A2 Scenario Research Articles (Page 1)

Dhaka, the highly populated capital of Bangladesh, generates a huge amount of solid waste that goes directly into the landfills posing a serious threat to public health, and land use. In this study, the current and some feasible alternative treatment strategies were assessed through life cycle analysis to find an answer for a sustainable waste management approach for Dhaka city. Four alternative waste management strategies: Landfilling + Composting (A1), Landfilling + Composting + Incineration (A2 & A3; variation in waste percentage), and Landfill + Incineration (A4) were structured to compare the environmental impacts with the baseline Landfilling scenario (B0). The Life Cycle Inventory (LCI) was constructed by blending the unit waste databases from ecoinvent 3.8, and field reports to project a representative municipal solid waste (MSW) scenario. Organic waste was found to be the major fraction of MSW. The life cycle impact analysis indicated that Scenario A2, with approximately 75% composting and 8.8% incineration of the collected waste, was the most environmentally friendly strategy in most impact assessment categories such as fine particulate matter formation, freshwater eutrophication, marine eutrophication and ecotoxicity etc. The second cleanest option, A1, reduced the burden of freshwater ecotoxicity, human carcinogenic toxicity, and terrestrial ecotoxicity the most. Compared to the baseline B0 practice, composting and incineration favored land use but composting was found to be the most feasible land use option in the long run. The electricity generation from the incineration of major waste fraction was only 3–5% of the concurrent requirement.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-19949-w.

This study investigated the influence of the Antarctic Oscillation (AAO) on the interannual variability of precipitation in the Indian monsoon region, aiming to address discrepancies in the existing literature. The degree of correlation between the AAO and moisture transport from the main oceanic sources supplying moisture to India, as well as precipitation over the region, was assessed using Pearson and partial correlation coefficients. The latter was employed to account for the potential confounding influence of the El Niño-Southern Oscillation (ENSO), the dominant mode of climatic variability. Five datasets were used: moisture sinks derived from the FLEXPART model driven by ERA-Interim data (1980-2012), and precipitation data (1984-2016) from two surface rain gauge datasets (IITM-IMR and IMD4), ERA5 reanalysis, and PERSIANN-CDR. In addition, spatial patterns of climate teleconnections associated with the AAO were analyzed using a composite approach. Seasonal time series were constructed under two analytical frameworks: the first (scenario A1) was based on patterns linked to seasonal variations in solar radiation between hemispheres due to Earth’s orbital movement around the Sun, while the second (scenario A2) focused on patterns associated with the strengthening and weakening of the Antarctic polar vortex, considering the specific climatic characteristics of India. Among the key findings, scenario A2 yielded improved results compared to scenario A1. The strongest correlation emerged over the Peninsular region, where the AAO showed a significant in-phase relationship with precipitation during October, November, and December (OND), and an out-of-phase relationship with precipitation during January-February (JF), relative to the OND period. Another notable result was found for the Northwestern region, where a positive relationship was identified between the AAO during the June-September (JJAS) period and precipitation during the subsequent OND season. These findings align with the “coupled ocean-atmosphere bridge” mechanism, which involves anomalies in the high-pressure system over the Indian Ocean and its interaction with key components of the Indian monsoon system.

Invasive plant species, such as Imperata cylindrica (cogongrass), threaten native ecosystems, natural resources, and lands worldwide. With climate change, the risk of invasions may increase as more favorable conditions enable non-native species to spread into new areas. This study employs the CLIMEX model to predict the potential distribution of I. cylindrica under current and future climate scenarios, under the SRES A2 scenario. A comprehensive dataset comprising 6,414 occurrence records was used to simulate the species' ecological niche based on key climatic parameters, including temperature and soil moisture. Our results indicate that more than 16% of the global land surface is currently highly suitable for I. cylindrica (Ecoclimatic Index ≥ 30), with significant risk areas identified in Central America, Africa, and Australia. Future projections under the A2 scenario suggest an expansion of suitable habitats by 2050, 2080, and 2100, particularly in regions such as southern Argentina and parts of North America, while areas in Africa may experience a decrease in suitability due to rising temperatures. Sensitivity analysis revealed that temperature-related parameters (DV0, DV1, DV2, and DV3) are the most influential in determining the species' distribution, highlighting the critical role of climate in driving the invasive potential of I. cylindrica. These findings provide valuable insights into the future risks associated with I. cylindrica invasions.

Bangladesh, one of the most vulnerable countries to climate change, has been experiencing significant climate change-induced risks. Particularly, the northwest region of the country has been severely affected by climate extremes, including droughts and heat waves. Therefore, proper understanding and assessment of future climate change scenarios is crucial for the adaptive management of water resources. The current study used the statistical downscaling model (SDSM) to downscale and analyze climate change-induced future changes in temperature and precipitation based on multiple global climate models (GCMs), including HadCM3, CanESM2, and CanESM5. A quantitative approach was adopted for both calibration and validation, showing that the SDSM is well-suited for downscaling mean temperature and precipitation. Furthermore, bias correction was applied to enhance the accuracy of the downscaled climate variables. The downscaled projections revealed an upward trend in mean annual temperatures, while precipitation exhibited a declining trend up to the end of the century for all scenarios. The observed data periods for the CanESM5, CanESM2, and HadCM3 GCMs used in SDSM were 1985–2014, 1975–2005, and 1975–2001, respectively. Based on the aforementioned periods, the projections for the next century indicate that under the CanESM5 (SSP5-8.5 scenario), temperature is projected to increase by 0.98 °C, with a 12.4% decrease in precipitation. For CanESM2 (RCP8.5 scenario), temperature is expected to rise by 0.94 °C, and precipitation is projected to decrease by 10.3%. Similarly, under HadCM3 (A2 scenario), temperature is projected to increase by 0.67 °C, with a 7.0% decrease in precipitation. These downscaled pathways provide a strong basis for assessing the potential impacts of future climate change across the northwestern region of Bangladesh.

This paper describes various methods of statistical downscaling used to downscale the temperatures of the city of Bhuntar in Himachal Pradesh. We have used NCEP data for this study. Statistical downscaling has been done in three main ways. First, three machine learning methods have been used. Simple linear regression just uses temperature as a predictor and multiple linear regression uses the NCEP parameters fas, vas, 500as, 5thas, and humas. Non-linear regression was performed using the same variables. Among the machine learning methods, non-linear regression had the best correlation with an R2 of 0.857. Second, a deep learning method was developed for climate downscaling, and it has shown significant performance based on an R2 value of 0.84. Third, SDSM (Statistical Downscaling Model) was used, a tool that is based on multiple linear regression for prediction. It gave an R2 value of 0.9895 in the A2 scenario and 0.9901 in the B2 scenario. This tool gives the highest value of correlation among all the methods carried out in this study. SDSM has also predicted future values of Bhuntar based on given GCM values. Hence, SDSM has proven to be the most efficient.

Mapping and assessing the future provision of lake ecosystem services in Lithuania

The long-term shifts in temperatures and weather patterns are referred to as climate change. Climate change not only leads to long-term shifts in average temperatures but also changes in the spatial and temporal distribution of rainfall over continents. This study aims to predict likely changes in the rainfall pattern induced by climate change over the West Central (WC) region of India. The approach uses a statistical downscaling technique that converts coarse-scale outputs of the global climate model (GCM) to high-resolution future precipitation projections giving refined distribution. The decision support tool that uses a robust statistical downscaling technique viz. statistical downscaling model (SDSM) is used for assessing local climate change impacts. The research includes the study of likely regional climate variability, by integrating historical observational data and empirical relationships between large-scale climate variables and local weather patterns. Historical data and the SDSM, version 4.2, are employed to forecast future rainfall trends. Rainfall data from the India Meteorological Department and the National Centre for Environmental Prediction (NCEP) from 1961 to 2001 are used along with outputs from general circulation models (GCMs), viz. Hadley Centre coupled model, version 3 (HadCM3), and coupled global climate model, version 3 (CGCM3), for the period 1961–2099. Rainfall scenarios are presented for three future time periods (2011–2040, 2041–2070, and 2071–2099). The study indicates a significant increase in the mean annual precipitation across the West Central India region, particularly in the 2050s and 2080s. Mean annual rainfall is projected to rise by 10–19.4% under HadCM3 A2 and B2 scenarios. The HadCM3 indicates the month of September as the month of the highest precipitation in later time periods, whereas it is the month of August, according to CGCM3 simulations. When comparing the results of the two models, HadCM3 gives better results, as indicated by better R2 value in validation. Thus, the analysis gives climate change-induced likely changes in the spatiotemporal distribution of precipitation over the West Central India region. The insight given by the work will be useful for decision making in many sectors like agriculture, water management, disaster risk reduction, and infrastructure planning.

The aim of this study is to determine the effect of climate change on reference evapotranspiration (ETo) and sunflower and wheat evapotranspiration (ETs and ETw, respectively) in the Trakya Region of Türkiye. ETo Calculator (version 3.2) and CROPWAT 8.0 were used to compute ETo and ET in the reference period (1970–1990), short- (2016–2025), mid- (2046–2055), and long- (2076–2085) terms. Additionally, ETo was tested in 2012 and ETo was simulated for every 1 °C temperature increase up to 5 °C in the reference period. Calculated ETo and ET values for the future were compared with the reference period. For the future, climate data estimated by RegCM3 Regional Climate Model, A2 scenario were used. While the average ETo value of the reference period was 3.3 mm day−1, it was 3.0 mm day−1 in 2012. Compared to the reference period, ETo values change by −3% (3.2 mm day−1), 9% (3.6 mm day−1), and 21% (4.0 mm day−1) in the short-, mid-, and long-term, respectively. The 575 mm ET deficit calculated during the vegetation period of sunflower in the model reference period was forecasted to change by −11% (514 mm), +15% (660 mm), and +25% (721 mm) in the short-, mid-, and long-term, respectively. For wheat, while 59 mm of excess water was calculated in the reference period, it became 193 mm (+227%) in the short-term and a water deficit of 8 mm (−113%) and 6 mm (−110%) in the mid- and long-term, respectively. In addition, it is estimated that there will be an increase of 0.1 mm day−1 (4%) in ETo values for each 1 °C temperature increase compared to the reference period (1970–1990). It was concluded that climate change in the Trakya Region will not significantly affect wheat farming; however, it will cause a serious water deficit in sunflower production.

Forest fire is one of the dominant disturbances in the forests of Heilongjiang Province, China, and is one of the most rapid response predictors that indicate the impact of climate change on forests. This study calculated the Canadian FWI (Fire Weather Index) and its components from meteorological record over past years, and a linear model was built from the monthly mean FWI and monthly fire numbers. The significance test showed that fire numbers and FWI had a very pronounced correlation, and monthly mean FWI was suitable for predicting the monthly fire numbers in this region. Then FWI and its components were calculated from the SRES (IPCC Special Report on Emission Scenarios) A2 and B2 climatic scenarios, and the linear model was rebuilt to be suitable for the climatic scenarios. The results indicated that fire numbers would increase by 2.98–129.97% and −2.86–103.30% in the A2 and B2 climatic scenarios during 2020–2090, respectively. The monthly variation tendency of the FWI components is similar in the A2 and B2 climatic scenarios. The increasing fire risk is uneven across months in these two climatic scenarios. The monthly analysis showed that the FFMC (Fine Fuel Moisture Code) would increase dramatically in summer, and the decreasing precipitation in summer would contribute greatly to this tendency. The FWI would increase rapidly from the spring fire season to the autumn fire season, and the FWI would have the most rapid increase in speed in the spring fire season. DMC (Duff Moisture Code) and DC (Drought Code) have relatively balanced rates of increasing from spring to autumn. The change in the FWI in this region is uneven in space as well. In early 21st century, the FWI of the north of Heilongjiang Province would increase more rapidly than the south, whereas the FWI of the middle and south of Heilongjiang Province would gradually catch up with the increasing speed of the north from the middle of 21st century. The changes in the FWI across seasons and space would influence the fire management policy in this region, and the increasing fire numbers and variations in the FWI scross season and space suggest that suitable development of the management of fire sources and forest fuel should be conducted.

Thermal comfort in a two-storey malaysian terrace house: Are passive cooling methods sufficient in present and future climates?

In recent decades, in third world countries, especially in the Middle East, the concept of urban micro-climate has undergone many changes in the process of development and construction, leading to environmental crises and the discrete structure of energy consumption in urban blocks. The urban form, the product of morphological changes in recent periods, has had significant effects on the micro-climate of the city. The city of Tabriz in the cold and dry areas of Iran has suffered from the inadequacies of the urban form and adverse effects on the micro-climate of the city as a result of unbalanced development. The main aim of research as parametric study on the interactions between urban morphology and microclimate is to investigate density metric to analysis effect amount in micro-climates. The research is analytical-descriptive and method of collecting data in the form of documents includes literature review, modeling and simulation using Envi-met software and density metric explain modes of a hypothetical in 10 scenarios and are presented in the form of two groups. The construction parts of the hypothetical areas are located in the urban area of Tabriz city, Iran. All scenarios were assumed to be in the same area configuration, where buildings are located in 25 plots of 40 m x 40 m. The result shows Investigation the average ratings obtained from microclimatic simulation of the first group of scenarios shows that by keeping FAR constant and changing BSC, one cannot expect a specific sequence of changes in microclimatic parameters in the space around the buildings but in the case of the second scenario group which is presented with constant BSC and variable FAR, there is a significant sequence in the order of the obtained ranks and the change trend in the average parameters. The results show scenario A2 with FAR 1 and BSC 40% with the lowest average value (3.5) of the total of four parameters of simulating the hottest and coldest day has achieved the best result and is introduced as the best scenario. For future researches, it is possible to propose a more focused investigation on each of the mentioned parameters. DOI: https://doi.org/10.52783/pst.544

The present study is to understand how climatic variables such as precipitation and temperature vary over time and how those changes affect stream flow in the Jhelum River basin in Pakistan under different emission scenarios A2 and B2. The simulation results of HadCM3 were employed to create potential climate change scenarios with the Statistically Downscale Model (SDSM). The calibrated model Soil and Water Assessment Tool (SWAT) was used to forecast imminent stream flow to develop a proposed future climate change scenario. Results indicated that cooling patterns were identified in the north portion of the study area whereas warming patterns were detected in the south portion. The projected mean annual maximum temperature (Tmax) of 2020’s 2050’s and 2080’s would be 0.3 oC, 0.8 oC, and 0.99 oC, respectively, under the A2 scenario. The changes in mean annual minimum temperature (Tmin) were also observed as it would be 0.4 oC, 0.7 oC, and 1.4 oC during 2020’s (2021-2040), 2050’s (2041-2070) and 2080’s (2071-2100), respectively. Similarly, it was observed that average annual rainfall would rise by 14%, 10%, and 20% during the 2020s, 2050s, and 2080s, respectively, in the Mangla basin. The results showed an increase in annual stream flows of 100% (1545 m3/sec), with increases in the winter and autumn seasons of up to 409% and 211%, respectively, and a drop in the spring and summer seasons of up to 29% and 25%, respectively, in the 2080’s compared to baseline. Water managers should consider the current trends and variability brought on by climate change to improve water management where water is scarce.

In this research, we forecasted both the degree-day units and annual generations of the egg parasitoid Telenomus remus Nixon, which parasitizes fall armyworm (Spodoptera frugiperda). The aim was to comprehend its potential spread across diverse agro-climatic zones, considering both current conditions and potential future climates. This was achieved by examining the correlation between degree-day units and population fluctuations. Climate change data from the HadCM3 model was utilized, focusing on A1 scenarios recommended by the Intergovernmental Panel on Climate Change (IPCC). We aimed to evaluate how temperature projections are anticipated to impact the annual generations in three Egyptian governorates. The investigation revealed that T. remus populations in Aswan, an Upper Egyptian governorate, exhibited a higher number of generations compared to other regions, namely El Sharkia and Beni Suef governorates, in the current climate. The completion of generations by T. remus in El Sharkia, Beni Suef, and Aswan took 13.42, 12.6, and 10.08 days, respectively. The results highlighted that the average generation period in 2021 was the longest, reaching 13.42 ± 6.17 days in El Sharkia governorate. Predictions suggest that T. remus is anticipated to undergo 23 generations between 2040 and 2060, indicating a two-generation increase from 2021. Conversely, in the Beni Suef governorate, where T. remus completed generations in 10.86 ± 5.72 days, the generation period was the longest in 2021. Projections indicate that T. remus is expected to have 24 generations in 2040 and 28 generations in 2060, compared to 22 generations in 2021. Additionally, Aswan’s T. remus is forecasted to experience 32 generations in 2040 and 35 generations in 2060, up from 29 generations in the 2021 climate. The duration of the first generation took 13, 11, and 12 days in the years 2021, 2040, and 2060, respectively. A comprehensive understanding of thermal requirements and biological factors is crucial for accurately predicting generation duration, serving as a valuable reference for the mass production and preservation of parasitoids.

Future climate scenarios lead to changes in the boundary conditions impacting the service life of building envelopes. This may increase or decrease the risk of degradation caused by e.g., freezing and thawing on brick façades. In this study, the risk of degradation based on individual years is compared for different moisture reference year (MRY) selection methods. Furthermore, two new MRY indices, based on the Frost Decay Exposure Index (FDEI), are proposed to assess future climate scenarios. A brick façade in Gothenburg, Sweden, is used as a case study to investigate the microclimate caused by façade orientation and solar radiation on three different parts of the façade. The risk of damage is compared for climate scenarios A1B and A2 from 1961 to 2100. The microclimate of the façade is modelled to obtain boundary conditions for each part instead of using MRYs as uniform boundary conditions for the whole building. The study demonstrates a 67% difference in risk of degradation between the different parts of the façade. Furthermore, the risk of freeze-thaw degradation reduces in the future. Finally, it is indicated that the basic FDEI index is better at evaluating the severity of exposure compared to its derivatives.

The chapter presents the Climate Atlas of Bosnia and Herzegovina with 180 thematic maps. The digital interactive Climate Atlas was created for the first time for the needs of the Third National Communication of Bosnia and Herzegovina and was published in 2016. The publisher was the Faculty of Natural Sciences and Mathematics of the University of Banja Luka, and the climatological maps are displayed in the form of a WEB interactive climate atlas. The interactive climate atlas can be accessed via the link: http://www.unfccc.ba/klimatski_atlas/. By decision of the Teaching and Scientific Council of the Faculty of Natural Sciences and Mathematics of the University of Banja Luka number: 19/3.1370/16 from May 18, 2016 the Climate Atlas of Bosnia and Herzegovina by authors Davorin Bajić and Goran Trbić was approved to be published as a scientific publication. In this monograph, the Climate Atlas is published for the first time in a printed edition. The Climatic Atlas of Bosnia and Herzegovina consists of sets of digital climatological maps related to two climatological parameters, air temperature and precipitation, displayed by month, season, growing sesaon and year. Climate maps were made for three climatological periods, namely: the observed period 1961‒1990, and the periods 2001‒2030 and 2071‒2100, which refer to scenarios A1B and A2. Climate maps for the period 1961‒1990 were made based on the interpolation of climate parameters from 45 meteorological stations in Bosnia and Herzegovina.

The study highlights the potential characteristics of droughts under future climate change scenarios. For this purpose, the changes in Standardized Precipitation Evapotranspiration Index (SPEI) under the A1B, A2, and B1 climate change scenarios in Iran were assessed. The daily weather data of 30 synoptic stations from 1992 to 2010 were analyzed. The HadCM3 statistical model in the LARS-WG was used to predict the future weather conditions between 2011 and 2112, for three 34-year periods; 2011-2045, 2046-2079, and 2080-2112. In regard to the findings, the upward trend of the potential evapotranspiration in parallel with the downward trend of the precipitation in the next 102 years in three scenarios to the base timescale was transparent. The frequency of the SPEI in the base month indicated that 17.02% of the studied months faced the drought. Considering the scenarios of climate change for three 34-year periods (i.e., 2011-2045, 2046-2079, and 2080-2112) the average percentages of potential drought occurrences for all the stations in the next three periods will be 8.89, 16.58, and 27.27 respectively under the B1 scenario. While the predicted values under the A1B scenario are 7.63, 12.66, and 35.08%respectively. The relevant findings under the A2 scenario are 6.73, 10.16, 40.8%. As a consequence, water shortage would be more serious in the third period of study under all three scenarios. The percentage of drought occurrence in the future years under the A2, B1, and A1B will be 19.23%, 17.74%, and 18.84%, respectively which confirms the worst condition under the A2 scenario. For all stations, the number of months with moderate drought was substantially more than severe and extreme droughts. Considering the A2 scenario as a high emission scenario, the analysis of SPEI frequency illustrated that the proportion of dry periods in regions with humid and cool climate is more than hot and warm climates; however, the duration of dry periods in warmer climates is longer than colder climates. Moreover, the temporal distribution of precipitation and potential evapotranspiration indicated that in a large number of stations, there is a significant difference between them in the middle months of the year, which justifies the importance of prudent water management in warm months.

The Simineh River is heavily reliant on water resources for agricultural aims in the Lake Urmia. However, the hydrological system of the Simineh basin is highly susceptible to the impacts of climate change scenarios, primarily due to the presence of diverse topographical features, limited availability of data, and the complex nature of the local climate. This study aimed to simulate the monthly discharge of the Simineh River using the SWAT and assess the effects of climate change on the monthly discharge. Future climate scenarios for the years 2011-2030 were generated using the HadCM3 weather models under the A2, B1, and A1B scenarios. After evaluating the performance of the LARS-WG model in producing precipitation, minimum and maximum temperatures for the Simineh River watershed, the output of the HadCM3 under the A1B, B1, and A2 scenarios reduced, and the desired meteorological parameters predicted. These predicted values used as inputs for the SWAT model. In this study, assuming no change in land use, the focus was solely on the impact of climate change scenarios. However, appropriate measures can be taken to save the Simineh River's water consumption by optimizing irrigation efficiency through innovative methods. This is crucial because the results indicate that a total reduction of up to 25% in discharge in the Lake Urmia basin under climate change leads to a significant decrease in the annual average inflow to the lake from 570 million cubic meters to 394, 398, and 440 million cubic meters under the A2, B1, and A1B scenarios, respectively. The Simineh River supplies 11% of the water in Lake Urmia, and taking necessary measures to conserve its water resources is essential.

Aeolesthes sarta or Trirachys sarta is a polyphagous long-horned beetle that has caused severe damage to the Populus alba forests/plantations in its regions of origin. Climate change could accelerate the introduction and spread of invasive pest species, potentially causing ecological damage and economic losses. Furthermore, globalization and increased trade can inadvertently transport pests across borders into regions where they do not already occur. Hence, it is crucial to identify areas where the climate is most suitable for the establishment of A. sarta’s and which areas of the world are suitable for the growth of P. alba under climate change scenarios. This study employed the CLIMEX model to estimate the potential global distribution of A. sarta and its correlation with its dominant host, P. alba, under current climatic conditions and potential future scenarios, namely the A1B and A2 climate change scenarios (CCSs). Under current climatic conditions, the model indicates that the establishment of a climatically suitable habitat for A. sarta extends beyond its current known range. The model estimated that, under the world’s current climatic conditions, 41.06% of the world can provide suitable areas (EI > 0) for the survival of A. sarta. For P. alba, under the current climatic conditions, suitable regions for the growth of P. alba are present in all continents (excluding Antarctica); under the world’s current climatic conditions, 53.52% of the world can provide suitable areas for the growth of P. alba (EI > 0). Climate change will significantly alter the number of suitable habitats for A. sarta development and P. alba growth globally. In future climatic conditions, the number areas capable of supplying suitable habitats (EI > 0) for A. sarta will slightly decrease to 40.14% (under A1B and A2 CCSs), while, for P. alba, the number areas capable of supplying suitable habitats will also marginally decrease to 50.39% (under A1B scenario), and this figure is estimated to drop to 48.41% (under A2 scenario) by the end century (2100). Asia, Europe, North America, South America, and Oceania have a high percentage of highly suitable areas for A. sarta development and P. alba growth under current climatic conditions; however, according to estimates of future climatic conditions, by the end century, only Asia, Europe, North America, and Oceania will have a high percentage of highly suitable areas for A. sarta development and P. alba growth. The range of highly suitable habitats is likely to increase in the northern hemisphere; however, this range is expected to shrink with regards to the southern hemisphere. The range contraction was higher under the A2 climate change scenario due to a higher warming trend than in the A1B scenario. Due to climate change, the range of A. sarta development shifted, as did the P. alba growth range, which, thanks to the suitable environmental conditions for the growth of P. alba, makes all those regions vulnerable to the introduction and development of A. sarta. Strict monitoring, prevention, and control measures at borders, airports, and seaports before the trade of P. alba and other suitable host species wood (logs/billets) are highly recommended to prevent the spread of A. sarta and ensure biodiversity security. It is expected that the A. sarta and P. alba climate models presented here will be useful for management purposes since both can be adapted to guide decisions about imparting resources to regions where the threat of pest invasion remains and away from regions where climate suitability is predicted to decrease in the future.

ABSTRACT In this study, a simple polynomial bias correction method is developed to correct the bias in the forecasted streamflow (runoff) derived from a global circulation model (GCM). First, a set of polynomial correction factors was derived comparing observed and GCM-derived runoff for a hindcast period (1961–2000) for each of the 11 selected GCMs. The correction factors are used to correct the GCM-derived streamflow for projected periods (2046–2065 and 2081–2100) for the Intergovernmental Panel on Climate Change scenarios A2 and B1 (CMIP3) for the Murray-Hotham catchment of Western Australia. The assumption is that the correction factors derived for each GCM for the observed period (1961–2000) are valid for the projected periods. Results show the method reduces biases considerably for the projected runoff at a catchment scale. The method developed here uses CMIP3 data but it may be applicable to any GCM data, such as CMIP5/CMIP6.

The Caribbean fruit fly, Anastrepha suspensa (Lower, 1862) (Diptera: Tephritidae), is a pest of significant economic importance in Central America and Florida (USA). This study was carried out to examine the influence of climate change on the space-time distribution of A. suspensa on temporal and spatial scales. The CLIMEX software was used to model the current distribution and for climate change. The future distribution was performed using two global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H (MR), under the emission scenarios (SRES) A2 and A1B for the years 2050, 2080, and 2100. The results indicate a low potential for global distribution of A. suspensa in all scenarios studied. However, tropical areas were identified with high climatic suitability for A. suspensa in South America, Central America, Africa, and Oceania until the end of the century. Projections of areas with climatic suitability for A. suspensa can provide helpful information to develop preventive strategies of phytosanitary management avoiding economic impacts with the introduction of the species.