scholarly journals Changes in Thornthwaite Moisture Index and Reactive Soil Movements under Current and Future Climate Scenarios—A Case Study

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6760
Author(s):  
Md Rajibul Karim ◽  
Md Mizanur Rahman ◽  
Khoi Nguyen ◽  
Donald Cameron ◽  
Asif Iqbal ◽  
...  
Keyword(s):  
Climate Change ◽  
Expansive Soils ◽  
South Australia ◽  
Future Climate ◽  
Ground Movement ◽  
Weather Data ◽  
Emission Scenarios ◽  
Moisture Index ◽  
Premature Failure ◽  
Soil Behaviour

Expansive soils go through significant volume changes due to seasonal moisture variations resulting in ground movements. The ground movement related problems are likely to worsen in the future due to climate change. It is important to understand and incorporate likely future changes in design to ensure the resilience of structures built on such soils. However, there has been a limited amount of work quantifying the effect of climate change on expansive soils movement and related behaviour of structures. The Thornthwaite Moisture Index (TMI) is one of the commonly used climate classifiers in quantifying the effect of atmospheric boundary on soil behaviour. Using the long-term weather data and predicted future changes under different emission scenarios, a series of TMI maps are developed for South Australia. Potential changes in ground movement are then estimated for a selected area using a simplified methodology where the effect of future climate is captured through changes in TMI. Results indicate that South Australia is likely to face a significant reduction in TMI under all emission scenarios considered in this study. The changes in TMI will lead to a considerable increase in potential ground movement which will influence the behaviour of structures built on them and in some areas may lead to premature failure if not considered in the design.

scholarly journals An evaluation of the effect of future climate on runoff in the Dongjiang River basin, South China

2015 ◽  
Vol 368 ◽  
pp. 257-262
Author(s):  
K. Lin ◽  
W. Zhai ◽  
S. Huang ◽  
Z. Liu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Annual Runoff ◽  
Future Climate ◽  
Weather Data ◽  
Future Climate Change ◽  
Dongjiang River ◽  
The Future ◽  
The Impact

Abstract. The impact of future climate change on the runoff for the Dongjiang River basin, South China, has been investigated with the Soil and Water Assessment Tool (SWAT). First, the SWAT model was applied in the three sub-basins of the Dongjiang River basin, and calibrated for the period of 1970–1975, and validated for the period of 1976–1985. Then the hydrological response under climate change and land use scenario in the next 40 years (2011–2050) was studied. The future weather data was generated by using the weather generators of SWAT, based on the trend of the observed data series (1966–2005). The results showed that under the future climate change and LUCC scenario, the annual runoff of the three sub-basins all decreased. Its impacts on annual runoff were –6.87%, –6.54%, and –18.16% for the Shuntian, Lantang, and Yuecheng sub-basins respectively, compared with the baseline period 1966–2005. The results of this study could be a reference for regional water resources management since Dongjiang River provides crucial water supplies to Guangdong Province and the District of Hong Kong in China.

scholarly journals Climate change impact – residential unit

2019 ◽  
Vol 279 ◽  
pp. 03007
Author(s):  
Ján Hollý ◽  
Adela Palková
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Weather Data ◽  
Emission Scenarios ◽  
Climate Data ◽  
Climate Conditions ◽  
Residential Unit ◽  
Data Application ◽  
Change Impact ◽  
Selection Of

The issue of climate change is undeniably demonstrating its presence. Consequently, there is a rising need to be prepared for upcoming threats by any means possible. One of the precautions includes obtaining the information characterizing the expected impact of global warming. This will allow authorities and other stakeholders to act accordingly in time. The article presents the assessment of the extent of impact of energy-related construction solutions in dwelling type unit situated in Central Europe region under the 21st century climate conditions. The findings represent eventual demands of energy for cooling and heating and its prospective savings. This is conducted by consecutively and automatically changing the parameters in individual simulation runs. As a basis for simulations, regionally scaled weather data of three different climate areas are used. These data are based on the emission scenarios by IPCC and are reaching to the year 2100. The selection of assessed parameters and climate data application are briefly explained in the article. The results of simulations are evaluated and recommended solutions are stated in regard to the specific energy-related construction changes. The aim is to successfully mitigate and adapt to the climate change phenomenon.

Projecting future vegetation change for northeast China using CMIP6

2020 ◽  
Author(s):  
Wei Yuan ◽  
Shuang-ye Wu ◽  
Shugui Hou
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Management Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Vegetation Changes ◽  
Emission Scenarios ◽  
Climate Data ◽  
Climate Conditions ◽  
Temperature And Precipitation

<p>This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87<sup>o</sup>C in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585 respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability in the future.</p>

Impact of climate change on harvest security and biomass yield of two timothy ley harvesting systems in Norway

2013 ◽  
Vol 152 (2) ◽  
pp. 205-216 ◽  
Author(s):  
T. PERSSON ◽  
M. HÖGLIND
Keyword(s):  
Climate Change ◽  
Biomass Yield ◽  
Phleum Pratense ◽  
Future Climate ◽  
Weather Data ◽  
Future Climate Change ◽  
Daily Weather ◽  
Daily Weather Data ◽  
Dry Spell ◽  
Harvesting Regime

SUMMARYPredicted future climate changes in northern Europe include increased air temperature and altered precipitation patterns. There is a lack of knowledge about potential climate change effects on the biomass yield and security of agricultural crops. The present study determined the potential impact of future climate change on the yield and harvest security of timothy (Phleum pratense L.). Harvest security was assessed using data on accumulated precipitation and the length of dry spell period within the 7 days after cutting. Timothy production as a function of weather, soil and management practices was simulated using the LINGRA model for the periods 1961–90, 2046–65 and 2080–99, and the locations Apelsvoll, Ås, Sola, Tromsø and Værnes in Norway and harvest systems with 600 and 800 °C days between cuts. One hundred years of daily weather data were generated with the LARS-WG tool, using future daily weather data sets based on 12 Global Climate Models. Total seasonal biomass yield varied between 690 g dry matter (DM)/m2 for the 800 °C days harvesting regime in the period 1961–90 at Tromsø and 1548 g DM/m2 for the same harvesting regime in the period 2046–65 at Sola. In general, the biomass was higher in the two future periods than in 1961–90 across locations and harvesting regimes, mainly owing to more cuts per season. Accumulated precipitation after cutting varied between 12·2 mm after the first cut for the 600 °C days harvesting regime in the period 1961–90 at Værnes and 42·5 mm after the fourth cut in the 800 °C days harvesting regime in the period 2080–99 at Sola. The longest duration of dry spell 7 days after pre-planned harvest varied between 1·8 days after the fourth cut at Sola in the 600 °C days harvesting regime for the period 2080–99, and 3·9 days after the first cut at Ås in the 800 °C days harvesting regime for the period 2046–65. Potential consequences of these results are discussed.

scholarly journals Coupled application of R and WetSpa models for assessment of climate change impact on streamflow of Werie Catchment, Tigray, Ethiopia

2020 ◽  
Author(s):  
Selam Kidanemariam ◽  
Haddush Goitom ◽  
Yigzaw Desta
Keyword(s):  
Climate Change ◽  
Baseline Period ◽  
Future Climate ◽  
Calibration Data ◽  
Climate Variables ◽  
Emission Scenarios ◽  
Climate Data ◽  
Validation Data ◽  
Data Set ◽  
Rcp 8.5

Abstract This research assesses the streamflow response of Werie River to climate change. Baseline (1980–2009) climate data of precipitation, maximum and minimum temperature were analyzed using delta based statistical downscaling approach in R software packages to predict future 90 years (2010–2099) periods under two emission scenarios of Representative Concentration Pathways (RCP) 4.5 and RCP 8.5, indicating medium and extremely high emission scenarios respectively. Generated future climate variables indicate Werie will experience a significant increase in precipitation, and maximum and minimum air temperature for both RCPs. Further, Water and Energy Transfer between Soil, Plants, and Atmosphere (WetSpa) was applied to assess the water balance of Werie River. The WetSpa model reproduced the streamflow well with performance statistics values of R2 = 0.84 and 0.85, Nash–Sutcliffe efficiency = 0.72 and 0.72, and model bias = –0.14 and –0.15 for the calibration data set of 1999–2010 and validation data of 2011–2014 respectively. Finally, by taking the downscaled future climate variables as input, WetSpa future prediction shows that there will an increase in the Werie catchment mean annual streamflow up to 29.6% for RCP 4.5 and 35.6% for RCP 8.5 compared to the baseline period.

SPAGETTA Weather Generator Linked with Climate Models May Produce Weather Series for Future Climate 

2021 ◽  
Author(s):  
Martin Dubrovsky ◽  
Ondrej Lhotka ◽  
Jiri Miksovsky ◽  
Petr Stepanek ◽  
Jan Meitner
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
Climate Change Scenario ◽  
Emission Scenario ◽  
Future Climate ◽  
Change Scenario ◽  
Emission Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

<p>Stochastic weather generators (WGs) are tools for producing weather series, which are statistically similar to the real world weather series. The synthetic series may represent both present and changed (not only the future) climate. In the latter case, WG parameters derived from the observed weather series are modified with climate change scenario, which is typically based on RCM or GCM simulations. As the GCM/RCM simulations are very demanding on computer resources, the numbers of simulations made for individual possible emission scenarios are limited, especially for some (mostly the less probable ones) emission scenarios (e.g. RCP 2.6). Still, many climate change impact studies try to give projections of the CC impacts assuming uncertainties coming from all possible sources, including the modeling uncertainty and  uncertainties in emissions & climate sensitivity. To allow generation of weather series fitting the projection of any GCM forced by any emission scenario, we use a pattern scaling approach, in which the standardized climate change scenario (consisting of changes in climatic characteristic related to 1ºC change in global mean temperature) derived from a given GCM is multiplied by a change in global mean temperature (dTg) projected (for a selected emission scenario and climate sensitivity) by a simple climate model MAGICC.</p><p>In our contribution, we will demonstrate the use of the generator (using SPAGETTA WG, which is our multi-site multi-variate parametric daily WG) in probabilistic projection of future changes in selected climatic characteristics of temperature (T) and precipitation (P); we will focus on spatial hot/cold/dry/wet/hot-dry/hot-wet/cold-dry/cold-wet spells). Standardized climate change scenarios will be derived from multiple GCMs (taken from CMIP5 database) and scaled by dTg projected by MAGICC. Effects of the three above-named sources of uncertainty, as well as the effects of changes in individual statistical characteristics (the means & the site-specific variabilities & the characteristics of the temporal and spatial variability of both T and P) will be assessed.</p><p>Acknowledgements: Projects GRIMASA (Czech Science Foundation, project no. 18-15958S) and SustES (European Structural and Investment Funds, project no. CZ.02.1.01/0.0/0.0/16_019/0000797).</p>

scholarly journals Analysis of Climate Change and Extreme Climatic Events in the Lake Victoria Region of Tanzania

2020 ◽  
Vol 2 ◽  
Author(s):  
Philbert Modest Luhunga ◽  
Alexander Elias Songoro
Keyword(s):  
Climate Change ◽  
Lake Victoria ◽  
Regional Climate ◽  
Future Climate ◽  
Emission Scenarios ◽  
Climate Condition ◽  
Lake Victoria Region ◽  
Rcp 8.5 ◽  
Maximum Temperatures ◽  
Future Climate Condition

The understanding of climate change impacts and the associated climate extreme events at regional and local scales is of critical importance for planning and development of feasible adaptation strategies. In this paper, we present an analysis of climate change and extreme climate events in the Lake Victoria region of Tanzania, focusing on the Kagera and Geita regions. We use daily simulated climate variables (rainfall and minimum and maximum temperatures) from the Coordinated Regional Climate Downscaling Experiment Program Regional Climate Models (CORDEX_RCMs) for the analysis. Extreme climate event, rainfall, and minimum and maximum temperatures time series during historical (1971–2000) climate condition are compared to future climate projection (2011–2100) under two Representative Concentration Pathway (RCP): RCP 4.5 and RCP 8.5 emission scenarios. The existence, magnitude, and statistical significance of potential trends in climate data time series are estimated using the Mann–Kendall (MK) non-parametric test and Theil-SEN slope estimator methods. Results show that during historical (1971–2000) climate, the Lake Victoria region of Tanzania experienced a statistically significant increasing trend in temperature. The annual minimum and maximum temperatures in the Kagera and Geita regions have increased by 0.54–0.69°C, and 0.51–0.69°C, respectively. The numbers of warm days (TX90p) and warm nights (TN90p) during the historical climate have increased, while the numbers of cold days (TX10p) and cold nights (TN10p) have decreased significantly. However, in future climate condition (2011–2100) under both RCP 4.5 and RCP 8.5 emission scenarios, the Lake Victoria region is likely to experience increased temperatures and rainfall. The frequency of cold events (cold days and cold nights) is likely to decrease, while the frequency of warm events (warm days and warm nights) is likely to increase significantly. The number of consecutive wet days, the intensity of very wet days, and the number of extreme wet days are likely to increase. These results indicate that in future climate condition, socioeconomic livelihoods of people in the Kagera and Geita regions are likely to experience significant challenges from climate-related stresses. It is, therefore, recommended that appropriate planning and effective adaptation policies are in place for disaster risk prevention.

scholarly journals Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Fabiani Denise Bender ◽  
Paulo Cesar Sentelhas
Keyword(s):  
Climate Change ◽  
Solar Radiation ◽  
Climate Models ◽  
Global Climate Models ◽  
Future Climate ◽  
Weather Data ◽  
Data Series ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Project Climate Change

The quantification of climate change impacts on several human activities depends on reliable weather data series, without gaps and long enough to build up future climate. Based on that, this study aimed to evaluate the performance of temperature-based models for estimating global solar radiation and gridded databases (AgCFSR, AgMERRA, NASA/POWER, and XAVIER) as alternative ways for filling gaps in historical weather series (1980–2009) in Brazil and to project climate change scenarios based on measured and gridded weather data. Projections for mid- and end-of-century periods (2040–2069 and 2070–2099), using seven global climate models from CMIP5 under intermediate (RCP4.5) and high (RCP8.5) emission scenarios, were performed. The Bristow–Campbell model was the one that best estimated solar radiation, whereas the XAVIER gridded database was the closest to observed weather data. Future climate projections, under RCP4.5 and RCP8.5 scenarios, as expected, showed warmer conditions for all scenarios over Brazil. On the contrary, rainfall projections are more uncertain. Despite that, the rainfall amounts will be reduced in the North-Northeast region and increased in Southern Brazil. No significant differences between projections using the observed and XAVIER gridded database were observed; therefore, such a database showed to be reliable for both to fill gaps and to generate climate change scenarios.

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