scholarly journals Urban Areas and Urban–Rural Contrasts under Climate Change: What Does the EURO-CORDEX Ensemble Tell Us?—Investigating near Surface Humidity in Berlin and Its Surroundings

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 730 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Relative Humidity ◽  
Urban Areas ◽  
Regional Climate ◽  
First Century ◽  
Wilcoxon Test ◽  
Climate Change Signal ◽  
Model Ensemble ◽  
Near Surface ◽  
Twenty First Century

Climate change will impact urban areas. Decision makers need useful climate information to adapt adequately. This research aims to improve understanding of changes in moisture and temperature projected under climate change in Berlin compared to its surroundings. Simulations for the Representative Concentration Pathway (RCP) 8.5 scenario from the European Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) 0.11° are analyzed, showing a difference in moisture and temperature variables between Berlin and its surroundings. The running mean over 30 years shows a divergence throughout the twenty-first century for relative humidity between Berlin and its surroundings. Under this scenario, Berlin gets drier over time. The Mann-Kendall test quantifies a robust decreasing trend in relative humidity for the multi-model ensemble throughout the twenty-first century. The Mann-Whitney-Wilcoxon test for relative humidity indicates a robust climate change signal in Berlin. It is drier and warmer in Berlin compared to its surroundings for all months with the largest difference existing in summer. Additionally, the change in humidity for the period 2070–2099 compared to 1971–2000 is larger in the summer months. This study presents results to better understand near surface moisture change and related variables under long-term climate change in urban areas compared to their rural surroundings using a regional climate multi-model ensemble.

A Hybrid Dynamical–Statistical Downscaling Technique. Part II: End-of-Century Warming Projections Predict a New Climate State in the Los Angeles Region

2015 ◽  
Vol 28 (12) ◽  
pp. 4618-4636 ◽  
Author(s):  
Fengpeng Sun ◽  
Daniel B. Walton ◽  
Alex Hall
Keyword(s):  
Climate Change ◽  
Los Angeles ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Regional Scale ◽  
Global Climate Models ◽  
First Century ◽  
Climate Change Signal ◽  
Uncertainty Estimates ◽  
Twenty First Century

Abstract Using the hybrid downscaling technique developed in part I of this study, temperature changes relative to a baseline period (1981–2000) in the greater Los Angeles region are downscaled for two future time slices: midcentury (2041–60) and end of century (2081–2100). Two representative concentration pathways (RCPs) are considered, corresponding to greenhouse gas emission reductions over coming decades (RCP2.6) and to continued twenty-first-century emissions increases (RCP8.5). All available global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are downscaled to provide likelihood and uncertainty estimates. By the end of century under RCP8.5, a distinctly new regional climate state emerges: average temperatures will almost certainly be outside the interannual variability range seen in the baseline. Except for the highest elevations and a narrow swath very near the coast, land locations will likely see 60–90 additional extremely hot days per year, effectively adding a new season of extreme heat. In mountainous areas, a majority of the many baseline days with freezing nighttime temperatures will most likely not occur. According to a similarity metric that measures daily temperature variability and the climate change signal, the RCP8.5 end-of-century climate will most likely be only about 50% similar to the baseline. For midcentury under RCP2.6 and RCP8.5 and end of century under RCP2.6, these same measures also indicate a detectable though less significant climatic shift. Therefore, while measures reducing global emissions would not prevent climate change at this regional scale in the coming decades, their impact would be dramatic by the end of the twenty-first century.

Synoptic-Statistical Approach to Regional Downscaling of IPCC Twenty-First-Century Climate Projections: Seasonal Rainfall over the Hawaiian Islands*

2009 ◽  
Vol 22 (16) ◽  
pp. 4261-4280 ◽  
Author(s):  
Oliver Timm ◽  
Henry F. Diaz
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Hawaiian Islands ◽  
Dry Season ◽  
First Century ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Wet Season ◽  
Near Surface ◽  
Twenty First Century

Abstract A linear statistical downscaling technique is applied to the projection of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) climate change scenarios onto Hawaiian rainfall for the late twenty-first century. Hawaii’s regional rainfall is largely controlled by the strength of the trade winds. During the winter months, disturbances in the westerlies can produce heavy rainfall throughout the islands. A diagnostic analysis of sea level pressure (SLP), near-surface winds, and rainfall measurements at 134 weather observing stations around the islands characterize the correlations between the circulation and rainfall during the nominal wet season (November–April) and dry season (May–October). A comparison of the base climate twentieth-century AR4 model simulations with reanalysis data for the period 1970–2000 is used to define objective selection criterion for the AR4 models. Six out of 21 available models were chosen for the statistical downscaling. These were chosen on the basis of their ability to more realistically simulate the modern large-scale circulation fields in the Hawaiian Islands region. For the AR4 A1B emission scenario, the six analyzed models show important changes in the wind fields around Hawaii by the late twenty-first century. Two models clearly indicate opposite signs in the anomalies. One model projects 20%–30% rainfall increase over the islands; the other model suggests a rainfall decrease of about 10%–20% during the wet season. It is concluded from the six-model ensemble that the most likely scenario for Hawaii is a 5%–10% reduction of the wet-season precipitation and a 5% increase during the dry season, as a result of changes in the wind field. The authors discuss the sources of uncertainties in the projected rainfall changes and consider future improvements of the statistical downscaling work and implications for dynamical downscaling methods.

scholarly journals Changes in the Risk of Cool-Season Tornadoes over Southern Australia due to Model Projections of Anthropogenic Warming

2010 ◽  
Vol 23 (9) ◽  
pp. 2440-2449 ◽  
Author(s):  
B. Timbal ◽  
R. Kounkou ◽  
G. A. Mills
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Weather Prediction ◽  
First Century ◽  
Climate Projections ◽  
Cool Season ◽  
Near Surface ◽  
Impact Of Climate Change ◽  
Twenty First Century ◽  
The Impact

Abstract Anthropogenic climate change is likely to be felt most acutely through changes in the frequency of extreme meteorological events. However, quantifying the impact of climate change on these events is a challenge because the core of the climate change science relies on general circulation models to detail future climate projections, and many of these extreme events occur on small scales that are not resolved by climate models. This note describes an attempt to infer the impact of climate change on one particular type of extreme meteorological event—the cool-season tornadoes of southern Australia. The Australian Bureau of Meteorology predicts threat areas for cool-season tornadoes using fine-resolution numerical weather prediction model output to define areas where the buoyancy of a near-surface air parcel and the vertical wind shear each exceed specified thresholds. The diagnostic has been successfully adapted to coarser-resolution climate models and applied to simulations of the current climate, as well as future projections of the climate over southern Australia. Simulations of the late twentieth century are used to validate the models’ ability to reproduce the climatology of the risk of cool-season tornado formation by comparing these with similar computations based on historical reanalyses. Model biases are overcome by setting model specific thresholds to define the cool-season tornado risk. The diagnostic, applied to simulations of the twenty-first century, is then used to quantify the impact of the projected climate change on cool-season tornado risk. The sign of the response is consistent across all models: a decrease of the risk of formation during the twenty-first century is projected, driven by the thermodynamical response. The thermal response is modulated by the dynamical response, which varies between models. The projected decrease in tornadoes risk during the cool season is consistent with the projection of positive southern annular mode trends and the known influence of this mode of variability on interannual to intraseasonal time-scale variations in cool-season tornado occurrence.

scholarly journals Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

2021 ◽  
Author(s):  
Hyun Min Sung ◽  
Jisun Kim ◽  
Sungbo Shim ◽  
Jeong-byn Seo ◽  
Sang-Hoon Kwon ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Scientific Information ◽  
Earth System Model ◽  
First Century ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Future Projections ◽  
Twenty First Century

AbstractThe National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

scholarly journals Climate pattern-scaling set for an ensemble of 22 GCMs – adding uncertainty to the IMOGEN version 2.0 impact system

2018 ◽  
Vol 11 (2) ◽  
pp. 541-560 ◽  
Author(s):  
Przemyslaw Zelazowski ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Nathalie Schaller
Keyword(s):  
Climate Change ◽  
Relative Humidity ◽  
Land Surface ◽  
Land Surface Model ◽  
Individual Performance ◽  
Balance Model ◽  
Surface Model ◽  
Near Surface ◽  
Global Circulation Models ◽  
Version 2.0

Abstract. Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25±5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44±4.37 and 14.98±4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.

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