scholarly journals Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention

2019 ◽  
Author(s):  
Sadie J. Ryan ◽  
Catherine A. Lippi ◽  
Fernanda Zermoglio
Keyword(s):  
Climate Change ◽  
At Risk ◽  
Malaria Transmission ◽  
Climate Model ◽  
Population Projections ◽  
Eastern Africa ◽  
Parasite Development ◽  
Worst Case ◽  
Population At Risk ◽  
Recent Climate

AbstractBackgroundMalaria continues to be a disease of massive burden in Africa, and the public health resources targeted at surveillance, prevention, control, and intervention comprise large outlays of expense. Malaria transmission is largely constrained by the suitability of the climate for Anopheles mosquitoes and Plasmodium parasite development. Thus, as climate changes, we will see shifts in geographic locations suitable for transmission, and differing lengths of seasons of suitability, which will require changes in the types and amounts of resources.MethodsWe mapped the shifting geographic risk of malaria transmission, in context of changing seasonality (i.e. endemic to epidemic, and vice-versa), and the number of people affected. We applied a temperature-dependent model of malaria transmission suitability to continental gridded climate data for multiple future climate model projections. We aligned the resulting outcomes with programmatic needs to provide summaries at national and regional scales for the African continent. Model outcomes were combined with population projections to estimate the population at risk at three points in the future, 2030, 2050, and 2080, under two scenarios of greenhouse gas emissions (RCP4.5 and RCP8.5).ResultsGeographic shifts in endemic and seasonal suitability for malaria transmission were observed across all future scenarios of climate change. The worst-case regional scenario (RCP8.5) of climate change places an additional 75.9 million people at risk from endemic (10-12 months) exposure to malaria transmission in Eastern and Southern Africa by the year 2080, with the greatest population at risk in Eastern Africa. Despite a predominance of reduction in season length, a net gain of 51.3 million additional people will be put at some level of risk in Western Africa by midcentury.ConclusionsThis study provides an updated view of potential malaria geographic shifts in Africa under climate change for the more recent climate model projections (AR5), and a tool for aligning findings with programmatic needs at key scales for decision makers. In describing shifting seasonality, we can capture transitions between endemic and epidemic risk areas, to facilitate the planning for interventions aimed at year-round risk versus anticipatory surveillance and rapid response to potential outbreak locations.

scholarly journals Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Joseph Leedale ◽  
Adrian M. Tompkins ◽  
Cyril Caminade ◽  
Anne E. Jones ◽  
Grigory Nikulin ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Climate Projections ◽  
Model Ensemble ◽  
East African Community ◽  
Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

scholarly journals Climate change and variability: a review of what is known and ought to be known for Uganda

2018 ◽  
Vol 10 (5) ◽  
pp. 752-771 ◽  
Author(s):  
Francis Wasswa Nsubuga ◽  
Hannes Rautenbach
Keyword(s):  
Climate Change ◽  
Agricultural Sector ◽  
Climate Model ◽  
Regional Climate ◽  
Future Research ◽  
Daily Maximum ◽  
Inter Tropical Convergence Zone ◽  
Content Type ◽  
Climate Change And Variability ◽  
Recent Climate

Purpose In view of the consensus that climate change is happening, scientists have documented several findings about Uganda’s recent climate, as well as its variability and change. The purpose of this study is to review what has been documented, thus it gives an overview of what is known and seeks to explain the implications of a changing climate, hence what ought to be known to create a climate resilient environment. Design/methodology/approach Terms such as “climate”, “climate change” and “climate variability” were identified in recent peer-reviewed published literature to find recent climate-related literature on Uganda. Findings from independent researchers and consultants are incorporated. Data obtained from rainfall and temperature observations and from COSMO-CLM Regional Climate Model-Coordinated Regional Climate Downscaling Experiment (CCLM CORDEX) data, European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data and Global Precipitation Climatology Centre (GPCC) have been used to generate spatial maps, seasonal outputs and projections using GrADS 2.02 and Geographic Information System (GIS) software for visualization. Findings The climate of Uganda is tropical in nature and influenced by the Inter-Tropical Convergence Zone (ITCZ), varied relief, geo-location and inland lakes, among other factors. The impacts of severe weather and climate trends and variability have been documented substantially in the past 20-30 years. Most studies indicated a rainfall decline. Daily maximum and minimum temperatures are on the rise, while projections indicate a decrease in rainfall and increase in temperature both in the near and far future. The implication of these changes on society and the economy are discussed herein. Cost of inaction is expected to become huge, given factors like, the growing rate of the population and the slow expanding economy experienced in Uganda. Varied forms of adaptation to the impacts of climate change are being implemented, especially in the agricultural sector and at house hold level, though not systematically. Originality/value This review of scientific research findings aims to create a better understanding of the recent climate change and variability in Uganda and provides a baseline of summarized information for use in future research and actions.

Degrading permafrost threatens Arctic nature and built environment

2020 ◽  
Author(s):  
Jan Hjort ◽  
Olli Karjalainen ◽  
Juha Aalto ◽  
Sebastian Westermann ◽  
Vladimir Romanovsky ◽  
...  
Keyword(s):  
Climate Change ◽  
At Risk ◽  
High Resolution ◽  
Human Activities ◽  
Environmental Data ◽  
The Arctic ◽  
Permafrost Degradation ◽  
Engineering Structures ◽  
Near Surface ◽  
Population At Risk

<p>Arctic earth surface systems are undergoing unprecedented changes, with permafrost thaw as one of the most striking examples. Permafrost is critical because it controls ecosystem processes, human activities, and landscape dynamics in the north. Degradation (i.e. warming and thawing) of permafrost is related to several hazards, which may pose a serious risk to humans and the environment. Thaw of ice-rich permafrost increases ground instability, landslides, and infrastructure damages. Degrading permafrost may lead to the release of significant amounts of greenhouse gases to the atmosphere and threatens also biodiversity, geodiversity and ecosystem services. Thawing permafrost may even jeopardize human health. Consequently, a deeper understanding of the hazards and risks related to the degradation of permafrost is fundamental for science and society.</p><p>To address climate change effects on infrastructure and human activities, we (i) mapped circumpolar permafrost hazard areas and (ii) quantified critical engineering structures and population at risk by mid-century. We used observations of ground thermal regime, geospatial environmental data, and statistically-based ensemble methods to model the current and future near-surface permafrost extent at ca. 1 km resolution. Using the forecasts of ground temperatures, a consensus of three geohazard indices, and geospatial data we quantified the amount and proportion of infrastructure elements and population at risk owing to climate change. We show that ca. 70% of current infrastructure and population in the permafrost domain are in areas with high potential for thaw of near-surface permafrost by 2050. One-third of fundamental infrastructure is located in high hazard regions where the ground is susceptible to thaw-related ground instability. Owing to the observed data-related and methodological limitations we call for improvements in the circumpolar hazard mappings and infrastructure risk assessments.</p><p>To successfully manage climate change impacts and support sustainable development in the Arctic, it is critical to (i) produce high-resolution geospatial datasets of ground conditions (e.g., content of organic material and ground ice), (ii) develop further high-resolution permafrost modelling, (iii) comprehensively map permafrost degradation-related hazards, and (iv) quantify the amount and economic value of infrastructure and natural resources at risk across the circumpolar permafrost area.</p>

Systematic review and meta-analysis of global food security projections to 2050

2021 ◽  
Author(s):  
Michiel van Dijk ◽  
Tom Morley ◽  
Marie Luise Rau ◽  
Yashar Saghai
Keyword(s):  
Climate Change ◽  
At Risk ◽  
Food Security ◽  
Meta Analysis ◽  
Food Demand ◽  
Climate Change Scenarios ◽  
Policy Debate ◽  
Population At Risk ◽  
Global Food Security ◽  
Global Food

Abstract Ending hunger and achieving food security - one of the UN sustainable development goals - is a major global challenge. To inform the policy debate, quantified global scenarios and projections are used to assess long-term future global food security under a range of socio-economic and climate change scenarios. However, due to differences in model design and scenario assumptions, there is uncertainty about the range of food security projections and outcomes. We conducted a systematic literature review and meta-analysis to assess the range of future global food security projections to 2050. We reviewed 57 global food security projection and quantitative scenario studies that have been published over the last two decades and discussed the methodology, underlying drivers, indicators and projections. We harvested quantitative information from 26 studies to compare future trends of the two most used global food security indicators: per capita food demand (593 projections) and population at risk of hunger (358 projections). We found that across five representative scenarios that span divergent but plausible socio-economic futures total global food demand is expected to increase by +35% to +56% between 2010 and 2050, while population at risk of hunger is expected to change by -91% to +8% over the same period. If climate change is taken into account the range changes slightly (+30% to +62% for total food demand and -91% to +30% for population at risk of hunger) but overall we do not find statistical support for differences in projections with and without climate change. Finally, our review suggests that current modeling approaches can be improved by better incorporating several options that have been proposed to tackle global food security, in particular aquaculture and ‘future foods’, and expand the number of indicators to better cover the multiple dimensions of food security. The results of our review can be used to benchmark new global food security projections and quantitative scenario studies and inform policy analysis and the public debate on the future of food.

scholarly journals Impact analysis of climate change for an Alpine catchment using high resolution dynamic downscaling of ECHAM4 time slices

2004 ◽  
Vol 8 (6) ◽  
pp. 1031-1045 ◽  
Author(s):  
H. Kunstmann ◽  
K. Schneider ◽  
R. Forkel ◽  
R. Knoche
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Climate Scenario ◽  
Dynamic Downscaling ◽  
Hydrological Simulation ◽  
Recent Climate

Abstract. Global climate change affects spatial and temporal patterns of precipitation and so has a major impact on surface and subsurface water balances. While global climate models are designed to describe climate change on global or continental scales, their resolution is too coarse for them to be suitable for describing regional climate change. Therefore, regional climate models are applied to downscale the coarse meteorological fields to a much higher spatial resolution to take account of regional climate phenomena. The changes of atmospheric state due to regional climate change must be translated into surface and sub-surface water fluxes so that the impact on water balances in specific catchments can be investigated. This can be achieved by the coupled regional climatic/hydrological simulations presented here. The non-hydrostatic regional climate model MCCM was used for dynamic downscaling for two time slices of a global climate model simulation with the GCM ECHAM4 (IPCC scenario IS92a, "business as usual") from 2.8° × 2.8° to 4 × 4 km2 resolution for the years 1991–1999 and 2031–2039. This allowed derivation of detailed maps showing changes in precipitation and temperature in a region of southern Germany and the central Alps. The performance of the downscaled ECHAM4 to reproduce the seasonality of precipitation in central Europe for the recent climate was investigated by comparison with dynamically downscaled ECMWF reanalyses in 20 × 20 km2 resolution. The downscaled ECHAM4 fields underestimate precipitation significantly in summer. The ratio of mean monthly downscaled ECHAM4 and ECMWF precipitation showed little variation, so it was used to adjust the course of precipitation for the ECHAM4/MCCM fields before it was applied in the hydrological model. The high resolution meteorological fields were aggregated to 8-hour time steps and applied to the distributed hydrological model WaSiM to simulate the water balance of the alpine catchment of the river Ammer (c. 700 km2) at 100 × 100 m2 resolution. To check the reliability of the coupled regional climatic/hydrological simulation results for the recent climate, they were compared with those of a station-based hydrological simulation for the period 1991–1999. This study shows the changes in the temperature and precipitation distributions in the catchment from the recent climate to the future climate scenario and how these will affect the frequency distribution of runoff. Keywords: coupled climate-hydrology simulations, dynamic downscaling, distributed hydrological modelling, ECHAM4 climate scenario, alpine hydrology

scholarly journals Observed Antarctic sea ice expansion reproduced in a climate model after correcting biases in sea ice drift velocity

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shantong Sun ◽  
Ian Eisenman
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Drift Velocity ◽  
Climate Model ◽  
Future Climate Change ◽  
Antarctic Sea Ice ◽  
Ice Drift ◽  
Recent Climate ◽  
Sea Ice Drift ◽  
The Antarctic

AbstractThe Antarctic sea ice area expanded significantly during 1979–2015. This is at odds with state-of-the-art climate models, which typically simulate a receding Antarctic sea ice cover in response to increasing greenhouse forcing. Here, we investigate the hypothesis that this discrepancy between models and observations occurs due to simulation biases in the sea ice drift velocity. As a control we use the Community Earth System Model (CESM) Large Ensemble, which has 40 realizations of past and future climate change that all undergo Antarctic sea ice retreat during recent decades. We modify CESM to replace the simulated sea ice velocity field with a satellite-derived estimate of the observed sea ice motion, and we simulate 3 realizations of recent climate change. We find that the Antarctic sea ice expands in all 3 of these realizations, with the simulated spatial structure of the expansion bearing resemblance to observations. The results suggest that the reason CESM has failed to capture the observed Antarctic sea ice expansion is due to simulation biases in the sea ice drift velocity, implying that an improved representation of sea ice motion is crucial for more accurate sea ice projections.

scholarly journals Impact of Reference Dataset Selection on RCM Evaluation, Bias Correction, and Resulting Climate Change Signals of Precipitation

2019 ◽  
Vol 20 (9) ◽  
pp. 1813-1828 ◽  
Author(s):  
David Gampe ◽  
Josef Schmid ◽  
Ralf Ludwig
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Regional Scale ◽  
Mapping Method ◽  
Reference Dataset ◽  
Recent Climate ◽  
Observational Uncertainty ◽  
Projected Change

Abstract Gridded datasets of precipitation are of great importance to evaluate recent climate models and are frequently applied to select a subset of available models. As climate models are still prone to biases on the regional scale, gridded datasets are also essential to correct or adjust these biases. Various studies revealed considerable differences, that is, observational uncertainty, in the available gridded datasets of precipitation, especially over complex terrain. This study focuses on the impacts of observational uncertainty on the evaluation, selection, and bias correction of 15 regional climate model (RCM) simulations provided through the EURO-CORDEX initiative over the alpine Adige catchment located in northern Italy. Nine reference datasets originating from observations, reanalysis, and remote sensing are applied to evaluate the performance of RCMs and select a subset based on validity. These reference datasets are then applied to bias correct the RCM ensemble using a standard quantile mapping method, and the resulting changes in the projections are assessed. The presented results show a selection of similar RCMs, indicating that observational uncertainty is lower than model uncertainty. The influence of the choice of the reference dataset on bias correction is negligible for the climate change signals. Small differences in projected change signals can be attributed to model selection. As expected, the choice of the reference dataset strongly influences future projections of precipitation even more pronounced for the extremes. The findings of this study highlight the need to account for observational uncertainty for bias correction of RCM simulations for impact modeling studies.

scholarly journals Climate change threatens Chinook salmon throughout their life cycle

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Lisa G. Crozier ◽  
Brian J. Burke ◽  
Brandon E. Chasco ◽  
Daniel L. Widener ◽  
Richard W. Zabel
Keyword(s):  
Climate Change ◽  
Chinook Salmon ◽  
Climate Model ◽  
Pacific Salmon ◽  
Global Climate ◽  
Global Climate Model ◽  
Climate Impacts ◽  
Future Climate Change ◽  
Life Stages ◽  
Recent Climate

AbstractWidespread declines in Atlantic and Pacific salmon (Salmo salar and Oncorhynchus spp.) have tracked recent climate changes, but managers still lack quantitative projections of the viability of any individual population in response to future climate change. To address this gap, we assembled a vast database of survival and other data for eight wild populations of threatened Chinook salmon (O. tshawytscha). For each population, we evaluated climate impacts at all life stages and modeled future trajectories forced by global climate model projections. Populations rapidly declined in response to increasing sea surface temperatures and other factors across diverse model assumptions and climate scenarios. Strong density dependence limited the number of salmon that survived early life stages, suggesting a potentially efficacious target for conservation effort. Other solutions require a better understanding of the factors that limit survival at sea. We conclude that dramatic increases in smolt survival are needed to overcome the negative impacts of climate change for this threatened species.

Dry season water availability changes attributed to human-induced climate change

2020 ◽  
Author(s):  
Ryan S. Padrón ◽  
Lukas Gudmundsson ◽  
Agnès Ducharne ◽  
David M. Lawrence ◽  
Jiafu Mao ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Water Availability ◽  
Land Surface ◽  
Radiative Forcing ◽  
Climate Model ◽  
Dry Season ◽  
Eastern Africa ◽  
Northern Asia ◽  
Climate Model Simulations

<p><span>Human-induced climate change poses potential impacts on the availability of water resources. Previous assessments of warming-induced changes in dryness, however, are influenced by short observational records and show conflicting results due to uncertainties in the response of evapotranspiration. In this study we use novel observation-based water availability reconstructions from data-driven and land surface models from 1902 to 2014; a period during which the Earth has warmed approximately 1°C relative to pre-industrial conditions. These reconstructions reveal consistent changes in average water availability of the driest month of the year during the last 30 years compared to the first half of the 20<sup>th </sup>century. We conduct a simple attribution approach based on a spatial correlation analysis between the reconstructions and different climate model simulations. Results indicate that the spatial pattern of changes is <em>extremely likely</em> influenced by human-induced greenhouse gas emissions as it is consistent with climate model estimates that include historical radiative forcing, whereas the pattern is not expected from natural climate variability given by climate simulations with greenhouse gas levels set to pre-industrial conditions. Changes in water availability are characterized by drier dry seasons predominantly in extratropical latitudes and including Europe, Western North America, Northern Asia, Southern South America, Australia, and Eastern Africa. Finally, we find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.</span></p>

Impact of Climate Change on Apricot Yield in Turkey in the Near Future

2021 ◽  
Author(s):  
M. Tufan Turp ◽  
Nazan An ◽  
Gökhan Özertan ◽  
M. Levent Kurnaz
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Prunus Armeniaca ◽  
Soil Conditions ◽  
Climate Projections ◽  
Worst Case ◽  
Black Sea Region ◽  
Main Producer

<p>Apricot (<em>Prunus armeniaca</em> L.) is one of the most important export crops in Turkey and Turkey is the leader for both fresh and dried apricots production in the world. Apricot can be grown in all regions of Turkey with climate and vegetation diversities, except in the Eastern Black Sea Region and in the high plateaus of the East Anatolian Region. Malatya is the main producer province, which has good ecological and soil conditions in terms of apricot cultivation with the highest quality in Turkey. However, it is possible to talk about irregularities and decreases in apricot yield due to climate change in the region. Therefore, this study aims to observe climate change impacts on apricot yield in the main producer city, Malatya. Hereunder, climate projections were made at a 10 km horizontal resolution for the future period of 2021-2050 under the “worst-case” scenario (RCP8.5) using a regional climate model (RegCM4.4) for Malatya province considering 13 sub-regions. A statistical model, panel data method-multiple regression model, is designed to observe the effect of climate change and variability on the yield. Results indicate that adverse impacts of climate change on biological development of apricot lead to production irregularities and significant losses in yield in Malatya.</p><p> </p><p>Acknowledgement: This research has been supported by Boğaziçi University Research Fund Grant Number 16763.</p>

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