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      Refugee settlements are highly exposed to extreme weather conditions

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          Significance

          Refugee settlements are often located in countries most vulnerable to climate variability. This article provides a systematic analysis examining the exposure to slow- and rapid-onset events of the 20 largest refugee settlements worldwide. We find that refugee populations in the settlements are highly exposed to extreme weather conditions, particularly low rainfall, high temperatures, and extreme rainfall (in the case of Bangladesh). This high level of exposure, in combination with often-limited abilities to cope and adapt, enhances the vulnerability of already-marginalized populations and their host communities, and reduces their ability to create sustainable livelihoods. Climate adaptation and sustainable development policies should therefore strive for the inclusion of displaced populations, in order to create equitable sustainable development pathways in refugee-hosting countries.

          Abstract

          Involuntary displacement from conflict and other causes leads to clustering of refugees and internally displaced people, often in long-term settlements. Within refugee-hosting countries, refugee settlements are frequently located in isolated and remote areas, characterized by poor-quality land and harsh climatic conditions. Yet, the exposure of refugee settlements to climatic events is underresearched. In this article, we study the exposure of the 20 largest refugee settlements worldwide to extreme variations in climatic conditions. The analysis integrates exposure of camp locations compared to the national trends for both slow- and rapid-onset events and includes descriptive statistics, signal-to-noise analyses, and trend analyses. Our findings show that most refugee settlements included face relatively high exposure to slow-onset events, including high temperatures (for settlements in Kenya, Ethiopia, Rwanda, Sudan, and Uganda), low temperatures (in the case of Jordan and Pakistan), and low levels of rainfall (in Ethiopia, Rwanda, Kenya, and Uganda) compared to national averages. Our findings for rapid-onset events—heatwaves, coldwaves, and extreme rainfall—are less conclusive compared to country trends, although we find relatively high exposure to extreme rainfall in Cox’s Bazar, Bangladesh. Our analyses confirm that refugee populations are exposed to extreme weather conditions postdisplacement, which, in combination with their sociopolitical exclusion, poses a threat to well-being and increased marginalization. Our findings call for an inclusive and integrated approach, including refugees and their host communities, in designing climate adaptation and sustainable development policies, in order to promote equitable sustainable development pathways in refugee-hosting countries.

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          Most cited references32

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          Is Open Access

          Present and future Köppen-Geiger climate classification maps at 1-km resolution

          We present new global maps of the Köppen-Geiger climate classification at an unprecedented 1-km resolution for the present-day (1980–2016) and for projected future conditions (2071–2100) under climate change. The present-day map is derived from an ensemble of four high-resolution, topographically-corrected climatic maps. The future map is derived from an ensemble of 32 climate model projections (scenario RCP8.5), by superimposing the projected climate change anomaly on the baseline high-resolution climatic maps. For both time periods we calculate confidence levels from the ensemble spread, providing valuable indications of the reliability of the classifications. The new maps exhibit a higher classification accuracy and substantially more detail than previous maps, particularly in regions with sharp spatial or elevation gradients. We anticipate the new maps will be useful for numerous applications, including species and vegetation distribution modeling. The new maps including the associated confidence maps are freely available via www.gloh2o.org/koppen.
            • Record: found
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            Is Open Access

            Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes

            The frequency of climate extremes will change in response to shifts in both mean climate and climate variability. These individual contributions, and thus the fundamental mechanisms behind changes in climate extremes, remain largely unknown. Here we apply the probability ratio concept in large-ensemble climate simulations to attribute changes in extreme events to either changes in mean climate or climate variability. We show that increased occurrence of monthly high-temperature events is governed by a warming mean climate. In contrast, future changes in monthly heavy-precipitation events depend to a considerable degree on trends in climate variability. Spatial variations are substantial however, highlighting the relevance of regional processes. The contributions of mean and variability to the probability ratio are largely independent of event threshold, magnitude of warming and climate model. Hence projections of temperature extremes are more robust than those of precipitation extremes, since the mean climate is better understood than climate variability.
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              • Abstract: not found
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              Environmental Causes and Impact of Refugee Movements: A Critique of the Current Debate

                Author and article information

                Contributors
                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                5 June 2023
                16 January 2024
                5 June 2023
                : 121
                : 3
                : e2206189120
                Affiliations
                [1] aUnited Nations University–Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT), Maastricht University , Maastricht, 6211 LK, the Netherlands
                [2] bFaculty of Technology, Policy and Management, Delft University of Technology , Delft, 2628 CB, the Netherlands
                [3] cSchool of Business and Economics, Maastricht University , Maastricht, 6211 LK, the Netherlands
                Author notes
                1To whom correspondence may be addressed. Email: Sonja.fransen@ 123456maastrichtuniversity.nl .

                Edited by William Clark, Harvard University, Cambridge, MA; received May 7, 2022; accepted November 11, 2022

                Author information
                https://orcid.org/0000-0001-5989-3446
                https://orcid.org/0000-0002-8721-8314
                Article
                202206189
                10.1073/pnas.2206189120
                10801877
                37276435
                a1357068-64d9-44ec-81d1-bea98a1adb82
                Copyright © 2023 the Author(s). Published by PNAS.

                This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                : 07 May 2022
                : 11 November 2022
                Page count
                Pages: 9, Words: 5173
                Categories
                research-article, Research Article
                554, Special Feature: Migration and Sustainability
                sustainability-soc, Sustainability Science
                554
                9
                Social Sciences
                Sustainability Science
                Migration and Sustainability
                Custom metadata
                free

                refugee settlements,extreme weather conditions,exposure,signal-to-noise analysis

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