Projection Of Climate Change Scenarios Research Articles

Climate change scenario projections and their implications on food systems in Taita Taveta County, Kenya

This study explored how Taita Taveta County could use the power of climate scenarios in planning agricultural activities on food systems to enhance sustainable food. The study involved the use of climate scenarios to model the past, present and future climate with the view of predicting probable changes in climate and how these changes may impact on food production, transformation and utilization and the ultimate handling of ensuing food wastes to mitigate the looming climate change scenarios. The research was conducted in Taita Taveta County that is characterized into three agro-ecological zones based on altitude and an ensemble of the top two models (ICHEC-EC-EARTH and MPI-M-MPI-ESM-LR) was used to analyse climate projections following RCP4.5 and RCP8.5 pathways. Rainfall and temperature from the Kenya Meteorological Department and supplemented with datasets from Kenya Agricultural and Livestock Research Organization (KALRO), Climate Hazard Group Infrared Precipitation with Stations (CHIRPS) and European Centre for Medium-Range Weather Forecast Reanalysis v5 (ERA5) respectively for the period 1981–2021 were used. The results exhibited occurrences of climate variability and change, and the seasons when the rainfall amounts were highest and lowest. Projected temperatures up to 2065 revealed likelihood of significant future warming and predicted future rainfall variations indicated insignificant increase. The study concluded by predicting a significant rise in temperatures and insignificant increase in rainfall leading to probable decrease in food production. The study recommended adoption climate smart technologies and early warning systems by the communities and policy makers to mainstream climate information in food systems, particularly production, transformation and utilization to enhance efficiency and avoid unnecessary wastage. State and non-state actors and other stakeholders could leverage these results to devise suitable adaptation and mitigation measures in the county.

Potencial productivo agrícola y modelación del cambio climático en la cuenca del Papaloapan

The objective of this work was to make a proposal for potential land use and the projection of climate change scenarios in the Papaloapan basin, using the multi-criteria and multi-objective analysis technique to generate potential capabilities in the basin. From the greatest aptitude, the scenarios were generated using the methodology for Maximum Entropy. The hydrological region was delimited through cartographic material and climatic information was obtained from meteorological stations, geographic information and databases were collected from official secondary sources, the information was processed in the ArcGIS version 10.2.2 program, to obtain the geodatabases and geospatial matrices that served as cartographic input for the multi-criteria analysis. Based on the geospatial matrices and vector data, raster data were generated, which were used in the modeling with geo-statistical algorithms and potential zones were identified from a structured language. The result of the modeling regarding the suitability of the soil generated two classes with six levels of suitability: land for basic crops and for the cultivation of species of industrial importance and two climate change scenarios, current and future.

Projection of Climate Change Scenarios in the Kabul River Basin, Afghanistan

Projection of Climate Change Scenarios in the Kabul River Basin, Afghanistan

Projection of Climate Change Scenarios in Different Temperature Zones in the Eastern Monsoon Region, China

The Eastern Monsoon Region of China is sensitive to climate change because of its special location. In this study, the Automated Statistical Downscaling (ASD) tool was used to simulate and project future climate change scenarios in different temperate zones in the Eastern Monsoon Region of China. The performances of the single General Circulation Model (GCM) and the GCMs ensemble from Coupled Model Inter-comparison Project Phase 5 (CMIP5) were compared, and the capability of the ASD model was evaluated. The simple mathematical averaging ensemble of GCMs is superior to the single GCM and to the other two weighted ensembles. The ASD model was capable of presenting the temporal and spatial variation of four variables (precipitation, mean air temperature, maximum and minimum air temperature) during both the calibration and validation periods. The performance of the ASD model varied among the different temperate zones. In the simulated future scenarios, the air temperature in the four zones showed an upward trend. Except for the subtropical zone, there was a tendency for increased precipitation in both the warm temperate zone and the cold temperate and middle temperate zones. Of particular interest is that, in the subtropical zone, the precipitation will decline in the future, whereas the air temperature (especially the maximum air temperature) will increase, which may put more pressure on water resource situations in this area.

Grassland production under global change scenarios for New Zealand pastoral agriculture

Abstract. We adapt and integrate the Biome-BGC and Land Use in Rural New Zealand models to simulate pastoral agriculture and to make land-use change, intensification of agricultural activity and climate change scenario projections of New Zealand's pasture production at time slices centred on 2020, 2050 and 2100, with comparison to a present-day baseline. Biome-BGC model parameters are optimised for pasture production in both dairy and sheep/beef farm systems, representing a new application of the Biome-BGC model. Results show up to a 10% increase in New Zealand's national pasture production in 2020 under intensification and a 1–2% increase by 2050 from economic factors driving land-use change. Climate change scenarios using statistically downscaled global climate models (GCMs) from the IPCC Fourth Assessment Report also show national increases of 1–2% in 2050, with significant regional variations. Projected out to 2100, however, these scenarios are more sensitive to the type of pasture system and the severity of warming: dairy systems show an increase in production of 4% under mild change but a decline of 1% under a more extreme case, whereas sheep/beef production declines in both cases by 3 and 13%, respectively. Our results suggest that high-fertility systems such as dairying could be more resilient under future change, with dairy production increasing or only slightly declining in all of our scenarios. These are the first national-scale estimates using a model to evaluate the joint effects of climate change, CO2 fertilisation and N-cycle feedbacks on New Zealand's unique pastoral production systems that dominate the nation's agriculture and economy. Model results emphasise that CO2 fertilisation and N-cycle feedback effects are responsible for meaningful differences in agricultural systems. More broadly, we demonstrate that our model output enables analysis of decoupled land-use change scenarios: the Biome-BGC data products at a national or regional level can be re-sampled quickly and cost-effectively for specific land-use change scenarios and future projections.

Impacts of 21st‐Century Climate Change on Hydrologic Extremes in the Pacific Northwest Region of North America

AbstractClimate change projections for the Pacific Northwest (PNW) region of North America include warmer temperatures (T), reduced precipitation (P) in summer months, and increasedPduring all other seasons. Using a physically based hydrologic model and an ensemble of statistically downscaled global climate model scenarios produced by the Columbia Basin Climate Change Scenarios Project, we examine the nature of changing hydrologic extremes (floods and low flows) under natural conditions for about 300 river locations in thePNW. The combination of warming, and shifts in seasonalPregimes, results in increased flooding and more intense low flows for most of the basins in thePNW. Flood responses depend on average midwinterTand basin type. Mixed rain and snow basins, with average winter temperatures near freezing, typically show the largest increases in flood risk because of the combined effects of warming (increasing contributing basin area) and more winterP. Decreases in low flows are driven by loss of snowpack, drier summers, and increasing evapotranspiration in the simulations. Energy‐limited basins on the west side of the Cascades show the strongest declines in low flows, whereas more arid, water‐limited basins on the east side of the Cascades show smaller reductions in low flows. A fine‐scale analysis of hydrologic extremes over the Olympic Peninsula echoes the results for the larger rivers discussed above, but provides additional detail about topographic gradients.

GOTILWA+: un modelo de procesos que evalúa efectos del cambio climático en los bosques y explora alternativas de gestión para su mitigación

Nadal-Sala, D., Sabate, S., Gracia, C. 2013. GOTILWA+: a process-based model that evaluates the effects of climate change on forests and explores forest management options for its mitigation. Ecosistemas 22(3):29-36. Doi.: 10.7818/ECOS.2013.22-3.05. In the current climate change context, it is essential to develop tools able to explore forest ecosystems’ responses to different climate change projections. GOTILWA + is a forest growth process-based model that allows to explore the effects of different climate change scenarios on forests, as well as their responses to different forest management options. Despite Spanish forests are, in general, currently performing as carbon sinks, during the second half of this century, some of them may become net carbon sources. The main cause of this change would be driven by an increased aridity according to climate change scenario projections. Furthermore, for the same reason, the relative amount of evapotranspiration will be also increased due to a rising atmospheric evaporative demand. However, adaptive forest management to climate change would help to increase water use efficiency by forests, as well as to maintain positives its carbon balances.

An Overview of the Columbia Basin Climate Change Scenarios Project: Approach, Methods, and Summary of Key Results

The Columbia Basin Climate Change Scenarios Project (CBCCSP) was conceived as a comprehensive hydrologic database to support climate change planning, impacts assessment, and adaptation in the Pacific Northwest (PNW) by a diverse user community with varying technical capacity over a wide range of spatial scales. The study has constructed a state-of-the-art, end-to-end data processing sequence from “raw” climate model output to a suite of hydrologic modelling products that are served to the user community from a web-accessible database. A calibrated 1/16 degree latitude-longitude resolution implementation of the VIC hydrologic model over the Columbia River basin was used to produce historical simulations and 77 future hydrologic projections associated with three different statistical downscaling methods and three future time periods (2020s, 2040s, and 2080s). Key products from the study include summary data for about 300 river locations in the PNW and monthly Geographic Information System products for 21 hy...

Regional climate models downscaling in the Alpine area with multimodel superensemble

Abstract. The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control period.

Developing climate change scenarios for Tamil Nadu, India using MAGICC/SCENGEN

This paper describes the projection of climate change scenarios under increased greenhouse gas emissions, using the results of atmospheric-ocean general circulation models in the Coupled Model Intercomparison Project phase 3 dataset. A score is given to every model based on global and regional performance. Four out of 20 general circulation models (GCMs) were selected based on skill in predicting observed annual temperature and precipitation conditions. The ensemble of these four models shows superiority over the individual model scores. These models were subjected to increases in future anthropogenic radiative forcings for constructing climate change scenarios. Future climate scenarios for Tamil Nadu were developed with MAGICC/SCENGEN software. Model results show both temperature and precipitation increases under increased greenhouse gas scenarios. Northeast and northwest parts of Tamil Nadu show a greater increase in temperature and precipitation. Seasonally, the maximum rise in temperature occurred during the MAM season, followed by DJF, JJA, and SON. Decreasing trends of precipitation were observed during DJF and MAM.

Hydrological projections of climate change scenarios over the 3H region of China: A VIC model assessment

To examine the potential sensitivity of the Huang‐Huai‐Hai Plain (3H) region of China to potential changes in future precipitation and temperature, a hydrological evaluation using the VIC hydrological model under different climate scenarios was carried out. The broader perspective is providing a scientific background for the adaptation in water resource management and rural development to climate change. Twelve climate scenarios were designed to account for possible variations in the future with respect to the baseline of historic climate patterns. Results from the six representative types of climate scenarios (+2°C and +5°C warming, and 0%, +15%, −15% change in precipitation) show that rising temperatures for normal precipitation and for wet scenarios (+15% precipitation) yield greater increased evapotranspiration in the south than in the north, which is confirmed by the remaining six scenarios described below. For a 15% change in precipitation, the largest increase or decrease of evapotranspiration occurs between 33 and 36°N and west of 118°E, a region where evapotranspiration is sensitive to precipitation variation and is affected by the amount of water available for evaporation. Rising temperatures can lead to a south‐to‐north decreasing gradient of surface runoff. The six scenarios yield a large variation of runoff in the southern end of the 3H, which means that this zone is sensitive to climate change through surface runoff change. The Jiangsu province in the southeastern part of the 3H region shows an obvious sensitivity in soil moisture to climate change. On a regional mean scale, the hydrological change induced by the increasing precipitation from 15% to 30% is more obvious than that induced by greater warming of +5°C relative to +2°C. These simulations identify key regions of sensitivity in hydrological variation to climate change in the provinces of 3H, which can be used as guides in implementing adaptation.

Assessment of meteorological climate models as inputs for coastal studies

Modeling studies of future changes in coastal hydrodynamics, in terms of storm surges and wave climate, need appropriate wind and atmospheric forcings, a necessary requirement for the realistic reproduction of the statistics and the resolution of small scale features. This work compares meteorological results from different climate models in the Mediterranean area, with a focus on the Adriatic Sea, in order to assess their capability to reproduce coastal meteorological features and their possibility to be used as forcings for hydrodynamic simulations. Five meteorological datasets are considered. They are obtained from two regional climate models, implemented with different spatial resolutions and setups and are downscaled from two different global climate models. Wind and atmospheric pressure fields are compared with measurements at four stations along the Italian Adriatic coast. The analysis is carried out both on simulations of the control period 1960–1990 and on the A1B Intergovernmental Panel for Climate Change scenario projections (2070–2100), highlighting the ability of each model in reproducing the statistical coastal meteorological behavior and possible changes. The importance of simulated global- and regional-scale meteorological processes, in terms of correct spatial resolution of the phenomena, is also discussed. Within the Adriatic Sea, the meteorological climate is influenced by the local orography that controls the strengthening of north-eastern katabatic winds like Bora. Results show indeed that the increase in spatial resolution provides a more realistic wind forcing for the hydrodynamic simulations. Moreover, the chosen setup and the global climate models that drive the regional downscalings appear to play an important role in reproducing correct atmospheric pressure fields. The comparison between scenario and control simulations shows a small increase in the mean atmospheric pressure values, while a decrease in mean wind speed and in extreme wind events is observed, particularly for the datasets with higher spatial resolution. Finally, results suggest that an ensemble of downscaled climate models is likely to provide the most suitable climatic forcings (wind and atmospheric pressure fields) for coastal hydrodynamic modeling.

Habitat preferences of Maculinea arion and its Myrmica host ants: implications for habitat management in Italian Alps

Projections of climate-change scenarios indicate that many Maculinea arion populations will disappear from Europe over the next 50 years. Extinctions will be particularly concentrated around the southern limits of the species’ range, such as the Italian peninsula, except mountain populations, mainly in the Alps. M. arion is a social parasite of Myrmica ants and its survival depends on the presence and abundance of two resources, i.e. (1) a specific larval foodplant and (2) a suitable Myrmica host ant. We collected data on Thymus plants distribution, Myrmica ants abundance, turf height around Myrmica nests, distance between nests and the closest thyme plant (Thymus pulegioides), and vegetation structure at 14 patches of a M. arion fragmented population occurring in the Western Italian Alps (Val Ferret: Aosta). We found that patches with the highest abundance of M. arion had significantly higher foodplant abundance. Among 407 nests belonging to nine Myrmica species, we found M. arion larvae in one Myrmica lonae and in two Myrmica sulcinodis nests. The distribution of M. sulcinodis nests showed the best spatial overlap with Thymus plants. M. sulcinodis was also significantly more abundant on pastures showing high M. arion density, and therefore offered higher adoption probabilities to develop butterfly larvae. On M. arion habitat patches, the mean turf height around Myrmica nests varied from 10.5 to 22.3 cm and best matched the habitat requirements of T. pulegioides. Thus, we suggest that extensive grazing is needed to maintain the two most important resources for M. arion. Moreover, patches where M. arion was abundant included more numerous plant species characteristic of these mountain pastures, as well as higher plant diversity (Shannon index). As a consequence, M. arion represents an umbrella species and a good indicator for the conservation status of mountain grasslands.

The Wet and Dry Spells across India during 1951–2007

Abstract Characteristics of wet spells (WSs) and intervening dry spells (DSs) are extremely useful for water-related sectors. The information takes on greater significance in the wake of global climate change and climate-change scenario projections. The features of 40 parameters of the rainfall time distribution as well as their extremes have been studied for two wet and dry spells for 19 subregions across India using gridded daily rainfall available on 1° latitude × 1° longitude spatial resolution for the period 1951–2007. In a low-frequency-mode, intra-annual rainfall variation, WS (DS) is identified as a “continuous period with daily rainfall equal to or greater than (less than) daily mean rainfall (DMR) of climatological monsoon period over the area of interest.” The DMR shows significant spatial variation from 2.6 mm day−1 over the extreme southeast peninsula (ESEP) to 20.2 mm day−1 over the southern-central west coast (SCWC). Climatologically, the number of WSs (DSs) decreases from 11 (10) over the extreme south peninsula to 4 (3) over northwestern India as a result of a decrease in tropical and oceanic influences. The total duration of WSs (DSs) decreases from 101 (173) to 45 (29) days, and the duration of individual WS (DS) from 12 (18) to 7 (11) days following similar spatial patterns. Broadly, the total rainfall of wet and dry spells, and rainfall amount and rainfall intensity of actual and extreme wet and dry spells, are high over orographic regions and low over the peninsula, Indo-Gangetic plains, and northwest dry province. The rainfall due to WSs (DSs) contributes ∼68% (∼17%) to the respective annual total. The start of the first wet spell is earlier (19 March) over ESEP and later (22 June) over northwestern India, and the end of the last wet spell occurs in reverse, that is, earlier (12 September) from northwestern India and later (16 December) from ESEP. In recent years/decades, actual and extreme WSs are slightly shorter and their rainfall intensity higher over a majority of the subregions, whereas actual and extreme DSs are slightly (not significantly) longer and their rainfall intensity weaker. There is a tendency for the first WS to start approximately six days earlier across the country and the last WS to end approximately two days earlier, giving rise to longer duration of rainfall activities by approximately four days. However, a spatially coherent, robust, long-term trend (1951–2007) is not seen in any of the 40 WS/DS parameters examined in the present study.

Dynamic adaptation of maize and wheat production to climate change

Agriculture represents the main source of livelihood for small scale farmers, and a significant fraction of the gross domestic product in the case of intensive commercial agriculture. Because crop performance at the end of a growing season is strongly linked to the observed meteorological conditions, agricultural systems have been one of the main subjects of analysis to understand the impacts of both climatic variability and climatic change. As climate scientists make progress understanding the key elements of the atmosphere and provide with better projections of climate change scenarios, more effort is devoted to impact assessment and the evaluation of adaptation strategies to reduce vulnerability of crops and farmers. The objective of this work was to document the impacts of climate change on maize and wheat yields in Chile as well as to describe the dynamics of adaptation (i.e. changes in management decisions over time) that will take place, considering that farmers can “learn” from previous crop yield outcomes. Yield outcomes were obtained using a crop simulation model run under climate change scenarios based on HadCM3 projections. A simple decision model for a risk neutral farmer was used to investigate changes in optimum management decisions over time. Maize showed yield reductions in the order of 5% to 10%. Under irrigation, the best alternative for adaptation corresponded to adjustments in sowing dates. In the case of winter wheat significant yield reductions were observed for the no adaptation case. Because this crop showed positive responses to the increase of carbon dioxide, adaptation strategies were very effective counterbalancing the impacts of a warmer and drier environment. Dynamic adaptation was referred here to the introduction of small adjustments in management based on previous observed changes in productivity. This type of adaptation strategy outperformed prescriptive decisions based on historical or projected climate change scenarios, since it was sufficiently flexible to maintain near optimum economic performance over time, as climate varied from baseline to projected future conditions.

Potential change in lodgepole pine site index and distribution under climatic change in Alberta

We estimated the impact of global climate change on lodgepole pine ( Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) site productivity in Alberta based on the Alberta Climate Model and the A2 SRES climate change scenario projections from three global circulation models (CGCM2, HADCM3, and ECHAM4). Considerable warming is apparent in all three models. On average, the increases in mean GDD5 (growing degree-days >5 °C) are 18%, 38%, and 65% by the 2020s, 2050s, and 2080s, respectively. Change in precipitation is essentially nil. This results in proportional increases in dryness index. We used the dryness index to predict the potential future range and GDD5 to predict its potential productivity. Generally, lodgepole pine site index is predicted to increase steadily by 3 m for each 30-year period. Offsetting this increase is a large reduction in suitable area as drying increases. At first, the warming increases the potential range up to 67% by the 2020s but then shrinks from 34% to 58% of its current area by 2080. Such major changes will need to be considered when setting long-term forest management plans. The increased risk of both wildfire and insect outbreaks further compounds this planning problem, especially because these disturbance events can interact and further increase risk.

Performance of High Arctic tundra plants improved during but deteriorated after exposure to a simulated extreme temperature event.

Arctic ecosystems are known to be extremely vulnerable to climate change. As the Intergovernmental Panel on Climate Change scenarios project extreme climate events to increase in frequency and severity, we exposed High Arctic tundra plots during 8 days in summer to a temperature rise of approximately 9°C, induced by infrared irradiation, followed by a recovery period. Increased plant growth rates during the heat wave, increased green cover at the end of the heat wave and higher chlorophyll concentrations of all four predominating species (Salix arctica Pall., Arctagrostis latifolia Griseb., Carex bigelowii Torr. ex Schwein and Polygonum viviparum L.) after the recovery period, indicated stimulation of vegetative growth. Improved plant performance during the heat wave was confirmed at plant level by higher leaf photochemical efficiency (Fv /Fm ) and at ecosystem level by increased gross canopy photosynthesis. However, in the aftermath of the temperature extreme, the heated plants were more stressed than the unheated plants, probably because they acclimated to warmer conditions and experienced the return to (low) ambient as stressful. We also calculated the impact of the heat wave on the carbon balance of this tundra ecosystem. Below- and aboveground respiration were stimulated by the instantaneous warmer soil and canopy, respectively, outweighing the increased gross photosynthesis. As a result, during the heat wave, the heated plots were a smaller sink compared with their unheated counterparts, whereas afterwards the balance was not affected. If other High Arctic tundra ecosystems react similarly, more frequent extreme temperature events in a future climate may shift this biome towards a source. It is uncertain, however, whether these short-term effects will hold when C exchange rates acclimate to higher average temperatures.