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

2020 ◽  
Vol 12 (4) ◽  
pp. 2959-2970
Author(s):  
Maialen Iturbide ◽  
José M. Gutiérrez ◽  
Lincoln M. Alves ◽  
Joaquín Bedia ◽  
Ruth Cerezo-Mota ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Atmospheric Model ◽  
Future Climate Change ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Scatter Plots ◽  
Projected Changes

Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and 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 dataset. 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 atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 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 plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

scholarly journals Impacts of climate change on temperature, precipitation and hydrology in Finland – studies using bias corrected Regional Climate Model data

2015 ◽  
Vol 12 (3) ◽  
pp. 2657-2706 ◽  
Author(s):  
T. Olsson ◽  
J. Jakkila ◽  
N. Veijalainen ◽  
L. Backman ◽  
J. Kaurola ◽  
...  
Keyword(s):  
Climate Change ◽  
Seasonal Changes ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Catchment Scale ◽  
Temperature And Precipitation

Abstract. Assessment of climate change impacts on climate and hydrology on catchment scale requires reliable information about the average values and climate fluctuations of the past, present and future. Regional Climate Models (RCMs) used in impact studies often produce biased time series of meteorological variables. In this study bias correction of RCM temperature and precipitation for Finland is carried out using different versions of distribution based scaling (DBS) method. The DBS adjusted RCM data is used as input of a hydrological model to simulate changes in discharges in four study catchments in different parts of Finland. The annual mean discharges and seasonal variation simulated with the DBS adjusted temperature and precipitation data are sufficiently close to observed discharges in the control period (1961–2000) and produce more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data. Furthermore, with most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data during 1961–2100. However, if the biases in the mean or the SD of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections. The DBS method influences especially the projected seasonal changes in discharges and the use of uncorrected data can produce unrealistic seasonal discharges and changes. The projected changes in annual mean discharges are moderate or small, but seasonal distribution of discharges will change significantly.

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>

scholarly journals New Insights in Regional Climate Change: Coupled Land Albedo Change Estimation in Greenland from 1981 to 2017

2020 ◽  
Vol 12 (5) ◽  
pp. 756
Author(s):  
Fei Peng ◽  
Haoran Zhou ◽  
Gong Chen ◽  
Qi Li ◽  
Yongxing Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Scale ◽  
Spatiotemporal Variation ◽  
Future Climate Change ◽  
Anthropogenic Factors ◽  
The Past

Land albedo is an essential variable in land surface energy balance and climate change. Within regional land, albedo has been altered in Greenland as ice melts and runoff increases in response to global warming against the period of the pre-industrial revolution. The assessment of spatiotemporal variation in albedo is a prerequisite for accurate prediction of ice sheet loss and future climate change, as well as crucial prior knowledge for improving current climate models. In our study, we employed the satellite data product from the global land surface satellite (GLASS) project to obtain the spatiotemporal variation of albedo from 1981 to 2017 using the non-parameter-based M-K (Mann-Kendall) method. It was found that the albedo generally showed a decreasing trend in the past 37 years (−0.013 ± 0.001 decade−1, p < 0.01); in particular, the albedo showed a significant increasing trend in the middle part of the study area but a decreasing trend in the coastal area. The interannual and seasonal variations of albedo showed strong spatial-temporal heterogeneity. Additionally, based on natural and anthropogenic factors, in order to further reveal the potential effects of spatiotemporal variation of albedo on the regional climate, we coupled climate model data with observed data documented by satellite and adopted a conceptual experiment for detections and attributions analysis. Our results showed that both the greenhouse gas forcing and aerosol forcing induced by anthropogenic activities in the past 37 decades were likely to be the main contributors (46.1%) to the decrease of albedo in Greenland. Here, we indicated that overall, Greenland might exhibit a local warming effect based on our study. Albedo–ice melting feedback is strongly associated with local temperature changes in Greenland. Therefore, this study provides a potential pathway to understanding climate change on a regional scale based on the coupled dataset.

scholarly journals Impacts of climate change on temperature, precipitation and hydrology in Finland – studies using bias corrected Regional Climate Model data

2015 ◽  
Vol 19 (7) ◽  
pp. 3217-3238 ◽  
Author(s):  
T. Olsson ◽  
J. Jakkila ◽  
N. Veijalainen ◽  
L. Backman ◽  
J. Kaurola ◽  
...  
Keyword(s):  
Climate Change ◽  
Seasonal Changes ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Catchment Scale ◽  
Temperature And Precipitation

Abstract. Assessment of climate change impacts on climate and hydrology on catchment scale requires reliable information about the average values and climate fluctuations of the past, present and future. Regional climate models (RCMs) used in impact studies often produce biased time series of meteorological variables. In this study bias correction (BC) of RCM temperature and precipitation for Finland is carried out using different versions of the distribution based scaling (DBS) method. The DBS-adjusted RCM data are used as input of a hydrological model to simulate changes in discharges of four study catchments in different parts of Finland. The annual mean discharges and seasonal variation simulated with the DBS-adjusted temperature and precipitation data are sufficiently close to observed discharges in the control period 1961–2000 and produce more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data. Furthermore, with most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data during 1961–2100. However, if the biases in the mean or the standard deviation of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections. The DBS method influences especially the projected seasonal changes in discharges and the use of uncorrected data can produce unrealistic seasonal discharges and changes. The projected changes in annual mean discharges are moderate or small, but seasonal distribution of discharges will change significantly.

scholarly journals Future climate change and it`s impact on precipitation and temperature in Ukraine

2017 ◽  
pp. 76-82
Author(s):  
V. Khokhlov ◽  
N. Yermolenko
Keyword(s):  
Climate Change ◽  
Climatic Change ◽  
Air Temperature ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Annual Precipitation ◽  
Future Climate Change ◽  
Temperature And Precipitation ◽  
Southern Ukraine

Global climate change has provoked an active development in modern methods relating to the prediction of spatiotemporal hydrometeorological fields. Numerical modeling of nearest-future climatic changes allows to generate strategies of development for different areas of economic activity. The paper aims to assess the expected air temperature and precipitation features in Ukraine considering different scenarios of climatic change. The modeling future changes of air temperature and precipitation were carried out using the A1B and A2 scenarios of climatic change. The outcomes of regional climate model ECHAM5 from ENSEMBLES Project were used as initial data. It was revealed that the air temperature will gradually increase in most of Ukrainian regions. Moreover highest air temperature will be recorded in Southern Ukraine during 2031-2050. The analysis of linear trends for 2031-2050 showed that the air temperature for the scenario A1B will exhibit a tendency to the decrease of temperature. However, the annually mean temperature in 2031-2050 for the ‘moderate’ scenario A1B will be higher than for the ‘hard’, in terms of greenhouse gases concentrations, scenario A2. The annual precipitation in Ukraine, both for the A1B and A2 scenario, will slightly increase toward the 2050 with the exception of Southern Ukraine. Also, the highest annual precipitation will be registered in the western part of Ukraine, and lowest – in the southern one. The paper can be expanded to the analysis of future dangerous weather phenomena depending on the changes of air temperature and precipitation.

scholarly journals A multi-model, multi-scenario, and multi-domain analysis of regional climate projections for the Mediterranean

2019 ◽  
Vol 19 (8) ◽  
pp. 2621-2635 ◽  
Author(s):  
George Zittis ◽  
Panos Hadjinicolaou ◽  
Marina Klangidou ◽  
Yiannis Proestos ◽  
Jos Lelieveld
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Mediterranean Region ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Signal ◽  
Climate Projections ◽  
Temperature And Precipitation ◽  
The Mediterranean ◽  
Projected Changes

AbstractObservation and model-based studies have identified the Mediterranean region as one of the most prominent climate change “hot-spots.” Parts of this distinctive region are included in several Coordinated Regional Downscaling Experiment (CORDEX) domains such as those for Europe, Africa, the Mediterranean, and the Middle East/North Africa. In this study, we compile and analyze monthly temperature and precipitation fields derived from regional climate model simulations performed over different CORDEX domains at a spatial resolution of 50 km. This unique multi-model, multi-scenario, and multi-domain “super-ensemble” is used to update projected changes for the Mediterranean region. The statistical robustness and significance of the climate change signal is assessed. By considering information from more than one CORDEX domains, our analysis addresses an additional type of uncertainty that is often neglected and is related to the positioning of the regional climate model domain. CORDEX simulations suggest a general warming by the end of the century (between 1 and 5 °C with respect to the 1986–2005 reference period), which is expected to be strongest during summer (up to 7 °C). A general drying (between 10 and 40%) is also inferred for the Mediterranean. However, the projected precipitation change signal is less significant and less robust. The CORDEX ensemble corroborates the fact that the Mediterranean is already entering the 1.5 °C climate warming era. It is expected to reach 2 °C warming well within two decades, unless strong greenhouse gas concentration reductions are implemented. The southern part of the Mediterranean is expected to be impacted most strongly since the CORDEX ensemble suggests substantial combined warming and drying, particularly for pathways RCP4.5 and RCP8.5.

scholarly journals 2 °C vs. High Warming: Transitions to Flood-Generating Mechanisms across Canada

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1494
Author(s):  
Bernardo Teufel ◽  
Laxmi Sushama
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Model ◽  
Regional Climate ◽  
Adaptation Measures ◽  
Relative Contribution ◽  
Late 21St Century ◽  
Transient Climate Change ◽  
Projected Changes ◽  
Change Mitigation

Fluvial flooding in Canada is often snowmelt-driven, thus occurs mostly in spring, and has caused billions of dollars in damage in the past decade alone. In a warmer climate, increasing rainfall and changing snowmelt rates could lead to significant shifts in flood-generating mechanisms. Here, projected changes to flood-generating mechanisms in terms of the relative contribution of snowmelt and rainfall are assessed across Canada, based on an ensemble of transient climate change simulations performed using a state-of-the-art regional climate model. Changes to flood-generating mechanisms are assessed for both a late 21st century, high warming (i.e., Representative Concentration Pathway 8.5) scenario, and in a 2 °C global warming context. Under 2 °C of global warming, the relative contribution of snowmelt and rainfall to streamflow peaks is projected to remain close to that of the current climate, despite slightly increased rainfall contribution. In contrast, a high warming scenario leads to widespread increases in rainfall contribution and the emergence of hotspots of change in currently snowmelt-dominated regions across Canada. In addition, several regions in southern Canada would be projected to become rainfall dominated. These contrasting projections highlight the importance of climate change mitigation, as remaining below the 2 °C global warming threshold can avoid large changes over most regions, implying a low likelihood that expensive flood adaptation measures would be necessary.

scholarly journals Projected Changes in Extreme Temperature and Precipitation Indices Over CORDEX-MENA Domain

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 622
Author(s):  
Tugba Ozturk ◽  
F. Sibel Saygili-Araci ◽  
M. Levent Kurnaz
Keyword(s):  
Regional Climate Model ◽  
Radiative Forcing ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Extreme ◽  
Pronounced Increase ◽  
Temperature And Precipitation ◽  
Projected Changes ◽  
Extreme Indices

In this study, projected changes in climate extreme indices defined by the Expert Team on Climate Change Detection and Indices were investigated over Middle East and North Africa. Changes in the daily maximum and minimum temperature- and precipitation- based extreme indices were analyzed for the end of the 21st century compared to the reference period 1971–2000 using regional climate model simulations. Regional climate model, RegCM4.4 was used to downscale two different global climate model outputs to 50 km resolution under RCP4.5 and RCP8.5 scenarios. Results generally indicate an intensification of temperature- and precipitation- based extreme indices with increasing radiative forcing. In particular, an increase in annual minimum of daily minimum temperatures is more pronounced over the northern part of Mediterranean Basin and tropics. High increase in warm nights and warm spell duration all over the region with a pronounced increase in tropics are projected for the period of 2071–2100 together with decrease or no change in cold extremes. According to the results, a decrease in total wet-day precipitation and increase in dry spells are expected for the end of the century.

Regional Climate Model Inter-Comparison for Antarctica within a Data Science Framework

2021 ◽  
Author(s):  
Jeremy Carter ◽  
Amber Leeson ◽  
Andrew Orr ◽  
Christoph Kittel ◽  
Melchior van Wessem
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate Change ◽  
Near Surface ◽  
Virtual Lab ◽  
Model Variability ◽  
The Antarctic

&lt;p&gt;Understanding the surface climatology of the Antarctic ice sheet is essential if we are to adequately predict its response to future climate change. This includes both primary impacts such as increased ice melting and secondary impacts such as ice shelf collapse events. Given its size, and inhospitable environment, weather stations on Antarctica are sparse. Thus, we rely on regional climate models to 1) develop our understanding of how the climate of Antarctica varies in both time and space and 2) provide data to use as context for remote sensing studies and forcing for dynamical process models. Given that there are a number of different regional climate models available that explicitly simulate Antarctic climate, understanding inter- and intra model variability is important.&lt;/p&gt;&lt;p&gt;Here, inter- and intra-model variability in Antarctic-wide regional climate model output is assessed for: snowfall; rainfall; snowmelt and near-surface air temperature within a cloud-based virtual lab framework. State-of-the-art regional climate model runs from the Antarctic-CORDEX project using the RACMO, MAR and MetUM models are used, together with the ERA5 and ERA-Interim reanalyses products. Multiple simulations using the same model and domain boundary but run at either different spatial resolutions or with different driving data are used. Traditional analysis techniques are exploited and the question of potential added value from more modern and involved methods such as the use of Gaussian Processes is investigated. The advantages of using a virtual lab in a cloud based environment for increasing transparency and reproducibility, are demonstrated, with a view to ultimately make the code and methods used widely available for other research groups.&lt;/p&gt;

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