scholarly journals Integration Of Convection Permitting Climate Models By Means Of Typical and Extreme Years in Building Energy Simulations In A Context Of Climate Change

Author(s):  
Delphine Ramon ◽  
Karen Allacker ◽  
Nicole P.M. van Lipzig
2011 ◽  
Vol 33 (4) ◽  
pp. 387-406 ◽  
Author(s):  
H Du ◽  
CP Underwood ◽  
JS Edge

In this study, test reference year (TRY) data for three UK cities are generated from the new UKCP09 climate change projections 1 for a variety of future time horizons and carbon emission scenario assumptions. The data are applied to the energy simulation of three commercial buildings and one house for the three city locations (London, Manchester and Edinburgh), three future time horizons in this century and three carbon emission scenarios. Results are compared with those generated using alternative TRYs from two other research groups who used UKCP09 1 as well as with the existing TRY data sets which form the CIBSE Future Weather Years 2 in order to produce robust results. Results of future simulations of peak summer operative temperatures, peak cooling demand, annual cooling energy, peak heating demand and annual heating energy are presented for the four building case studies benchmarked against control weather data for the period 1960–1989. The results show increasing internal operative temperatures (non-air-conditioned) and increasing air-conditioning demands (air-conditioned) throughout this century and though peak heating demands remain similar to control data, annual heating energy consumptions can be expected to fall sharply. Practical applications: Currently, practitioners can use Test Reference Years for use in building energy simulations. In 2009, the CIBSE released Future Weather Years, which go further by allowing practitioners to explore the thermal and comfort behaviour of buildings at future time horizons thus helping to ‘future proof’ a design. In 2009, the United Kingdom Climate Impacts Programme released a new generation of climate change scenario data (the UKCP09 climate change projections) using probabilistic methods. These are the most comprehensive data yet and provides a greater degree of detail than was available to generate the CIBSE Future Weather Years. It is therefore likely that the new data will gradually become the normal basis for investigating future building thermal and comfort response. In this study, a sample of TRY is generated from the UKCP09 data and applied to the simulation of a sample of ‘real’ buildings. The results are compared with both the existing CIBSE Future Weather Years as well as with Test Reference Years generated using UKCP09 by two other research groups. The results provide a robust way forward for simulating building thermal and comfort response using future weather data.


Buildings ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 166 ◽  
Author(s):  
Yassaghi ◽  
Hoque

It is becoming increasingly crucial to develop methods and strategies to assess building performance under the changing climate and to yield a more sustainable and resilient design. However, the outputs of climate models have a coarse spatial and temporal resolution and cannot be used directly in building energy simulation tools. This paper reviews methods to develop fine spatial and temporal weather files that incorporate climate emissions scenarios by means of downscaling. An overview of the climate change impact on building energy performance is given, and potential adaptation and mitigation factors in response to the changing climate in the building sector are presented. Also, methods to reflect, propagate, and partition main sources of uncertainties in both weather files and buildings are summarized, and a sample approach to propagate the uncertainties is demonstrated.


Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.


Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1819
Author(s):  
Eleni S. Bekri ◽  
Polychronis Economou ◽  
Panayotis C. Yannopoulos ◽  
Alexander C. Demetracopoulos

Freshwater resources are limited and seasonally and spatially unevenly distributed. Thus, in water resources management plans, storage reservoirs play a vital role in safeguarding drinking, irrigation, hydropower and livestock water supply. In the last decades, the dams’ negative effects, such as fragmentation of water flow and sediment transport, are considered in decision-making, for achieving an optimal balance between human needs and healthy riverine and coastal ecosystems. Currently, operation of existing reservoirs is challenged by increasing water demand, climate change effects and active storage reduction due to sediment deposition, jeopardizing their supply capacity. This paper proposes a methodological framework to reassess supply capacity and management resilience for an existing reservoir under these challenges. Future projections are derived by plausible climate scenarios and global climate models and by stochastic simulation of historic data. An alternative basic reservoir management scenario with a very low exceedance probability is derived. Excess water volumes are investigated under a probabilistic prism for enabling multiple-purpose water demands. Finally, this method is showcased to the Ladhon Reservoir (Greece). The probable total benefit from water allocated to the various water uses is estimated to assist decision makers in examining the tradeoffs between the probable additional benefit and risk of exceedance.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mulalo M. Muluvhahothe ◽  
Grant S. Joseph ◽  
Colleen L. Seymour ◽  
Thinandavha C. Munyai ◽  
Stefan H. Foord

AbstractHigh-altitude-adapted ectotherms can escape competition from dominant species by tolerating low temperatures at cooler elevations, but climate change is eroding such advantages. Studies evaluating broad-scale impacts of global change for high-altitude organisms often overlook the mitigating role of biotic factors. Yet, at fine spatial-scales, vegetation-associated microclimates provide refuges from climatic extremes. Using one of the largest standardised data sets collected to date, we tested how ant species composition and functional diversity (i.e., the range and value of species traits found within assemblages) respond to large-scale abiotic factors (altitude, aspect), and fine-scale factors (vegetation, soil structure) along an elevational gradient in tropical Africa. Altitude emerged as the principal factor explaining species composition. Analysis of nestedness and turnover components of beta diversity indicated that ant assemblages are specific to each elevation, so species are not filtered out but replaced with new species as elevation increases. Similarity of assemblages over time (assessed using beta decay) did not change significantly at low and mid elevations but declined at the highest elevations. Assemblages also differed between northern and southern mountain aspects, although at highest elevations, composition was restricted to a set of species found on both aspects. Functional diversity was not explained by large scale variables like elevation, but by factors associated with elevation that operate at fine scales (i.e., temperature and habitat structure). Our findings highlight the significance of fine-scale variables in predicting organisms’ responses to changing temperature, offering management possibilities that might dilute climate change impacts, and caution when predicting assemblage responses using climate models, alone.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.


Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 470
Author(s):  
Martha Charitonidou ◽  
Konstantinos Kougioumoutzis ◽  
John M. Halley

Climate change is regarded as one of the most important threats to plants. Already species around the globe are showing considerable latitudinal and altitudinal shifts. Helen’s bee orchid (Ophrys helenae), a Balkan endemic with a distribution center in northwestern Greece, is reported to be expanding east and southwards. Since this southeastern movement goes against the usual expectations, we investigated via Species Distribution Modelling, whether this pattern is consistent with projections based on the species’ response to climate change. We predicted the species’ future distribution based on three different climate models in two climate scenarios. We also explored the species’ potential distribution during the Last Interglacial and the Last Glacial Maximum. O. helenae is projected to shift mainly southeast and experience considerable area changes. The species is expected to become extinct in the core of its current distribution, but to establish a strong presence in the mid- and high-altitude areas of the Central Peloponnese, a region that could have provided shelter in previous climatic extremes.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.


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