Global predictability of temperature extremes
Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2018-01-01
|
| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/aab94a |
| _version_ | 1797748281294454784 |
|---|---|
| author | Erin Coughlan de Perez Maarten van Aalst Konstantinos Bischiniotis Simon Mason Hannah Nissan Florian Pappenberger Elisabeth Stephens Ervin Zsoter Bart van den Hurk |
| author_facet | Erin Coughlan de Perez Maarten van Aalst Konstantinos Bischiniotis Simon Mason Hannah Nissan Florian Pappenberger Elisabeth Stephens Ervin Zsoter Bart van den Hurk |
| author_sort | Erin Coughlan de Perez |
| collection | DOAJ |
| description | Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world’s population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations. |
| first_indexed | 2024-03-12T16:03:39Z |
| format | Article |
| id | doaj.art-72b0c7f00dcc4f248e49d3687601f0cb |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T16:03:39Z |
| publishDate | 2018-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-72b0c7f00dcc4f248e49d3687601f0cb2023-08-09T14:31:57ZengIOP PublishingEnvironmental Research Letters1748-93262018-01-0113505401710.1088/1748-9326/aab94aGlobal predictability of temperature extremesErin Coughlan de Perez0https://orcid.org/0000-0001-7645-5720Maarten van Aalst1https://orcid.org/0000-0003-0319-5627Konstantinos Bischiniotis2Simon Mason3Hannah Nissan4Florian Pappenberger5https://orcid.org/0000-0003-1766-2898Elisabeth Stephens6https://orcid.org/0000-0002-5439-7563Ervin Zsoter7Bart van den Hurk8Red Cross Red Crescent Climate Centre , The Hague, The Netherlands; International Research Institute for Climate and Society , Columbia University, New York, United States of America; Institute for Environmental Studies , VU University Amsterdam, The Netherlands; Author to whom any correspondence should be addressed.Red Cross Red Crescent Climate Centre , The Hague, The Netherlands; Institute for Environmental Studies , VU University Amsterdam, The Netherlands; Department of Science, Technology, Engineering and Public Policy, University College London , London, United KingdomInstitute for Environmental Studies , VU University Amsterdam, The NetherlandsInternational Research Institute for Climate and Society , Columbia University, New York, United States of AmericaInternational Research Institute for Climate and Society , Columbia University, New York, United States of AmericaEuropean Centre for Medium-Range Weather Forecasts , Reading, United KingdomSchool of Archaeology, Geography and Environmental Science, University of Reading , Reading, United KingdomEuropean Centre for Medium-Range Weather Forecasts , Reading, United KingdomSchool of Archaeology, Geography and Environmental Science, University of Reading , Reading, United Kingdom; Royal Netherlands Meteorological Institute (KNMI) , De Bilt, NetherlandsExtreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world’s population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations.https://doi.org/10.1088/1748-9326/aab94aheatcoldextremesclimate risk managementforecast verificationclimate |
| spellingShingle | Erin Coughlan de Perez Maarten van Aalst Konstantinos Bischiniotis Simon Mason Hannah Nissan Florian Pappenberger Elisabeth Stephens Ervin Zsoter Bart van den Hurk Global predictability of temperature extremes Environmental Research Letters heat cold extremes climate risk management forecast verification climate |
| title | Global predictability of temperature extremes |
| title_full | Global predictability of temperature extremes |
| title_fullStr | Global predictability of temperature extremes |
| title_full_unstemmed | Global predictability of temperature extremes |
| title_short | Global predictability of temperature extremes |
| title_sort | global predictability of temperature extremes |
| topic | heat cold extremes climate risk management forecast verification climate |
| url | https://doi.org/10.1088/1748-9326/aab94a |
| work_keys_str_mv | AT erincoughlandeperez globalpredictabilityoftemperatureextremes AT maartenvanaalst globalpredictabilityoftemperatureextremes AT konstantinosbischiniotis globalpredictabilityoftemperatureextremes AT simonmason globalpredictabilityoftemperatureextremes AT hannahnissan globalpredictabilityoftemperatureextremes AT florianpappenberger globalpredictabilityoftemperatureextremes AT elisabethstephens globalpredictabilityoftemperatureextremes AT ervinzsoter globalpredictabilityoftemperatureextremes AT bartvandenhurk globalpredictabilityoftemperatureextremes |