Hadley Centre Coupled Model Version Research Articles

Evaluation of statistical downscaling model's performance in projecting future climate change scenarios

Abstract Statistical downscaling (SD) is preferable to dynamic downscaling to derive local-scale climate change information from large-scale datasets. Many statistical downscaling models are available these days, but comparison of their performance is still inadequately addressed for choosing a reliable SD model. Thus, it is desirable to compare the performance of SD models to ensure their adaptability in future climate studies. In this study, a statistical downscaling model (SDSM) or multi-linear regression and the Least Square Support Vector Machine (LS-SVM) were used to do downscaling and compare the results with those obtained from general circulation model (GCM) for identifying the best SD model for the Indira Sagar Canal Command area located in Madhya Pradesh, India. The GCM, Hadley Centre Coupled Model version 3 (HadCM3), was utilized to extract and downscale precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) for 1961–2001 and then for 2001–2099. Before future projections, both SD models were initially calibrated (1961–1990) and validated (1991–2001) to evaluate their performance for precipitation and temperature variables at all gauge stations, namely Barwani, East Nimar, and West Nimar. Results showed that the precipitation trend was under-predicted owing to large errors in downscaling, while temperature was over-predicted by SD models.

Daily maximum runoff frequency analysis under non-stationary conditions due to climate change in the future period: Case study Ghareh Sou basin

Abstract The frequency analysis of the maximum instantaneous flood is mostly based on the stationary assumption. The purpose of the present study is to compare the results of maximum instantaneous flood analysis under stationary and non-stationary conditions in Ghareh Sou basin, and also answer the question as to whether there is a difference between estimating the return period of maximum instantaneous flood in stationary and non-stationary conditions. First, the values of the temperature, wind speed, and rainfall of the study area under the two scenarios of Representative Concentration Pathway (RCP) 2.6 and 8.5 of the Hadley Centre coupled Model, version3 (HadCM3) model were downscaled. In the following, the Variable Infiltration Capacity (VIC) model was utilized to generate daily runoff. For converting the daily discharge to the maximum instantaneous flood, four methods of Fuller, Sangal, Fill Steiner, and artificial neural network (ANN) were compared. Finally, the maximum instantaneous floods of the future period were introduced to the Non-stationary Extreme Value Analysis (NEVA) software. Based on the results obtained from the research, the lack of considering the non-stationary conditions in the flood frequency analysis can result in underestimating the maximum instantaneous flood, which can also provide more risks for the related hydraulic structures.

Downscaling diurnal temperature over west and southwest Iran : A comparison of statistical downscaling approaches

This study aimed to forecast temperature variations in the western and southwestern part of Iran using a general circulation model and artificial neural networks (ANN). The data included mean diurnal temperatures from synoptic stations, National Centers for Environmental Prediction/ National Center for Atmospheric Research (NCEP/NCAR) reanalysis data, and outputs of a third-generation global climate model, the Hadley Centre Coupled Model version 3 (HadCM3), under A2 and B2 scenarios for the baseline period (1961–1990). The data of the first (1961–1975) and second 15 years (1976–1990) of the baseline period were used for model calibration and validation, respectively. Both models, however, produced reliable estimates at the plain stations with neither outperforming the other due to their negligible errors. However, the neural network results of mountain synoptic stations showed a lower error rate than the statistical downscaling model (SDSM) outputs. All in all, we can say that there was a larger amount of error in the outputs of the atmospheric general circulation models (AGCMs) in the mountainous regions. According to the outputs of the neural network and the AGCMs, temperatures at the studied stations were on the rise. In fact, this increase was more noticeable at the plain stations. This can be attributed to their proximity to the sea, to their latitude, and to the more intensive industrial activities (especially, extraction of petroleum and production of petroleum products) taking place near the plain stations.

Sea ice feedbacks influence the isotopic signature of Greenland ice sheet elevation changes: last interglacial HadCM3 simulations

Abstract. Changes in the Greenland ice sheet (GIS) affect global sea level. Greenland stable water isotope (δ18O) records from ice cores offer information on past changes in the surface of the GIS. Here, we use the isotope-enabled Hadley Centre Coupled Model version 3 (HadCM3) climate model to simulate a set of last interglacial (LIG) idealised GIS surface elevation change scenarios focusing on GIS ice core sites. We investigate how δ18O depends on the magnitude and sign of GIS elevation change and evaluate how the response is altered by sea ice changes. We find that modifying GIS elevation induces changes in Northern Hemisphere atmospheric circulation, sea ice and precipitation patterns. These climate feedbacks lead to ice-core-averaged isotopic lapse rates of 0.49 ‰ (100 m)−1 for the lowered GIS states and 0.29 ‰ (100 m)−1 for the enlarged GIS states. This is lower than the spatially derived Greenland lapse rates of 0.62–0.72 ‰ (100 m)−1. These results thus suggest non-linearities in the isotope–elevation relationship and have consequences for the interpretation of past elevation and climate changes across Greenland. In particular, our results suggest that winter sea ice changes may significantly influence isotope–elevation gradients: winter sea ice effect can decrease (increase) modelled core-averaged isotopic lapse rate values by about −19 % (and +28 %) for the lowered (enlarged) GIS states, respectively. The largest influence of sea ice on δ18O changes is found in coastal regions like the Camp Century site.

Coupled impacts of sea ice variability and North Pacific atmospheric circulation on Holocene hydroclimate in Arctic Alaska

Arctic Alaska lies at a climatological crossroads between the Arctic and North Pacific Oceans. The modern hydroclimate of the region is responding to rapidly diminishing sea ice, driven in part by changes in heat flux from the North Pacific. Paleoclimate reconstructions have improved our knowledge of Alaska's hydroclimate, but no studies have examined Holocene sea ice, moisture, and ocean-atmosphere circulation in Arctic Alaska, limiting our understanding of the relationship between these phenomena in the past. Here we present a sedimentary diatom assemblage and diatom isotope dataset from Schrader Pond, located ∼80 km from the Arctic Ocean, which we interpret alongside synthesized regional records of Holocene hydroclimate and sea ice reduction scenarios modeled by the Hadley Centre Coupled Model Version 3 (HadCM3). The paleodata synthesis and model simulations suggest the Early and Middle Holocene in Arctic Alaska were characterized by less sea ice, a greater contribution of isotopically heavy Arctic-derived moisture, and wetter climate. In the Late Holocene, sea ice expanded and regional climate became drier. This climatic transition is coincident with a documented shift in North Pacific circulation involving the Aleutian Low at ∼4 ka, suggesting a Holocene teleconnection between the North Pacific and Arctic. The HadCM3 simulations reveal that reduced sea ice leads to a strengthened Aleutian Low shifted west, potentially increasing transport of warm North Pacific water to the Arctic through the Bering Strait. Our findings demonstrate the interconnectedness of the Arctic and North Pacific on multimillennial timescales, and are consistent with future projections of less sea ice and more precipitation in Arctic Alaska.

Crop pattern planning and irrigation water allocation compatible with climate change using a coupled network flow programming-heuristic optimization model

ABSTRACT Sustainable agricultural production has encountered difficulties such as water scarcity, improper use of available water resources and climate change in arid countries like Iran. Simulation-optimization approaches are helpful tools for crop pattern planning and irrigation water allocation to ensure maximum net benefit is gained from the system. In this paper, optimum cultivation area and allocation of irrigation water in conditions compatible with climate change are obtained for the Borkhar plain in Iran. To achieve this, the network flow programming-based MODSIM, as a water allocation simulation model, is coupled with the grey wolf optimization (GWO) algorithm to obtain the optimum irrigation amounts and cultivation areas in the plain under two conditions: status quo, and with climate change-affected streamflows. The Hadley Centre coupled Model version 3 (HadCM3) and the second-generation Canadian Earth System Model (CanESM2) are used to generate the climatic parameters in the study area. The Identification of unit Hydrographs and Component flows from Rainfall, Evapotranspiration and Streamflow (IHACRES) rainfall–runoff model is applied to calculate the coefficients of variation for the Zayandehroud River streamflows, as the surface water resource for irrigation of the plain. Results indicate that the agricultural net benefit gained from the plain will decrease by 1.5% in the A2 emissions scenario, and by 3.5%, 8% and 17.5% in the three representative concentration pathway (RCP) scenarios in the optimum states obtained by the GWO-MODSIM model. Moreover, the cultivation areas are decreased in the climate change scenarios. Therefore, appropriate management policies should be adopted for adaptation to the likely future situation.

Simulating the climate response to atmospheric oxygen variability in the Phanerozoic: a focus on the Holocene, Cretaceous and Permian

Abstract. The amount of dioxygen (O2) in the atmosphere may have varied from as little as 5 % to as much as 35 % during the Phanerozoic eon (54 Ma–present). These changes in the amount of O2 are large enough to have led to changes in atmospheric mass, which may alter the radiative budget of the atmosphere, leading to this mechanism being invoked to explain discrepancies between climate model simulations and proxy reconstructions of past climates. Here, we present the first fully 3-D numerical model simulations to investigate the climate impacts of changes in O2 under different climate states using the coupled atmosphere–ocean Hadley Centre Global Environmental Model version 3 (HadGEM3-AO) and Hadley Centre Coupled Model version 3 (HadCM3-BL) models. We show that simulations with an increase in O2 content result in increased global-mean surface air temperature under conditions of a pre-industrial Holocene climate state, in agreement with idealised 1-D and 2-D modelling studies. We demonstrate the mechanism behind the warming is complex and involves a trade-off between a number of factors. Increasing atmospheric O2 leads to a reduction in incident shortwave radiation at the Earth's surface due to Rayleigh scattering, a cooling effect. However, there is a competing warming effect due to an increase in the pressure broadening of greenhouse gas absorption lines and dynamical feedbacks, which alter the meridional heat transport of the ocean, warming polar regions and cooling tropical regions. Case studies from past climates are investigated using HadCM3-BL and show that, in the warmest climate states in the Maastrichtian (72.1–66.0 Ma), increasing oxygen may lead to a temperature decrease, as the equilibrium climate sensitivity is lower. For the Asselian (298.9–295.0 Ma), increasing oxygen content leads to a warmer global-mean surface temperature and reduced carbon storage on land, suggesting that high oxygen content may have been a contributing factor in preventing a “Snowball Earth” during this period of the early Permian. These climate model simulations reconcile the surface temperature response to oxygen content changes across the hierarchy of model complexity and highlight the broad range of Earth system feedbacks that need to be accounted for when considering the climate response to changes in atmospheric oxygen content.

Effect of a global warming model on the energetic performance of a typical solar photovoltaic system

This study provides insight into how the energetic performance of a typical photovoltaic solar system (PV) will change in a warmer world with increased levels of greenhouse gases. It was considered a photovoltaic system disconnected from the distribution grid, similar to those available in the market. The methodology covers systems without batteries and with the use of batteries with finite electric charge storage. The climatic change is accessed from a scenario predicted from the HadCM3(Hadley Centre Coupled Model, version 3) major global circulation model reported in the International Panel for Climatic Change (IPCC). The outputs from a future weather scenario were used as inputs for the long-term performance simulations for the typical PV solar system. The results encompass predictions for the decades of 2020, 2050 and 2080, and are presented in terms of monthly average daily energy output, fraction of the load supplied for a system with and without battery, and energetic efficiency. Seven cities in different climatic zones were evaluated. The cities and regions presented distinct behaviors, such that in some cases the PV system generated less energy, while in others an increase in photovoltaic generation was observed. However, regarding the energetic efficiency of the system, all scenarios presented increasing losses throughout the decades.

Assessment of Streamflow Variability with Upgraded HydroClimatic Conceptual Streamflow Model

HydroClimatic Conceptual Streamflow (HCCS) model is a conceptual model for prediction and future assessment of daily streamflow using climate inputs and time-varying watershed characteristics. However, without denying its useful salient features in a changing climate, applicability of the HCCS model is limited to the basins without any major man-made river structure(s), such as reservoirs. Considering this, the originally proposed HCCS model is upgraded (hereinafter ‘upgraded HCCS model’) to accommodate the human-intervened release from such structures within the basin, if any, and to include routing component through the river channels without using rigorous information from the river channels. The upgraded HCCS model is expected to be useful to assess (i) the effect on the streamflow at downstream due to upstream dam release, and (ii) the long-term modification required in the reservoir/dam operation under a changing climate for ensuring water-availability in downstream. The upgraded HCCS model is applied to three river basins for assessing the future streamflow characteristics. Two of these basins have one each and the third basin has two major man-made river structures within them. Hadley Centre Coupled Model, version 3 (HadCM3) simulated climate variables till 2035 are used as inputs for demonstration. The model predicts an increase in streamflow in future. In general, the upgraded HCCS model can be applied to any tropical river basin having major man-made river structure(s) for daily streamflow prediction as well as assessment of future streamflow variation considering the changing climate and watershed characteristics.

Pliocene and Eocene provide best analogs for near-future climates

As the world warms due to rising greenhouse gas concentrations, the Earth system moves toward climate states without societal precedent, challenging adaptation. Past Earth system states offer possible model systems for the warming world of the coming decades. These include the climate states of the Early Eocene (ca. 50 Ma), the Mid-Pliocene (3.3-3.0 Ma), the Last Interglacial (129-116 ka), the Mid-Holocene (6 ka), preindustrial (ca. 1850 CE), and the 20th century. Here, we quantitatively assess the similarity of future projected climate states to these six geohistorical benchmarks using simulations from the Hadley Centre Coupled Model Version 3 (HadCM3), the Goddard Institute for Space Studies Model E2-R (GISS), and the Community Climate System Model, Versions 3 and 4 (CCSM) Earth system models. Under the Representative Concentration Pathway 8.5 (RCP8.5) emission scenario, by 2030 CE, future climates most closely resemble Mid-Pliocene climates, and by 2150 CE, they most closely resemble Eocene climates. Under RCP4.5, climate stabilizes at Pliocene-like conditions by 2040 CE. Pliocene-like and Eocene-like climates emerge first in continental interiors and then expand outward. Geologically novel climates are uncommon in RCP4.5 (<1%) but reach 8.7% of the globe under RCP8.5, characterized by high temperatures and precipitation. Hence, RCP4.5 is roughly equivalent to stabilizing at Pliocene-like climates, while unmitigated emission trajectories, such as RCP8.5, are similar to reversing millions of years of long-term cooling on the scale of a few human generations. Both the emergence of geologically novel climates and the rapid reversion to Eocene-like climates may be outside the range of evolutionary adaptive capacity.

Influence of Low-frequency Solar Forcing on the East Asian Winter Monsoon Based on HadCM3 and Observations

In this study, we investigate the influence of low-frequency solar forcing on the East Asian winter monsoon (EAWM) by analyzing a four-member ensemble of 600-year simulations performed with HadCM3 (Hadley Centre Coupled Model, version 3). We find that the EAWM is strengthened when total solar irradiance (TSI) increases on the multidecadal time scale. The model results indicate that positive TSI anomalies can result in the weakening of Atlantic meridional overturning circulation, causing negative sea surface temperature (SST) anomalies in the North Atlantic. Especially for the subtropical North Atlantic, the negative SST anomalies can excite an anomalous Rossby wave train that moves from the subtropical North Atlantic to the Greenland Sea and finally to Siberia. In this process, the positive sea-ice feedback over the Greenland Sea further enhances the Rossby wave. The wave train can reach the Siberian region, and strengthen the Siberian high. As a result, low-level East Asian winter circulation is strengthened and the surface air temperature in East Asia decreases. Overall, when solar forcing is stronger on the multidecadal time scale, the EAWM is typically stronger than normal. Finally, a similar linkage can be observed between the EAWM and solar forcing during the period 1850–1970.

Acceleration of Northern Ice Sheet Melt Induces AMOC Slowdown and Northern Cooling in Simulations of the Early Last Deglaciation

AbstractThe cause of a rapid change in Atlantic Ocean circulation and northern cooling at the onset of Heinrich Stadial 1 ~18.5 ka is unclear. Previous studies have simulated the event using ice sheet and/or iceberg meltwater forcing, but these idealized freshwater fluxes have been unrealistically large. Here we use a different approach, driving a high‐resolution drainage network model with a recent time‐resolved global paleo‐ice sheet reconstruction to generate a realistic meltwater forcing. We input this flux to the Hadley Centre Coupled Model version 3 (HadCM3) climate model without adjusting the timing or amplitude and find that an acceleration in northern ice sheet melting (up to ~7.5 m/kyr global mean sea level rise equivalent) triggers a 20% reduction in the Atlantic Meridional Overturning Circulation. The simulated pattern of ocean circulation and climate change matches an array of paleoclimate and ocean circulation reconstructions for the onset of Heinrich Stadial 1, in terms of both rates and magnitude of change. This is achieved with a meltwater flux that matches constraints on sea level changes and ice sheet evolution around 19–18 ka. Since the rates of melting are similar to those projected for Greenland by 2200, constraining the melt rates and magnitude of climate change during Heinrich Stadial 1 would provide an important test of climate model sensitivity to future ice sheet melt.

Development of a time‐varying downscaling model considering non‐stationarity using a Bayesian approach

Stationarity in the relationship between causal variables and target variables is the fundamental assumption of statistical downscaling models. However, we hypothesize that this assumption may not be valid in a changing climate. This study develops a downscaling technique in which the relationship between causal and target variables is considered to be time‐varying rather than static. The proposed time‐varying downscaling model (TVDM) is utilized to downscale monthly precipitation over India to 0.25 × 0.25° gridded scale using the large‐scale outputs from multiple general circulation models (GCMs), namely the Hadley Centre Coupled Model version 3 (HadCM3), coupled Hadley Centre Global Environmental Model version 2‐Earth System model (HadGEM2‐ES) and Canadian Earth System Model version 2 (CanESM2). Observed precipitation data are obtained from the India Meteorological Department (IMD), Pune. For future projection, the temporal evolution of each of the TVDM parameters is investigated using its deterministic (trend and periodicity) and stochastic components. TVDM is found to outperform the most commonly used statistical downscaling model (SDSM) and regional climate model (RCM) output at all the locations. The Regional Climate Model version 4 (RegCM4) precipitation data (RCM outputs) are obtained from the Coordinated Regional Climate Downscaling Experiment (CORDEX) data portal supplied by Indian Institute of Tropical Meteorology (IITM), Pune. The proposed model (TVDM) differs from the existing stationarity assumption‐based approaches in updating the relationship between causal and target variables over time. It is understood that parameter uncertainty is the major issue in consideration of non‐stationarity. Still, the TVDM is found to be very useful in the context of climate change due to its time‐varying component.

Modeling Climate Change Projections for Ferozpur Sub-catchment of Jhelum Sub-basin of Kashmir Valley

Aims: The study aimed at modeling the climate change projections for Ferozpur subcatchment of Jhelum sub-basin of Kashmir Valley using the SDSM model.&#x0D; Study Design: The study was carried out in three different time slices viz Baseline (1985-2015), Mid-century (2030-2059) and End-century (2070-2099).&#x0D; Place and Duration of Study: Division of Agricultural Engineering, SKUAST-K, Shalimar between August 2015 and July 2016.&#x0D; Methodology: Statistical downscaling model (SDSM) was applied in downscaling weather files (Tmax, Tminand precipitation). The study includes the calibration of the SDSM model by using Observed daily climate data (Tmax, Tmin and precipitation) of thirty one years and large scale atmospheric variables encompassing National Centers for Environmental Prediction (NCEP) reanalysis data, the validation of the model, and the outputs of downscaled scenario A2 of the Global Climate Model (GCM) data of Hadley Centre Coupled Model, Version 3 (HadCM3) model for the future. Daily Climate (Tmax, Tmin and precipitation) scenarios were generated from 1961 to 2099 under A2 defined by Intergovernmental Panel on Climate Change (IPCC).&#x0D; Results: The results showed that temperature and precipitation would increase by 0.29°C, 255.38 mm (30.97%) in MC (Mid-century) (2030-2059); and 0.67oC and 233.28 mm (28.29%) during EC (End-century) (2070-2099), respectively.&#x0D; Conclusion: The climate projections for 21st century under A2 scenario indicated that both mean annual temperature and precipitation are showing an increasing trend.

Modeling impacts of climate change and human activities on groundwater resources using MODFLOW

Abstract This paper analyzes the impacts of climate change and human pressures on Yazd-Ardakan aquifer using the Hadley Centre Coupled Model, version 3 (HADCM3) circulation Model and A2 emission scenario. Water levels in the study aquifer were simulated using three-dimensional finite-difference groundwater model (MODFLOW 2000) with GMS 8.3 as pre- and postprocessing software. Input for groundwater recharge time series under the climate change scenarios were derived using a regression equation based on the cumulative deviation from mean rainfall using MATLAB. Human pressures on the aquifer were modeled through climate change impacts on water requirements of cultivated areas. Three scenarios were simulated to represent the effects of climate change and human pressures on aquifer storage and hydraulic head. Climate change and human pressures (scenario 1) will reduce aquifer storage and result in decreasing hydraulic head by −0.56 m year−1. Reduction in pumping water under scenario 2 (irrigation system modification) and scenario 3 (irrigation system modification and cropping patterns) will result in groundwater level fluctuation of about −0.32 and 0.08 m year−1, respectively. Scenario 3 is capable of restoring and protecting the groundwater resources in Yazd-Ardakan aquifer. The results of this study are useful to obtain sustainable groundwater management in Yazd-Ardakan aquifer.

Spatiotemporal reference evapotranspiration changes in humid and semi-arid regions of Iran: past trends and future projections

This study was undertaken to investigate the reference evapotranspiration (ET0) changes in semi-arid and humid regions of Iran during the past (1966–2010) and future (2011–2099). For detecting possible trend in ET0 over 1966–2010, the Mann–Kendall trend test was employed. The outputs of Hadley Centre coupled model version 3 (HadCM3) and the third generation couple global climate model (CGCM3) under A2, B2, and A1B emission scenarios were also used to simulate the future ET0 changes by statistical downscaling model (SDSM). The results indicated upward trends in annual ET0 during 1966–2010 in the most sites. Furthermore, the significant increasing ET0 trends were identified for 54.5, 18.2, 27.3, 22.7, and 36.3% of studied locations during winter, spring, summer, autumn, and entire year, respectively. Positive trends in ET0 were mostly found in northeast, west, and northwest Iran, and insignificant downward ET0 trends were primarily detected in southwestern and southern stations in 1966–2010. The ET0 changes were attributed to wind speed changes in semi-arid regions and mean temperature changes in humid areas in the past period. An increase in ET0 was projected under all scenarios due mainly to temperature rise and declined relative humidity in the investigated regions from 2011 to 2100. Averaged over all stations, the lowest and highest ET0 increment were, respectively, modeled for autumn and summer using CGCM3 outputs and winter and autumn using HadCM3 outputs. Given significant ET0 increase over the twenty-first century, appropriate adaptive measures are required to reduce negative impacts of climate change on water resources and agricultural productions.

Prediction of climate change in Brunei Darussalam using statistical downscaling model

Climate is changing and evidence suggests that the impact of climate change would influence our everyday lives, including agriculture, built environment, energy management, food security and water resources. Brunei Darussalam located within the heart of Borneo will be affected both in terms of precipitation and temperature. Therefore, it is crucial to comprehend and assess how important climate indicators like temperature and precipitation are expected to vary in the future in order to minimise its impact. This study assesses the application of a statistical downscaling model (SDSM) for downscaling General Circulation Model (GCM) results for maximum and minimum temperatures along with precipitation in Brunei Darussalam. It investigates future climate changes based on numerous scenarios using Hadley Centre Coupled Model, version 3 (HadCM3), Canadian Earth System Model (CanESM2) and third-generation Coupled Global Climate Model (CGCM3) outputs. The SDSM outputs were improved with the implementation of bias correction and also using a monthly sub-model instead of an annual sub-model. The outcomes of this assessment show that monthly sub-model performed better than the annual sub-model. This study indicates a satisfactory applicability for generation of maximum temperatures, minimum temperatures and precipitation for future periods of 2017–2046 and 2047–2076. All considered models and the scenarios were consistent in predicting increasing trend of maximum temperature, increasing trend of minimum temperature and decreasing trend of precipitations. Maximum overall trend of Tmax was also observed for CanESM2 with Representative Concentration Pathways (RCP) 8.5 scenario. The increasing trend is 0.014 °C per year. Accordingly, by 2076, the highest prediction of average maximum temperatures is that it will increase by 1.4 °C. The same model predicts an increasing trend of Tmin of 0.004 °C per year, while the highest trend is seen under CGCM3-A2 scenario which is 0.009 °C per year. The highest change predicted for the Tmin is therefore 0.9 °C by 2076. The precipitation showed a maximum trend of decrease of 12.7 mm year. It is also seen in the output using CanESM2 data that precipitation will be more chaotic with some reaching 4800 mm per year and also producing low rainfall about 1800 mm per year. All GCMs considered are consistent in predicting it is very likely that Brunei is expected to experience more warming as well as less frequent precipitation events but with a possibility of intensified and drastically high rainfalls in the future.

Changes in future climate indices using Statistical Downscaling Model in the upper Baro basin of Ethiopia

Climate indices are the diagnostic tools used to define the state of climate system. The main objective of this study was to investigate the climate index change in future time periods in the upper Baro basin of Ethiopia. The daily precipitation and maximum and minimum temperature data were downscaled using Statistical Downscaling Model (SDSM). The precipitation and temperature data were estimated according to UK Hadley Centre Coupled Model version 3 (HadCM3) global circulation model with medium-high (A2) and medium-low emission (B2) scenarios in three future time interval periods. The De Martonne Aridity Index and Pinna Combinative Index change of the future time periods centered at 2020s, 2050s, and 2080s was computed. The analysis was based on percentage change between the baseline and three future time periods. The monthly De Martonne Aridity Index result showed that there are months in the dry season classified as semi-dry with value of less than 20 and the land needs irrigation in these months. The Pinna Combinative Index value also showed the same trend like that of the De Martonne Aridity Index and a high correlation coefficient was noticed, verifying similar trend of the two indices for the three future time period changes. Overall, humidity is expected to decrease in most of the months in the three future time periods for both A2 and B2 emission scenarios because of the increment of temperature in the future.

Prediction of the impacts of climate change on energy consumption for a medium-size office building with two climate models

The paper presents an energy simulation-based study to investigate the impacts of climate change on energy consumptions of an office building located in five different cities, United States. Annual energy consumption of a medium-size office building was predicted by building energy simulation software—EnergyPlus using TMY3 weather data and future climate data. In this study, we have used two sets of further climate data with different climate models including (1) Hadley Centre Coupled Model, version 3 (HadCM3), and (2) NCAR Community Earth System Model version 1 (CESM1) with the Community Atmosphere Model version 5 (CAM5). A morphing method was applied to downscale the monthly weather forecast to hourly forecast for use in building energy simulation for the two General Circulation Models (GCMs): HadCM3 and CESM1. Using the generated future weather files, HVAC operation related mitigation measures including adjustment of thermostat setpoints, reduced HVAC operation hours, reduced VAV box minimum flow setting, and mixed-mode ventilation were simulated to compare with ASHRAE Standard 90.1 baseline simulated using TMY3 weather data. Simulation results on predicted whole building, heating and cooling energy consumptions were examined. The paper highlighted the importance of efficiently operating mechanical systems in buildings to ensure a more sustainable future.

Evaluation of Climate Change Impacts on Run-Off in the Gidabo River Basin: Southern Ethiopia

Climate change meaningfully affects the runoff, flooding and the riverfow in Gidabo river basin. Thus, this research study deals with the climate change impacts on the runoff in the Gidabo River basin. Statistical Downscaling Model version 5.1 has been used to downscale the daily precipitation and temperature in the Gelana river basin. The output of HadCM3 coupled atmosphere-ocean GCM model for A2a and B2a scenarios obtained from the Hadley Centre Coupled Model version 3 were used to show future climate change. Climate change scenarios for precipitation and temperature were developed for three future periods: 2011–2040 (2050s), 2041–2070 (2050s) and 2071–2099 (2080s). The meteorological variables were used as input to the SWAT hydrological model which was calibrated (R2=0.77) and validated (R2=0.81) with meteorological and hydrological historical data from the year 1980-2006. The results obtained from this study indicate that there is significant variation in the monthly, seasonal and annual runoff. The climate change impacts might causes increases in average monthly runoff in the 2020’s, 2050’s and 2080’s for both A2a and B2a scenario. The result of this study is based on a single climate model (HadCM3) output under A2a and B2a scenarios. Therefore, multiple climate models and scenario which may provide a detail climate change impact studies for comparison on hydrology in the Gidabo river basin.