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 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).

THE SCIENCE UNDERLYING THE ISSUE OF CLIMATE CHANGE AND PROSPECTS FOR ADAPTATION

2001 ◽  
Vol 41 (1) ◽  
pp. 689
Author(s):  
C.D. Mitchell ◽  
G.I. Pearman
Keyword(s):  
Climate Change ◽  
Risk Management ◽  
Greenhouse Gas ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Initial Response ◽  
Lower Atmosphere ◽  
Future Climate Change ◽  
Atmospheric Concentration

The prospect of global-scale changes in climate resulting from changes in atmospheric greenhouse gas concentrations has produced a complex set of public and private- sector responses. This paper reviews several elements of this issue that are likely to be most important to industry.Scientific research continues to provide evidence to suggest that global climate will change significantly over the coming decades due to increases in the atmospheric concentration of greenhouse gases. Nonetheless, there exists a debate over the difference between observations of temperature retrieved from satellite and temperature measurements taken from the surface. Recent research undertaken to inform the debate is discussed, with the conclusion that there are real differences in trend between the surface and the lower atmosphere that can be explained in physical terms. Attention is turning to developing an understanding as to why climate model results show apparently consistent trends between the surface and the lower atmosphere, in contrast to these observations.While such uncertainties in the underlying science have been used to question whether action on the greenhouse issues is necessary, the initial response, as evidenced by international negotiations, has been to start mitigating greenhouse gas emissions. Adaptation to future climate change has received less attention than mitigation. A number of reasons for this are discussed, including the fact that regional scenarios of climate change are uncertain.The principles of risk management may be one way to manage the uncertainties associated with projections of regional climate change. Although the application of risk management to the potential impacts of climate change requires further investigation, elements of such a framework are identified, and include:Identifying the critical climate-related thresholds that are important to industry and its operations (for example, a 1-in-100 year return tropical cyclone).Using this understanding to analyse, and where possible quantify, industry’s pre-existing or baseline adaptive state through the use of sensitivity surfaces and quantified thresholds (for example, were facilities designed for a 1-in-100 event or a 1-in-500 year event?)Establishing probabilistic statements or scenarios of climate that are relevant to industry practice (for example, risk of a storm surge may be more important to operations than elevated wind strength; if so, what is the probability that an event will exceed the design threshold during the lifetime of the facility?).Bringing information on existing adaptive mechanisms together with climate scenarios to produce a quantitative risk assessment.Deciding on risk treatment (additional adaptive measures).

scholarly journals A novel method for assessing climate change impacts in ecotron experiments

2020 ◽  
Vol 64 (10) ◽  
pp. 1709-1727
Author(s):  
Inne Vanderkelen ◽  
Jakob Zscheischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Air Temperature ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Forcing ◽  
Future Climate Change ◽  
Ecosystem Responses ◽  
Model Projection ◽  
Global Mean

Abstract Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future. Here, we present a new method for creating realistic climate forcing for manipulation experiments and apply it to the UHasselt Ecotron experiment. The new methodology uses data derived from the best available regional climate model projection and consists of generating climate forcing along a gradient representative of increasingly high global mean air temperature anomalies. We first identified the best-performing regional climate model simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European domain (EURO-CORDEX) ensemble based on two criteria: (i) highest skill compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. The time window is subsequently selected from the model projection for each ecotron unit based on the global mean air temperature of the driving global climate model. The ecotron units are forced with 3-hourly output from the projections of the 5-year period in which the global mean air temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The presented methodology can also be applied to other manipulation experiments, aiming at investigating ecosystem responses to realistic future climate change.

scholarly journals EFFECT OF THE REGIONAL CLIMATE CHANGE ON RUNOFF FROM THE LAKE ONEGO WATERSHED

2015 ◽  
Vol 2 ◽  
pp. 25
Author(s):  
L. E. Nazarova
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Air Temperature ◽  
Global Climate ◽  
Regional Climate ◽  
Hydrological Regime ◽  
Regional Climate Change ◽  
Mean Annual Precipitation ◽  
General Tendency ◽  
Temperature And Precipitation

As a result of the statistical analysis of the meteorological and water balance data for Onego Lake watershed over the period 1950-2000, noticeable changes were detected. It was found that time series of annual air temperature, precipitation and evapotranspiration over 50-year period contains positive linear trends, but no change in total streamflow to the lake has so far followed. Potential changes in the regional climate and hydrological regime for the period 2000-2050 were estimated using the results of numerical modeling with the ECHAM4/OPYC3 model for two scenarios of the global climate change. The estimation of these data shows that a general tendency to increase of annual air temperature and precipitation will remain in the new climate Mean annual precipitation will increase about 30-50 mm, mean average annual air temperature for the next 50-years period will rise from 1.6 up to 2.7-3.0 °C. Our estimation shows that for both scenarios all water balance parameters, excluding river runoff, will increase.

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 Assessing mean climate change signals in the global CORDEX-CORE ensemble

2020 ◽  
Author(s):  
Claas Teichmann ◽  
Daniela Jacob ◽  
Armelle Reca Remedio ◽  
Thomas Remke ◽  
Lars Buntemeyer ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Future Climate Change ◽  
Climate Services ◽  
Climate Change Information ◽  
Mean Climate

<p>The Coordinated Output for Regional Evaluations (CORE) simulation ensemble is an effort of the WCRP CORDEX community to provide high resolution regional climate change information for the major inhabited areas of the world and thus to generate the solid scientific basis for further research related to vulnerability, impact, adaptation and climate services (VIACS). This is especially important in those areas in which so far only few high-resolution simulations or only global comparatively coarse simulations were available. The driving simulations were selected to cover the spread of high, medium and low climate sensitivity at a global scale. Initially, the two RCMs REMO and RegCM4 were used to downscale these data global climate model output to a resolution of 0.22° (about 25km) while it is intended that the CORDEX CORE ensemble can then be extended by additional regional simulations to further increase the ensemble size and thus the representation of possible future climate change pathways.</p> <p>The aim of this study is to investigate and document the climate change information provided by the current CORDEX CORE ensemble with respect to mean climate change in different regions and in comparison to previously existing global climate information, especially those global climate simulations used as boundary forcing for CORDEX CORE, but also in comparison to the entire AR5-GCM ensemble. The analysis focuses on the representation of the AR5-GCM range of climate change signals by the CORDEX CORE ensemble with respect to mean temperature and precipitation changes and corresponding shifts in the annual cycles in the new AR6 IPCC physical reference regions. This also provides an indication for CORDEX CORE suitability for VIACS applications in each region.</p>

scholarly journals Early emergence in a butterfly causally linked to anthropogenic warming

2010 ◽  
Vol 6 (5) ◽  
pp. 674-677 ◽  
Author(s):  
Michael R. Kearney ◽  
Natalie J. Briscoe ◽  
David J. Karoly ◽  
Warren P. Porter ◽  
Melanie Norgate ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Change ◽  
Future Climate Change ◽  
Climate Data ◽  
Regional Warming

There is strong correlative evidence that human-induced climate warming is contributing to changes in the timing of natural events. Firm attribution, however, requires cause-and-effect links between observed climate change and altered phenology, together with statistical confidence that observed regional climate change is anthropogenic. We provide evidence for phenological shifts in the butterfly Heteronympha merope in response to regional warming in the southeast Australian city of Melbourne. The mean emergence date for H. merope has shifted −1.5 days per decade over a 65-year period with a concurrent increase in local air temperatures of approximately 0.16°C per decade. We used a physiologically based model of climatic influences on development, together with statistical analyses of climate data and global climate model projections, to attribute the response of H. merope to anthropogenic warming. Such mechanistic analyses of phenological responses to climate improve our ability to forecast future climate change impacts on biodiversity.

scholarly journals Current regional climate change studies in Hungary : a review

1999 ◽  
Vol 54 (3) ◽  
pp. 138-146 ◽  
Author(s):  
I. Matyasovszky ◽  
T. Weidinger ◽  
J. Bartholy ◽  
Z. Barcza
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Global Climate Change ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Future Climate Change ◽  
Local Effects ◽  
Temperature And Precipitation ◽  
Empirical Downscaling

Abstract. After focusing on the changes in Hungarian temperature and preeipitation during this Century, possible hydrological, agricultural and ecological consequences of a future climate change are described. These results have been obtained using a modified version of empirical downscaling techniques, developed to analyse the local effects of global climate change in a twofold concentration of atmospheric greenhouse gases scenario. In addition, regional changes in temperature and precipitation were examined with the help of the more specific stochastic downscaling method. The climate of Hungary has become warmer and drier over the last Century. It is to be expected that an increasing concentration of atmospheric greenhouse gases will enhance the tendency towards aridification.

scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

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