Hadley Centre Global Environmental Model Research Articles

Predicting facial eczema risks in a changing New Zealand climate

Facial eczema is a major concern for New Zealand farmers due to its economic impact and animal welfare implications. The disease occurs when animals ingest sporidesmin, a mycotoxin produced by spores of the fungus Pseudopithomyces chartarum. Spore production is related to weather conditions; thus the incidence and severity of facial eczema varies between years, with thedisease commonly occurring from late summer through autumn in the North Island. We developed a simple model to estimate climatic suitability for P. chartarum sporulation and ran it using climate data for 2008-2021 to compare its estimates with spore counts from the same years. Model climatic suitability estimates had significant linear correlations with an index of exposure to spores derived from spore counts at both national and local scales. Model results were also consistent with a documented outbreak of facial eczema. Using predicted future climate data from the Hadley Centre Global Environment Model version 2 and two emissionsscenarios, the model suggested climatic suitability for P. chartarum sporulation will increase with time in many New Zealand regions, particularly in the southern North Island and eastern parts of the South Island. However, it could remain relatively static in some other areas, thus the degree of change in climatic suitability for P. chartarum sporulation is predicted to vary between New Zealand regions.

Future Climate Prediction Based on Support Vector Machine Optimization in Tianjin, China

Climate is closely related to human life, food security and ecosystems. Forecasting future climate provides important information for agricultural production, water resources management and so on. In this paper, historical climate data from 1962–2001 was used at three sites in Tianjin Baodi, Tianjin and Tanggu districts as baseline and the model parameters were calibrated by the Long Ashton Research Station Weather Generator (LARS-WG). 2m-temperatures in 2011–2020 were verified under two scenarios, representative concentration pathway (RCP) 4.5 and RCP8.5 in different atmospheric circulation models with optimal minimum 2m-temperatures at the three sites. From 2031–2050, Tianjin will be using more moderate minimum 2m-temperatures in future simulations. Support vector machines (SVM) were used to optimize the simulated data to obtain more accurate future maximum and minimum 2m-temperatures for the three sites. The results showed that the determinant coefficient of LARS-WG simulation was 0.8 and SVM optimized determinant coefficient was 0.9 which greatly improved the prediction accuracy. The minimum and maximum future 2m-temperatures optimized under European Community Earth System Model (EC-EARTH) were relatively low and the same future 2m-temperatures optimized under Hadley Centre Global Environment Model Earth System (Had-GEM2-ES4) were high especially in the RCP8.5 scenario which simulated 2051–2070 climate. The SVM optimization showed that the maximum and minimum 2m-temperatures were in general agreement with the original simulation values.

MaxEnt modeling for predicting the potential distribution of Lebrunia bushaie Staner (Clusiaceae) under different climate change scenarios in Democratic Republic of Congo

Lebrunia bushaie Staner is an endangered medicinal plant that is endemic in the Democratic Republic of Congo (DRC). In this study, its current and future suitable distribution habitats were assessed using two Global Circulation Models (GCMs) HadGEM3-GC3.1-LL” (Third Hadley Centre Global Environment Model in the Global Coupled Configuration 3.1) and MIROC6 (Model for Interdisciplinary Research on Climate) under twoShared Socioeconomic Pathways (ssp) scenarios, ssp126 and ssp245 at the horizon 2050. Potential habitat predictions for L. bushaie were performed using MaxEnt software. The area under the curve (AUC˃ 0.90) revealed a high level of prediction for the current and future scenarios. Seasonal Temperature (Bio4), and isothermality (Bio3) were the variables with the greatest influence on the distribution of L. bushaie. The current distribution that is highly suitable for this plant corresponds to the habitat in which this species was inventoried. Furthermore, the projected future suitable area of L. bushaie based HadGEM3-GC3.1-LL and MIROC6 is expected to increase under the ssp126 and ssp245 scenarios by 2050.

Modelling the climate change impacts on river discharge and inundation extent in the Magdalena River basin – Colombia

ABSTRACT Climate change may have significant impacts on water balance and may considerably influence flooding dynamics of river systems by increasing extreme precipitation. This study evaluates the potential effects of climate change on river discharge and inundation in the Magdalena River basin, the main river in Colombia, using the synergy between the MGB (Modelo de Grandes Bacias) hydrological–hydrodynamic model and downscaled Eta-regional climate model (RCM) projections based on four global climate models (GCMs): BESM (Brazilian Earth System Model), CanESM2 (Canadian Earth System Model), MIROC5 (Model for Interdisciplinary Research on Climate Version Five), and HadGEM2-ES (Hadley Centre Global Environment Model version 2). We used two different greenhouse gas scenarios (RCP4.5 and RCP8.5 (Representative Concentration Pathway)) for the “historical” (1986–2005) and “mid-term prospective” (2046–2065) periods. Model results for the “mid-term prospective” period under scenarios RCP4.5 and RCP8.5 indicate increase in mean river discharges in the east portion of the basin, decreased river discharges (mainly in the dry season) in the upper Magdalena basin, and increased inundation extent. By coupling hydrological–hydrodynamic and GCMs/RCMs models, modelling frameworks like the one used in this study provide an effective management tool for stakeholders interested in potential climate change impacts on tropical river basins.

Characteristics of tropical–extratropical cloud bands over tropical and subtropical South America simulated by BAM‐1.2 and HadGEM3‐GC3.1

AbstractTropical–extratropical cloud bands are common in South America (SAm), contributing significantly to the total rainy season precipitation. Thus, it is fundamental that climate and weather forecast models correctly represent them and their associated dynamic aspects. Adopting an event‐based framework, we evaluate the performance of two global models in simulating the observed cloud bands over SAm: the Brazilian Global Atmospheric Model version 1.2 (BAM‐1.2) and the Hadley Centre Global Environment Model in the Global Coupled configuration 3.1 (HadGEM3‐GC3.1). Both models reproduce the main characteristics of cloud bands and the dynamical aspects leading to their development and persistence. Nonetheless, the biases in precipitation during simulated cloud bands contribute more than 50% of the bias in total precipitation in some regions. BAM‐1.2 simulates fewer but more persistent cloud bands than observed; HadGEM3‐GC3.1 simulates weaker cloud band activity during early summer and more persistent events after January than observed. In all models, the biases in cloud band events arise from the interaction between biases in the basic state and the synoptic‐scale regional circulation. In the basic state, stronger upper level westerlies over the midlatitude South Pacific support the propagation of longer and slower Rossby waves towards subtropical SAm, increasing the duration of the cloud band events. This bias interacts with negative biases in the upper level westerlies over subtropical SAm, increasing the wind shear, hindering the propagation of synoptic‐scale Rossby waves into lower latitudes, and resulting in biases in the cloud band location, intensity, and seasonality. The application in this study of an event‐based framework robust to differences in model resolution and complexity enables the identification of small but critical biases in circulation. These biases are linked to synoptic‐scale rainfall system biases and help to explain the season total rainfall model biases.

Does Increasing Climate Model Horizontal Resolution Be Beneficial for the Mediterranean Region?: Multimodel Evaluation Framework for High‐Resolution Model Intercomparison Project

AbstractThe Mediterranean region (MR) is one of the climate change hot spots, posing serious threats to society. The insufficient resolution of the global climate models limits their capability to resolve the complex topography over MR, resulting in a large bias in climate variables. This study examines the performance of four Coupled Model Intercomparison Project phase six models from the High‐Resolution Model Intercomparison Project (HighResMIP) in reproducing the Mediterranean climate. A special focus is put on the role of oceanic and atmospheric model horizontal resolution and spread among the models. Various aspects, relevant to air‐sea interactions and precipitation are examined, including the mean, extremes, and associated mechanisms. All HighResMIP models reasonably well capture the large‐scale oceanic and atmospheric characteristics, but there is a sizable model‐to‐model difference. The Hadley Centre Global Environment Model and European Centre for Medium‐Range Weather Forecasts generally perform better than the other models at comparable atmospheric and oceanic horizontal resolutions. A finer oceanic resolution improves the representation not only of oceanic characteristics (i.e., sea surface temperature, SST) but also of the atmospheric processes (wind and precipitation). Likewise, increasing atmospheric model resolution benefits various atmospheric and ocean characteristics. Over some sub‐basins of the Mediterranean Sea, the intensification of surface wind speed results in the deepening of the ocean's mixed layer leading to cooling, indicating negative feedback in Wind‐SST. In contrast, in other regions, the warmer SST results in the intensification of wind (positive feedback in Wind‐SST).

Habitat Suitability of Fig (Ficus carica L.) in Mexico under Current and Future Climates

Emerging or alternative crops are those that have been recently introduced in response to new demands and commercial opportunities. The fig has been introduced as an alternative fruit crop in Mexico due to its high nutritional, nutraceutical, and antioxidant capacity. A total of 644 points of presence were downloaded and filtered according to climatic ranges and agricultural areas, leaving 68 records. The MaxEnt algorithm was used to develop the habitat suitability models for current and future climate. The bioclimatic variables of the global circulation models, Hadley Centre Global Environment Model version 2-EarthSystem (HADGEM2-ES) and Max Planck Institute for Meteorology-Earth System Model Low Resolution (MPI-ESM-LR), were used under scenarios 2.6 and 8.5. The changes in the fig area for Mexico were analyzed based on the generated models. Under the current climate, 359,575.76 km2 were estimated for 2050, and a loss of area for the excellent category was estimated for both models and scenarios; however, for the MPI-ESM-LR model projected to 2070, an increase of 5.51% and 0.39% was estimated for scenarios 2.6 and 8.5, respectively. The effect of climate change on agronomic species such as figs will be expressed in variations in climatic ranges and areas suitable for their development. The results of this study reveal the negative and positive effects of climate change on fig habitat suitability in Mexico. The dynamics of changes in surface area will be reflected mainly in northern and central Mexico.

Predicted impacts of climate change and extreme temperature events on the future distribution of fruit bat species in Australia

Fruit bats are important pollinators and seed dispersers whose distribution may be affected by climate change and extreme-temperature events. We assessed the potential impacts of those changes and events on the future distribution of fruit bats in Australia. Correlative species distribution modelling was used to predict the distribution of seven (based on data availability) tropical and temperate fruit bat species. We used bioclimatic variables, the number of days where temperature ≥42 °C (known to induce extreme heat stress and mortality in fruit bats), and land cover (a proxy for habitat) as predictors. An ensemble of machine-learning algorithms was used to make predictions for the current-day distribution and future (2050 and 2070) scenarios, using multiple emission scenarios (RCP 4.5 and 8.5) and global circulation models (Australian Community Climate and Earth System Simulator, Hadley Centre Global Environment Model Carbon Cycle, and the Model for Interdisciplinary Research on Climate). Our results predict, under current conditions, on average, 9.1 % and 90.8 % of the area are suitable and unsuitable, respectively. Under future scenarios, on average, 6.7 % and 89.7 % continued to be suitable and unsuitable, respectively, while there was a 1.1 % gain and 2.4 % loss in suitable areas. Under current conditions, we predict, on average, 5.6 % and 3.4 % are suitable inside and outside species’ IUCN-defined range, respectively. While under future scenarios, 4.8 % (4.4 % stable and 0.4 % gain) and 2.9 % (2.2 % stable and 0.6 % gain) are suitable inside and outside the range respectively. On average, the gain in areas inside the range covers 2703.5 grid cells of size 5 km, while outside the range it is 4070.3 cells. Under future scenarios, the loss in areas is predicted to be 1.2 % and 1.1 % on average, inside and outside species range respectively. Fruit bats are likely to respond to climate change and extreme temperatures by migrating to more suitable areas, including regions not historically inhabited by those species. Our results can be used for identifying areas at risk of new fruit-bat colonisation, such as human settlements and orchards, as well as areas that might be important for habitat conservation.

Estimation of Runoff Under Changed Climatic Scenario of a Meso Scale River by Neural Network Based Gridded Model Approach

Climate change is linked with change in precipitation, evapotranspiration, and other climatological parameters, and therefore the runoff of a river basin will be affected. The Gomati River basin is the largest in Tripura. The increased settlement in the Gomati River basin and climate change may threaten the natural flow patterns that enable its diversity. This study assesses the impact of climate change on total flow from a catchment in northeast India (the Gomati River catchment). For this assessment, the Group Method of Data Handling (GMDH) model was used to simulate the rainfall–runoff relationship in the catchment with respect to the observed data during 2008–2009. The statistically downscaled outputs of the Hadley Centre Global Environment Model version 2 (HadGEM2-ES) general circulation model scenario was used to assess the impacts of climate change on the Gomati River basin. Future projections were developed for the 2030s, 2040s, and 2050s. The results of this study may contribute to the development of adaptive strategies and future policies for the sustainable management of water resources in northeast Tripura.

The global monsoon system representation in BAM‐v1.2 and HadGEM3 climate simulations

AbstractThe features of monsoon systems in the Northern and Southern Hemispheres are analysed in climate simulations of two atmospheric models: the Brazilian Global Atmospheric Model version 1.2 (BAM‐v1.2) and the UK Met Office Hadley Centre Global Environment Model version 3 (HadGEM3). The results are compared to GPCP precipitation and ERA5 datasets. Although they have different configurations and parameterizations, the purpose is to evaluate their ability in representing key features of the global monsoon system. The spatial extent of the monsoon domains is well simulated by the models, as well as the main characteristics of the monsoons, although precipitation biases are noticed in the regions affected by the systems, consistent with vertical motion and moisture flux biases. The largest precipitation biases are found in the West Pacific Monsoon Region, extended to the east, and in the Australia Monsoon Region extended to the Maritime continent. Deficiencies in precipitation can be related to inaccuracy of vertical motion and humidity flux, as well as to the lack of air–sea interaction. However, the atmospheric circulation features at low and high levels are well represented in all monsoon regions, as well as the annual cycle of precipitation in those regions by both models. The divergence at high levels and convergence at low levels associated with ascending air movement and precipitation in monsoon regions are well represented by the models. An analysis of two monsoon indices at eight monsoon regions showed the models are generally able to simulate the relationship between precipitation and circulation features. In the majority of years, the signs of indices from the models agree with observations. Correlations of precipitation and circulation indices between models and observations show statistically significant values for some monsoon regions. The results obtained contribute to improving knowledge about global monsoon features and their representation in the two models.

Sensitivity of the simulated atmospheric rivers over East Asia to horizontal resolution in the HadGEM3-GC3.1 general circulation model

This study evaluates the performance of the Met Office Hadley Centre Global Environment Model 3–Global Coupled version 3.1 (HadGEM3-GC3.1) in simulating the climatology of atmospheric rivers (ARs) over East Asia during the period 1951–2014. Compared to a high-resolution climate reanalysis dataset and three different precipitation observation datasets, better performances in simulating the characteristics of ARs, including the frequency of occurrences, intensity of moisture transport, meridional heat transport and contributions to precipitation, are demonstrated by the simulation at the N512 (0.35° × 0.23°, ~25-km) horizontal resolution compared to those at the N96 (1.875° × 1.25°, ~135-km) and N216 (0.83° × 0.56°, ~65-km) resolutions. Also, the N512 experiment is more capable of representing the significant increase in AR frequency for the years with preceding El Niño events. However, the N512 experiment still presents an underestimation of AR frequency in different seasons. In contrast to the N96 and N216 simulations, it overestimates the AR-associated extreme precipitation amount over most of the study region, which is partly explained by the more precipitation-favorable thermodynamic conditions along the simulated AR axes. Overall, a sufficiently high horizontal resolution is crucial for the GCM to realistically represent the observed characteristics of ARs over East Asia and to robustly project their potential changes in a warming climate, although the systematic errors still affect the realism of the simulated ARs.

Policy-Making toward Integrated Water Resources Management of Zarrine River Basin via System Dynamics Approach under Climate Change Impact

In terms of having a comprehensive vision toward supplying the water requirements, a multi-criteria decision-making approach was employed on the Zarrine River Basin (ZRB) in the northwest of Iran. First, the climate change impacts were analyzed with the Long Ashton Research Station Weather Generator (LARS-WG) downscaling approach by using General Circulation Models (GCMs) including the European Consortium Earth System Model (EC-EARTH), Hadley Centre Global Environment Model version 2 (HADGEM2), Model for Interdisciplinary Research on Climate, version 5 (MIROC5), and Max Planck Institute Earth System Model (MPI-ESM), from Coupled Model Intercomparison Project 5 (CMIP5) under Representative Concentration Pathway (RCP4.5, RCP8.5) scenarios for 2021–2080. Afterward, the downscaled variables were utilized as inputs to the Artificial Neural Network (ANN) model to predict future runoff under the climate change impact. Finally, the system dynamics (SD) model was employed to simulate various scenarios for assessing water balance utilizing the Vensim software. The results of downscaling models suggested that the temperature of the basin will increase by 0.47 and 0.91 °C under RCPs4.5 and 8.5 by 2040, respectively. Additionally, the precipitation will decrease by 3.5 percent under RCP4.5 and 14 percent under RCP8.5, respectively. Moreover, simulation results revealed that the water demand in various sectors will be enormously increased. The contribution of the climate change impact on the future run-off was a seven percent decrease, on average, over the basin. The SD model, according to presented plausible scenarios including decreasing agriculture product and shifting irrigation efficiency, cloud-seeding, population control, and household consumption reduction, reducing meat and animal-husbandry production, and groundwater consumption control, resulted in a water balance equilibrium over five years. However, the performance of individual scenarios was not effective; instead, a combination of several scenarios led to effective performance in managing reduced runoff under climate change.

Drivers and physical processes of drought events over the State of São Paulo, Brazil

The State of São Paulo, Brazil (SSP) was impacted by severe water shortages during the intense austral summer drought of 2013/2014 and 2014/2015 (1415SD). This study seeks to understand the features and physical processes associated with these summer droughts in the context of other droughts over the region during 1961–2010. Thus, this study examines the spatio-temporal characteristics of anomalously low precipitation over SSP and the associated large-scale dynamics at seasonal timescales, using an observation-based dataset from the Climatic Research Unit (CRU) and model simulation outputs from the Met Office Hadley Centre Global Environment Model (HadGEM3-GA6 at N216 resolution). The study analyzes Historical and Natural simulations from the model to examine the role of human-induced climate forcing on droughts over SSP. Composites of large-scale fields associated with droughts are derived from ERA-20C and ERA-Interim reanalysis and the model simulations. HadGEM3-GA6 simulations capture the observed interannual variability of normalized precipitation anomalies over SSP, but with biases. Drought events over SSP are related to subsidence over the region. This is associated with reduced atmospheric moisture over the region as indicated by the analysis of the vertically integrated moisture flux convergence, which is dominated by reduced moisture flux convergence. The Historical simulations simulate the subsidence associated with droughts, but there are magnitude and location biases. The similarities between the circulation features of the severe 1415SD and other drought events over the region show that understanding of the dynamics of the past drought events over SSP could guide assessment of changes in risk of future droughts and improvements of model performance. The study highlights the merits and limitations of the HadGEM3-GA6 simulations. The model possesses the skills in simulating the large-scale atmospheric circulations modulating precipitation variability, leading to drought conditions over SSP.

Modelling the impact of climate change on maize yield in Victoria Nile Sub-basin, Uganda

Agriculture is the backbone of Uganda’s economy, with about 24.9% contribution to the gross domestic product (GDP) as per the Uganda National Household Survey 2016/17. Agricultural productivity (yield per hectare) is still low due to the high dependence on rain-fed subsistence farming. Climate change is expected to further reduce the yield per hectare. Therefore, this study aims to evaluate the potential impact of climate change on maize yield in the Victoria Nile Sub-basin using the AquaCrop model. It further assesses the possible adaptation measures to climate change. The Hadley Centre Global Environmental Model version 2–Earth System (HadGEM2-ES) data downloaded from the Coordinated Regional Downscaling Experiment (CORDEX) was used to simulate maize yield in the near future (2021–2040), mid future (2041–2070) and late future (2071–2099). Results show that maize yield is likely to reduce by as high as 1–10%, 2–42% and 1–39% in the near, mid and late futures, respectively, depending on the agro-ecological zone. This decline in maize yield can have a significant impact on regional food security as well as socio-economic well-being since maize is a staple crop. The study also shows that improving soil fertility has no significant impact on maize yield under climate change. However, a combined application of supplementary irrigation and shifting the planting dates is a promising strategy to maintain food security and socio-economic development. This study presents important findings and adaptation strategies that policymakers and other stakeholders such as farmers can implement to abate the effects of climate change on crop production.

Assessing the representation of South American monsoon features in Brazil and U.K. climate model simulations

AbstractThis paper assesses how well the CPTEC/INPE Brazilian Global Atmospheric Model (BAM‐1.2) and the atmospheric component of the UK Met Office Hadley Centre Global Environment Model (HadGEM3‐GC3.1) represent the main South American monsoon features. Climatological (1981–2010) ensemble means of Atmospheric Model Intercomparison Project (AMIP)‐type climate simulations are evaluated. The assessment evaluated the models’ ability to represent the South America austral summer and winter precipitation contrast and associated circulation, key South American monsoon system elements, the association between south‐east Brazil and South America precipitation, and climatological (1997/1998 to 2013/2014) distributions of rainy season onset and demise dates over south‐east Brazil (15°S–25°S, 40°W–50°W) and the core monsoon region (10°S–20°S, 45°W–55°W). Despite some identified deficiencies, both models depict the monsoon region and represent the main features, including (1) the north‐west–south‐east precipitation band and associated ascending motion over central South America; (2) the upper‐level Bolivian High and the north‐east South America trough during the summer; (3) the lower‐level South Atlantic and Pacific subtropical anti‐cyclones and (4) the low‐level jet east of the Andes. Both models represent upper‐level divergence and lower‐level convergence over the core monsoon region, and upper‐level convergence and lower‐level divergence over the Pacific and Atlantic anti‐cyclones associated with the regional Walker circulation during the pre‐monsoon (spring) and peak monsoon (summer) seasons. Convection over South America is weaker in BAM‐1.2 than observed, consistent with continental precipitation deficit. The models reproduce the dipole‐like precipitation pattern between south‐east Brazil and south‐eastern South America during the austral summer but overestimate these patterns spatial extent over the South Atlantic. Both models simulate the main observed climatological features of rainy season onset and demise dates for the two above defined investigated regions. HadGEM3 overestimates onset dates interannual variability. These results can contribute towards understanding climate and land‐use change implications for environmental sustainability and for recommending climate adaptation strategies.

The contribution of melt ponds to enhanced Arctic sea-ice melt during the Last Interglacial

Abstract. The Hadley Centre Global Environment Model version 3 (HadGEM3) is the first coupled climate model to simulate an ice-free Arctic during the Last Interglacial (LIG), 127 000 years ago. This simulation appears to yield accurate Arctic surface temperatures during the summer season. Here, we investigate the causes and impacts of this extreme simulated ice loss. We find that the summer ice melt was predominantly driven by thermodynamic processes: atmospheric and ocean circulation changes did not significantly contribute to the ice loss. We demonstrate these thermodynamic processes were significantly impacted by melt ponds, which formed on average 8 d earlier during the LIG than during the pre-industrial control (PI) simulation. This relatively small difference significantly changed the LIG surface energy balance and impacted the albedo feedback. Compared to the PI simulation: in mid-June, of the absorbed flux at the surface over ice-covered cells (sea-ice concentration > 0.15), ponds accounted for 45 %–50 %, open water 35 %–45 %, and bare ice and snow 5 %–10 %. We show that the simulated ice loss led to large Arctic sea surface salinity and temperature changes. The sea surface temperature and salinity signals we identify here provide a means to verify, in marine observations, if and when an ice-free Arctic occurred during the LIG. Strong LIG correlations between spring melt pond and summer ice area indicate that, as Arctic ice continues to thin in future, the spring melt pond area will likely become an increasingly reliable predictor of the September sea-ice area. Finally, we note that models with explicitly modelled melt ponds seem to simulate particularly low LIG sea-ice area. These results show that models with explicit (as opposed to parameterised) melt ponds can simulate very different sea-ice behaviour under forcings other than the present day. This is of concern for future projections of sea-ice loss.

Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.

Warm Cloud Evolution, Precipitation, and Their Weak Linkage in HadGEM3: New Process-Level Diagnostics Using A-Train Observations

AbstractThe latest configuration of the Hadley Centre Global Environmental Model, version 3 (HadGEM3), contains significant changes in the formulation of warm rain processes and aerosols. We evaluate the impacts of these changes in the simulation of warm rain formation processes using A-Train observations. We introduce a new model evaluation tool, quartile-based contoured frequency by optical depth diagrams (CFODDs), in order to fill in some blind spots that conventional CFODDs have. Results indicate that HadGEM3 has weak linkage between the size of particle radius and warm rain formation processes, and switching to the new warm rain microphysics scheme causes more difference in warm rain formation processes than switching to the new aerosol scheme through reducing overly produced drizzle mode in HadGEM3. Finally, we run an experiment in which we perturb the second aerosol indirect effect (AIE) to study the rainfall–aerosol interaction in HadGEM3. Since the large changes in the cloud droplet number concentration (CDNC) appear in the AIE experiment, a large impact in warm rain diagnostics is expected. However, regions with large fractional changes in CDNC show a muted change in precipitation, arguably because large-scale constraints act to reduce the impact of such a big change in CDNC. The adjustment in cloud liquid water path to the AIE perturbation produces a large negative shortwave forcing in the midlatitudes.

The climate change potential effects on the run-of-river plant and the environmental and economic dimensions of sustainability

In this work, we evaluate the environmental and economic sustainability dimensions of a run-of-river hydroelectric plant operation regarding environmental impacts and potential direct and indirect effects of climate change. Results suggest the generation of a vicious cycle of clean generation and dirty generation, enhanced by a positive feedback with climate change impacts. This cycle is triggered by the tradeoffs between environmental protection policies and the socioeconomic pressure for energy production, embedded in an energy production matrix that prioritizes fossil fuel-based production as responses to peak energy demand. The climate projections were generated by the Eta Regional Climate Model from the National Institute for Space Research. They were forced by the atmospheric simulations of the Interdisciplinary Climate Research Model (MIROC5) and the Hadley Center Global Environmental Model (HadGEM2-ES) under the RCP4.5 and RCP 8.5 emission scenarios. The MHD-INPE Distributed Hydrological Model was used to generate streamflow projections. Environmental impacts were assessed by accounting for carbon stock and sequestration, greenhouse gas emissions, and energy cost. Climate projections indicated reduced precipitation and increased temperature. The streamflow will present progressively reductions of the flow volume until the end of the century, which undermines the plant's ability to ensure firm energy and induce thermal plants' activation to supply the demand. This activation will lead to an increase in greenhouse gas emissions and an increase in the price of energy, which may lower the benefits in carbon stock associated with a run-of-river hydropower plant and negatively influence the reduction commitments assumed by Brazil.

Climatology of Borneo Vortices in the HadGEM3-GC3.1 General Circulation Model

AbstractBorneo vortices (BVs) are intense precipitating winter storms that develop over the equatorial South China Sea and strongly affect the weather and climate over the western Maritime Continent because of their association with deep convection and heavy rainfall. In this study, the ability of the Hadley Centre Global Environment Model 3–Global Coupled, version 3.1 (HadGEM3-GC3.1), global climate model to simulate the climatology of BVs at different horizontal resolutions is examined using an objective feature-tracking algorithm. The HadGEM3-GC3.1 at the N512 (25 km) horizontal resolution simulates BVs with well-represented characteristics, including their frequency, spatial distribution, and lower-tropospheric structures when compared with BVs identified in a climate reanalysis, whereas the BVs in the N96 (~135 km) and N216 (~65 km) simulations are much weaker and less frequent. Also, the N512 simulation better captures the contribution of BVs to the winter precipitation in Borneo and the Malay Peninsula when compared with precipitation from a reanalysis data and from observations, whereas the N96 and N216 simulations underestimate this contribution because of the overly weak low-level convergence of the simulated BVs. The N512 simulation also exhibits an improved ability to reproduce the modulation of BV activity by the occurrence of northeasterly cold surges and active phases of the Madden–Julian oscillation in the region, including increased BV track densities, intensities, and lifetimes. A sufficiently high model resolution is thus found to be important to realistically simulate the present-climate precipitation extremes associated with BVs and to study their possible changes in a warmer climate.