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.

A Package of New Universal Non-Iterative Parametrizations for Stable Surface Layer Transfer Coefficients of Momentum, Heat and Moisture in Numerical Earth System Models

2021 ◽  
Author(s):  
Vladimir Gryanik ◽  
Christof Luepkes ◽  
Andrey Grachev ◽  
Dmitry Sidorenko
Keyword(s):  
Climate Models ◽  
Similarity Theory ◽  
Weather Prediction ◽  
Climate Projections ◽  
Transfer Coefficients ◽  
Near Surface ◽  
Stability Functions ◽  
Stable Surface Layer ◽  
Heat And Moisture ◽  
The Impact

<p><span>Results of weather forecast, present-day climate simulations and future climate projections depend among other factors on the interaction between the atmosphere and the underlying sea-ice, the land and the ocean. In numerical weather prediction and climate models some of these interactions are accounted for by transport coefficients describing turbulent exchange of momentum, heat and moisture. Currently used transfer coefficients have, however, large uncertainties in flow regimes being typical for cold nights and seasons, but especially in the polar regions. Furthermore, their determination is numerically complex. It is obvious that progress could be achieved when the transfer coefficients would be given by simple mathematical formulae in frames of an economic computational scheme. Such a new universal, so-called non-iterative parametrization scheme is derived for a package of transfer coefficients.</span></p><p><span>The derivation is based on the Monin-Obukhov similarity theory, which is over the years well accepted in the scientific community. The newly derived non-iterative scheme provides a basis for a cheap systematic study of the impact of near-surface turbulence and of the related transports of momentum, heat and moisture in NWP and climate models. </span></p><p><span>We show that often used transfer coefficients like those of Louis et al. (1982) or of Cheng and Brutsaert (2005) can be applied at large stability only with some caution, keeping in mind that at large stability they significantly overestimate the transfer coefficient compared with most comprehensive measurements. The latter are best reproduced by Gryanik et al. (2020) functions, which are part of the package. We show that the new scheme is flexible, thus, new stability functions can be added to the package, if required. </span></p><p> </p><p> <span>Gryanik, V.M., Lüpkes, C., Grachev, A., Sidorenko, D. (2020) New Modified and Extended Stability Functions for the Stable Boundary Layer based on SHEBA and Parametrizations of Bulk Transfer Coefficients for Climate Models, J. Atmos. Sci., 77, 2687-2716</span></p><p><br><br></p>

scholarly journals Estimating the potential impact of climate change on sunflower yield in the Konya province of Turkey

2021 ◽  
pp. 1-13
Author(s):  
Hudaverdi Gurkan ◽  
Vakhtang Shelia ◽  
Nilgun Bayraktar ◽  
Y. Ersoy Yildirim ◽  
Nebi Yesilekin ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Model Performance ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Adaptation To Climate Change ◽  
Impact Of Climate Change ◽  
The Impact

Abstract The impact of climate change on agricultural productivity is difficult to assess. However, determining the possible effects of climate change is an absolute necessity for planning by decision-makers. The aim of the study was the evaluation of the CSM-CROPGRO-Sunflower model of DSSAT4.7 and the assessment of impact of climate change on sunflower yield under future climate projections. For this purpose, a 2-year sunflower field experiment was conducted under semi-arid conditions in the Konya province of Turkey. Rainfed and irrigated treatments were used for model analysis. For the assessment of impact of climate change, three global climate models and two representative concentration pathways, i.e. 4.5 and 8.5 were selected. The evaluation of the model showed that the model was able to simulate yield reasonably well, with normalized root mean square error of 1.3% for the irrigated treatment and 17.7% for the rainfed treatment, a d-index of 0.98 and a modelling efficiency of 0.93 for the overall model performance. For the climate change scenarios, the model predicted that yield will decrease in a range of 2.9–39.6% under rainfed conditions and will increase in a range of 7.4–38.5% under irrigated conditions. Results suggest that temperature increases due to climate change will cause a shortening of plant growth cycles. Projection results also confirmed that increasing temperatures due to climate change will cause an increase in sunflower water requirements in the future. Thus, the results reveal the necessity to apply adequate water management strategies for adaptation to climate change for sunflower production.

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 Consensus on Twenty-First-Century Rainfall Projections in Climate Models More Widespread than Previously Thought

2012 ◽  
Vol 25 (11) ◽  
pp. 3792-3809 ◽  
Author(s):  
Scott B. Power ◽  
François Delage ◽  
Robert Colman ◽  
Aurel Moise
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Statistical Significance ◽  
First Century ◽  
Intergovernmental Panel ◽  
Ipcc Report ◽  
Projected Change ◽  
Twenty First Century ◽  
The Impact ◽  
Precipitation Projections

Under global warming, increases in precipitation are expected at high latitudes and near major tropical convergence zones in some seasons, while decreases are expected in many subtropical and midlatitude areas in between. In many other areas there is no consensus among models on the sign of the projected change. This is often assumed to indicate that precipitation projections in these regions are highly uncertain. Here, twenty-first century precipitation projections under the Special Report on Emissions Scenarios (SRES) A1B scenario using 24 World Climate Research Programme (WCRP)/Coupled Model Intercomparison Project phase 3 (CMIP3) climate models are examined. In areas with no consensus on the sign of projected change there are extensive subregions where the projected change is “very likely” (i.e., probability > 0.90) to be small (relative to, e.g., the size of interannual variability during the late twentieth century) or zero. The statistical significance of and interrelationships between methods used to identify model consensus on projected change in the 2007 Intergovernmental Panel on Climate Change (IPCC) report are examined, and the impact of interdependency among model projections on statistical significance is investigated. Interdependency among projections is shown to be much weaker than interdependency among simulations of climatology. The results show that there is more widespread consistency among the model projections than one might infer from the 2007 IPCC Fourth Assessment report. This discovery highlights the broader need to identify regions, variables, and phenomena that are expected to be little affected by anthropogenic climate change and to communicate this information to the wider community. This is especially important for projections of climate for the next 1–3 decades.

scholarly journals Climate Change Impacts on Reservoir Inflow in the Prairie Pothole Region: A Watershed Model Analysis

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 271 ◽  
Author(s):  
Ameer Muhammad ◽  
Grey R. Evenson ◽  
Fisaha Unduche ◽  
Tricia A. Stadnyk
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Assessment Tool ◽  
Prairie Pothole Region ◽  
Swat Model ◽  
Climate Projections ◽  
Prairie Pothole ◽  
Time Step ◽  
Impact Of Climate Change ◽  
The Impact

The Prairie Pothole Region (PPR) is known for its hydrologically complex landscape with a large number of pothole wetlands. However, most watershed-scale hydrologic models that are applied in this region are incapable of representing the dynamic nature of contributing area and fill-spill processes affected by pothole wetlands. The inability to simulate these processes represents a critical limitation for operators and flood forecasters and may hinder the management of large reservoirs. We used a modified version of the soil water assessment tool (SWAT) model capable of simulating the dynamics of variable contributing areas and fill-spill processes to assess the impact of climate change on upstream inflows into the Shellmouth reservoir (also called Lake of the Prairie), which is an important reservoir built to provide multiple purposes, including flood and drought mitigation. We calibrated our modified SWAT model at a daily time step using SUFI-2 algorithm within SWAT-CUP for the period 1991–2000 and validated for 2005–2014, which gave acceptable performance statistics for both the calibration (KGE = 0.70, PBIAS = −13.5) and validation (KGE = 0.70, PBIAS = 21.5) periods. We then forced the calibrated model with future climate projections using representative concentration pathways (RCPs; 4.5, 8.5) for the near (2011–2040) and middle futures (2041–2070) of multiple regional climate models (RCMs). Our modeling results suggest that climate change will lead to a two-fold increase in winter streamflow, a slight increase in summer flow, and decrease spring peak flows into the Shellmouth reservoir. Investigating the impact of climate change on the operation of the Shellmouth reservoir is critically important because climate change could present significant challenges to the operation and management of the reservoir.

Structural safety and design under climate change

2019 ◽  
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Structural Reliability ◽  
Greenhouse Gas Emission ◽  
Extreme Value ◽  
Structural Safety ◽  
Climate Projections ◽  
Climate Conditions ◽  
Impact Of Climate Change ◽  
The Impact

<p>The impact of climate change on climatic actions could significantly affect, in the mid-term future, the design of new structures as well as the reliability of existing ones designed in accordance to the provisions of present and past codes. Indeed, current climatic loads are defined under the assumption of stationary climate conditions but climate is not stationary and the current accelerated rate of changes imposes to consider its effects.</p><p>Increase of greenhouse gas emissions generally induces a global increase of the average temperature, but at local scale, the consequences of this phenomenon could be much more complex and even apparently not coherent with the global trend of main climatic parameters, like for example, temperature, rainfalls, snowfalls and wind velocity.</p><p>In the paper, a general methodology is presented, aiming to evaluate the impact of climate change on structural design, as the result of variations of characteristic values of the most relevant climatic actions over time. The proposed procedure is based on the analysis of an ensemble of climate projections provided according a medium and a high greenhouse gas emission scenario. Factor of change for extreme value distribution’s parameters and return values are thus estimated in subsequent time windows providing guidance for adaptation of the current definition of structural loads.</p><p>The methodology is illustrated together with the outcomes obtained for snow, wind and thermal actions in Italy. Finally, starting from the estimated changes in extreme value parameters, the influence on the long-term structural reliability can be investigated comparing the resulting time dependent reliability with the reference reliability levels adopted in modern Structural codes.</p>

scholarly journals An Assessment of Recent and Future Temperature Change over the Sichuan Basin, China, Using CMIP5 Climate Models

2017 ◽  
Vol 30 (17) ◽  
pp. 6701-6722 ◽  
Author(s):  
Daniel Bannister ◽  
Michael Herzog ◽  
Hans-F. Graf ◽  
J. Scott Hosking ◽  
C. Alan Short
Keyword(s):  
Climate Change ◽  
Sichuan Basin ◽  
Climate Models ◽  
Distribution Functions ◽  
Future Climate ◽  
First Century ◽  
Future Climate Change ◽  
Change Scenario ◽  
The Sichuan Basin ◽  
Twenty First Century

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

scholarly journals Impact of climate change on hydrological conditions in a tropical West African catchment using an ensemble of climate simulations

2017 ◽  
Vol 21 (4) ◽  
pp. 2143-2161 ◽  
Author(s):  
Yacouba Yira ◽  
Bernd Diekkrüger ◽  
Gero Steup ◽  
Aymar Yaovi Bossa
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
West African ◽  
Climate Projections ◽  
Impact Of Climate Change ◽  
Budget Analysis ◽  
High Uncertainty

Abstract. This study evaluates climate change impacts on water resources using an ensemble of six regional climate models (RCMs)–global climate models (GCMs) in the Dano catchment (Burkina Faso). The applied climate datasets were performed in the framework of the COordinated Regional climate Downscaling Experiment (CORDEX-Africa) project.After evaluation of the historical runs of the climate models' ensemble, a statistical bias correction (empirical quantile mapping) was applied to daily precipitation. Temperature and bias corrected precipitation data from the ensemble of RCMs–GCMs was then used as input for the Water flow and balance Simulation Model (WaSiM) to simulate water balance components.The mean hydrological and climate variables for two periods (1971–2000 and 2021–2050) were compared to assess the potential impact of climate change on water resources up to the middle of the 21st century under two greenhouse gas concentration scenarios, the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results indicate (i) a clear signal of temperature increase of about 0.1 to 2.6 °C for all members of the RCM–GCM ensemble; (ii) high uncertainty about how the catchment precipitation will evolve over the period 2021–2050; (iii) the applied bias correction method only affected the magnitude of the climate change signal; (iv) individual climate models results lead to opposite discharge change signals; and (v) the results for the RCM–GCM ensemble are too uncertain to give any clear direction for future hydrological development. Therefore, potential increase and decrease in future discharge have to be considered in climate change adaptation strategies in the catchment. The results further underline on the one hand the need for a larger ensemble of projections to properly estimate the impacts of climate change on water resources in the catchment and on the other hand the high uncertainty associated with climate projections for the West African region. A water-energy budget analysis provides further insight into the behavior of the catchment.

Twenty-First-Century Climate Change Hot Spots in the Light of a Weakening Sun

2020 ◽  
Vol 33 (9) ◽  
pp. 3431-3447
Author(s):  
Tobias Spiegl ◽  
Ulrike Langematz
Keyword(s):  
Climate Change ◽  
Hot Spots ◽  
Climate Model ◽  
Hot Spot ◽  
Ghg Emissions ◽  
Arctic Sea Ice ◽  
First Century ◽  
Vulnerability To Climate Change ◽  
Twenty First Century ◽  
The Impact

AbstractSatellite measurements over the last three decades show a gradual decrease in solar output, which can be indicative as a precursor to a modern grand solar minimum (GSM). Using a chemistry–climate model, this study investigates the potential of two GSM scenarios with different magnitude to counteract the climate change by projected anthropogenic greenhouse gas (GHG) emissions through the twenty-first century. To identify regions showing enhanced vulnerability to climate change (hot spots) and to estimate their response to a possible modern GSM, a multidimensional metric is applied that accounts for—in addition to changes in mean quantities—seasonal changes in the variability and occurrence of extreme events. We find that a future GSM in the middle of the twenty-first century would temporarily mitigate the global mean impact of anthropogenic climate change by 10%–23% depending on the GSM scenario. A future GSM would, however, not be able to stop anthropogenic global warming. For the GHG-only scenario, our hot-spot analysis suggests that the midlatitudes show a response to rising GHGs below global average, while in the tropics, climate change hot spots with more frequent extreme hot seasons will develop during the twenty-first century. A GSM would reduce the climate change warming in all regions. The GHG-induced warming in Arctic winter would be dampened in a GSM due to the impact of reduced solar irradiance on Arctic sea ice. However, even an extreme GSM could only mitigate a fraction of the tropical hot-spot pattern (up to 24%) in the long term.

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