Ezequiel Cimadevilla ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Future Climate Change ◽  
Temperature And Precipitation ◽  
Data Definition ◽  
Definition Of ◽  
Projected Changes

Abstract. Several sets of reference regions have been proposed in the literature for the regional synthesis of observed and model-projected climate change information. A popular example is the set of reference regions introduced in the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX) based on a prior coarser selection and then slightly modified for the 5th Assessment Report of the IPCC. This set was developed for reporting sub-continental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes (the typical resolution of the 5th Climate Model Intercomparison Projection, CMIP5, climate models was around 2º). These regions have been used as the basis for several popular spatially aggregated datasets, such as the seasonal mean temperature and precipitation in IPCC regions for CMIP5. Here we present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher model resolution (around 1º for CMIP6). As a result, the number of regions increased to 43 land plus 12 open ocean, better representing consistent regional climate features. The paper describes the rationale followed for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and shapefile together with companion R and Python notebooks to illustrate their use in practical problems (trimming data, etc.). We also describe the generation of a new dataset with monthly temperature and precipitation spatially aggregated in the new regions, currently for CMIP5 (for backwards consistency) and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter diagrams to offer guidance on the likely range of future climate change at the scale of reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository; https://github.com/SantanderMetGroup/ATLAS, doi:10.5281/zenodo.3688072 (Iturbide et al., 2020).

scholarly journals The Effects of Climate Change on Variability of the Growing Seasons in the Elbe River Lowland, Czech Republic

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Vera Potopová ◽  
Pavel Zahradníček ◽  
Luboš Türkott ◽  
Petr Štěpánek ◽  
Josef Soukup
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Growing Season ◽  
Spatiotemporal Variability ◽  
Elbe River ◽  
Study Region ◽  
The Elbe River ◽  
Projected Changes

This research aimed to identify an approach for adaptation of agriculture to increased climate variability and projected changes, taking into account regional specificity of climate change. Changes in the timing of growing season (GS) parameters for both observation and models data were computed using daily mean temperatures for three thresholds that correspond to the physiological requirements of the vegetable types. This research included a new assessment of the potential impacts of climate change on the GS of vegetables grown in the Elbe River lowland, one of the largest farmed vegetable regions in Central Europe. To accomplish this, a comprehensive analysis was conducted of the spatiotemporal variability of the date of the beginning of the growing season (BGS), the date of the end of the growing season (EGS), and the length of the growing season (GSL) for the period 1961–2011. In addition, an assessment was made of the potential changes in the dates of the BGS, EGS, and GSL for the Elbe River lowland, simulated using the regional climate models. Prospective areas for growing thermophilic vegetables in the study region were also determined.

scholarly journals Fine-scale variation in projected climate change presents opportunities for biodiversity conservation in Europe

2021 ◽  
Author(s):  
Tomáš Hlásny ◽  
Martin Mokroš ◽  
Laura Dobor ◽  
Katarína Merganičová ◽  
Martin Lukac
Keyword(s):  
Climate Change ◽  
Biodiversity Conservation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Scale ◽  
Regional Climate Models ◽  
Biodiversity Loss ◽  
Future Climate ◽  
Conservation Priorities ◽  
Continental Scale

Abstract Climate change is a major threat to global biodiversity, although projected changes show remarkable geographical and temporal variability. Understanding this variability allows for the identification of regions where the present-day conservation objectives may be at risk or where opportunities for biodiversity conservation emerge. We use a multi-model ensemble of regional climate models to identify areas with significantly high and low climate stability persistent throughout the 21st century in Europe. We then confront our predictions with the land coverage of three prominent biodiversity conservation initiatives at two scales. The continental-scale assessment shows that the most instable future climate in Europe is likely to occur at low and high latitudes, with the Iberian Peninsula and the Boreal zones identified as prominent areas of climatic instability. A follow-up regional scale investigation shows that robust climatic refugia exist even within the highly exposed southern and northern macro-regions. About 23–31 % of assessed biodiversity conservation sites in Europe coincide with these identified climatic refugia, we contend that these sites should be prioritised in the formulation of future conservation priorities as the stability of future climate is one of key factors determining their conservation prospects. Although such focus on climate refugia cannot halt the ongoing biodiversity loss, along with measures such as the resilience-based stewardship, it may improve the effectiveness of biodiversity conservation under climate change.

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