| 1. |
- An, Dong, et al.
(författare)
-
Extreme precipitation patterns in the Asia-Pacific region and its correlation with El Niño-Southern Oscillation (ENSO)
- 2023
-
Ingår i: Scientific Reports. - 2045-2322. ; 13
-
Tidskriftsartikel (refereegranskat)abstract
- In the Asia-Pacific region (APR), extreme precipitation is one of the most critical climate stressors, affecting 60% of the population and adding pressure to governance, economic, environmental, and public health challenges. In this study, we analyzed extreme precipitation spatiotemporal trends in APR using 11 different indices and revealed the dominant factors governing precipitation amount by attributing its variability to precipitation frequency and intensity. We further investigated how these extreme precipitation indices are influenced by El Niño-Southern Oscillation (ENSO) at a seasonal scale. The analysis covered 465 ERA5 (the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts) study locations over eight countries and regions during 1990-2019. Results revealed a general decrease indicated by the extreme precipitation indices (e.g., the annual total amount of wet-day precipitation, average intensity of wet-day precipitation), particularly in central-eastern China, Bangladesh, eastern India, Peninsular Malaysia and Indonesia. We observed that the seasonal variability of the amount of wet-day precipitation in most locations in China and India are dominated by precipitation intensity in June-August (JJA), and by precipitation frequency in December-February (DJF). Locations in Malaysia and Indonesia are mostly dominated by precipitation intensity in March-May (MAM) and DJF. During ENSO positive phase, significant negative anomalies in seasonal precipitation indices (amount of wet-day precipitation, number of wet days and intensity of wet-day precipitation) were observed in Indonesia, while opposite results were observed for ENSO negative phase. These findings revealing patterns and drivers for extreme precipitation in APR may inform climate change adaptation and disaster risk reduction strategies in the study region.
|
|
| 2. |
- Máñez Costa, Maria, et al.
(författare)
-
Co-production of Climate Services : A diversity of approaches and good practice from the ERA4CS projects (2017–2021)
- 2022
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This guide presents a joint effort of projects funded under the European Research Area for Climate Services (ERA4CS) (http://www.jpi-climate.eu/ERA4CS), a co- funded action initiated by JPI Climate with co-funding by the European Union (Grant 690462), 15 national public Research Funding Organisations (RFOs), and 30 Research Performing Organisations (RPOs) from 18 European countries. This guide sets out to increase the understanding of different pathways, methods, and approaches to improve knowledge co-production of climate services with users as a value-added activity of the ERA4CS Programme.Reflecting on the experiences of 16 of the 26 projects funded under ERA4CS, this guide aims to define and recommend good practices for transdisciplinary knowledge co-production of climate services to researchers, users, funding agencies, and private sector service providers. Drawing on responses from ERA4CS project teams to a questionnaire and interviews, this guide maps the diversity of methods for stakeholder identification, involvement, and engagement. It also conducts an analysis of methods, tools, and mechanisms for engagement as well as evaluation of co-production processes.This guide presents and discusses good practice examples based on the review of the ERA4CS projects, identifying enablers and barriers for key elements in climate service co-production processes. These were: namely (i) Forms of Engagement; (ii) Entry Points for Engagement; and, (iii) Intensity of Involvement. It further outlines key ingredients to enhance the quality of co-producing climate services with users and stakeholders.Based on the analysis of the lessons learned from ERA4CS projects, as well as a review of key concepts in the recent literature on climate service co-production, we provide a set of recommendations for researchers, users, funders and private sector providers of climate services.
|
|
| 3. |
- Adams, Nicholas, et al.
(författare)
-
El Niño Southern Oscillation, monsoon anomaly, and childhood diarrheal disease morbidity in Nepal
- 2022
-
Ingår i: PNAS Nexus. - : Oxford University Press (OUP). - 2752-6542. ; 1:2
-
Tidskriftsartikel (refereegranskat)abstract
- Climate change is adversely impacting the burden of diarrheal diseases. Despite significant reduction in global prevalence, diarrheal disease remains a leading cause of morbidity and mortality among young children in low- and middle-income countries. Previous studies have shown that diarrheal disease is associated with meteorological conditions but the role of large-scale climate phenomena such as El Niño-Southern Oscillation (ENSO) and monsoon anomaly is less understood. We obtained 13 years (2002–2014) of diarrheal disease data from Nepal and investigated how the disease rate is associated with phases of ENSO (El Niño, La Niña, vs. ENSO neutral) monsoon rainfall anomaly (below normal, above normal, vs. normal), and changes in timing of monsoon onset, and withdrawal (early, late, vs. normal). Monsoon season was associated with a 21% increase in diarrheal disease rates (Incident Rate Ratios [IRR]: 1.21; 95% CI: 1.16–1.27). El Niño was associated with an 8% reduction in risk while the La Niña was associated with a 32% increase in under-5 diarrheal disease rates. Likewise, higher-than-normal monsoon rainfall was associated with increased rates of diarrheal disease, with considerably higher rates observed in the mountain region (IRR 1.51, 95% CI: 1.19–1.92). Our findings suggest that under-5 diarrheal disease burden in Nepal is significantly influenced by ENSO and changes in seasonal monsoon dynamics. Since both ENSO phases and monsoon can be predicted with considerably longer lead time compared to weather, our findings will pave the way for the development of more effective early warning systems for climate sensitive infectious diseases.
|
|
| 4. |
- Eggeling, Jakob, et al.
(författare)
-
Spatiotemporal link between El Niño Southern Oscillation (ENSO), extreme heat, and thermal stress in the Asia-Pacific region
- 2024
-
Ingår i: Scientific Reports. - 2045-2322. ; 14:1
-
Tidskriftsartikel (refereegranskat)abstract
- Climate change is closely monitored and numerous studies reports increasing air temperature and weather extremes across the globe. As a direct consequence of the increase of global temperature, the increased heat stress is becoming a global threat to public health. While most climate change and epidemiological studies focus on air temperature to explain the increasing risks, heat strain can be predicted using comprehensive indices such as Universal Thermal Climate Index (UTCI). The Asia-Pacific region is prone to thermal stress and the high population densities in the region impose high health risk. This study evaluated the air temperature and UTCI trends between 1990 and 2019 and found significant increasing trends for air temperature for the whole region while the increases of UTCI are not as pronounced and mainly found in the northern part of the region. These results indicate that even though air temperature is increasing, the risks of heat stress when assessed using UTCI may be alleviated by other factors. The associations between El Niño Southern Oscillation (ENSO) and heat stress was evaluated on a seasonal level and the strongest regional responses were found during December-January (DJF) and March-May (MAM).
|
|
| 5. |
- Eggeling, Jakob, et al.
(författare)
-
Validating an advanced smartphone application for thermal advising in cold environments
- 2023
-
Ingår i: International Journal of Biometeorology. - 1432-1254. ; 67:12, s. 1957-1964
-
Tidskriftsartikel (refereegranskat)abstract
- The ClimApp smartphone application was developed to merge meteorological forecast data with personal information for individualized and improved thermal warning during heat and cold stress and for indoor comfort in buildings. For cold environments, ClimApp predicts the personal thermal stress and strain by the use of the Insulation REQuired model that combines weather and personal physiological data with additional consideration of the Wind Chill index based on the local weather forecast. In this study, we validated the individualized ClimApp index relative to measurements and compared it with the Universal Temperature Climate Index (UTCI). To this aim, 55 participants (27 females) were exposed to at least 1 h in an outdoor environment of 10 °C or below (average 1.4 °C air temperature, 74.9% relative humidity, and 4.7 m/s air velocity) inputting their activity level and clothing insulation as instructed by ClimApp. The UTCI and ClimApp indices were calculated and compared to the participants' perceived thermal sensation. The ClimApp index root mean square deviation (RMSD) was below the standard deviation of the perceived thermal sensation which indicates a valid prediction and the UTCI RMSD was higher than the standard deviation which indicates an invalid prediction. The correlation of ClimApp and UTCI to the perceived thermal sensation was statistically significant for both models.
|
|
| 6. |
- Gao, Chuansi, et al.
(författare)
-
Occupational heat stress assessment and protective strategies in the context of climate change
- 2018
-
Ingår i: International Journal of Biometeorology. - : Springer Science and Business Media LLC. - 1432-1254 .- 0020-7128. ; 62:3, s. 359-371
-
Tidskriftsartikel (refereegranskat)abstract
- Global warming will unquestionably increase the impact of heat on individuals who work in already hot workplaces in hot climate areas. The increasing prevalence of this environmental health risk requires the improvement of assessment methods linked to meteorological data. Such new methods will help to reveal the size of the problem and design appropriate interventions at individual, workplace and societal level. The evaluation of occupational heat stress requires measurement of four thermal climate factors (air temperature, humidity, air velocity and heat radiation); available weather station data may serve this purpose. However, the use of meteorological data for occupational heat stress assessment is limited because weather stations do not traditionally and directly measure some important climate factors, e.g. solar radiation. In addition, local workplace environmental conditions such as local heat sources, metabolic heat production within the human body, and clothing properties, all affect the exchange of heat between the body and the environment. A robust occupational heat stress index should properly address all these factors. This article reviews and highlights a number of selected heat stress indices, indicating their advantages and disadvantages in relation to meteorological data, local workplace environments, body heat production and the use of protective clothing. These heat stress and heat strain indices include Wet Bulb Globe Temperature, Discomfort Index, Predicted Heat Strain index, and Universal Thermal Climate Index. In some cases, individuals may be monitored for heat strain through physiological measurements and medical supervision prior to and during exposure. Relevant protective and preventive strategies for alleviating heat strain are also reviewed and proposed.
|
|
| 7. |
- Gao, Chuansi
(författare)
-
Translating climate service into personalized adaptation strategies to cope with thermal stress (ClimApp)
- 2021
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Climate change has increased the frequency and intensity of extreme weather events. Heat waves and cold spells pose a threat to human health, well-being and productivity. The impact of thermal stress depends on not only climate factors, but also individual factors and vulnerability. Current heat wave early warning systems are mainly based on air temperature. It is necessary to extend and improve current climate services by taking into account individual factors and all thermal climate variables to provide personalized heat-health early warnings to increase thermal resilience. ClimApp is smartphone app developed based on a European project to translate climate service into personalized adaptation strategies to cope with heat and cold stress. The app incorporated more than 10 relevant parameters that determine the heat exchange between human body and the environment. Weather forecast data are automatically extracted from user’s local weather forecast through GPS, as inputs into four human thermal models for hot, moderate and cold environments. The app works globally in a temperature range from -50 to +50 °C. ClimApp is publicly available for Android and iPhone in 10 languages. The App provides personalized health risk warnings and advice for individuals, vulnerable groups and organizations to support decision-making to increase adaptation capacity when extreme weather events. ClimApp was awarded by The World Meteorological Organization for Originality and Innovation.
|
|
| 8. |
- Gudmundsson, Anders, et al.
(författare)
-
Dust in Buildings - A Method for Identifying Particle Sources
- 2005
-
Ingår i: Environmental ergonomics XI : proceedings of the 11th International Conference, 22-26 May, 2005, Ystad, Sweden - proceedings of the 11th International Conference, 22-26 May, 2005, Ystad, Sweden. - 9163170620 ; , s. 507-510
-
Konferensbidrag (refereegranskat)
|
|
| 9. |
- Sharma, Ayushi, et al.
(författare)
-
Characterizing the effects of extreme heat events on all-cause mortality : a case study in Ahmedabad city of India, 2002–2018
- 2024
-
Ingår i: Urban Climate. - 2212-0955. ; 54
-
Tidskriftsartikel (refereegranskat)abstract
- Recent years have seen a rise in extreme heat event (EHE)-related deaths in India. However, the impact of specific temperature thresholds on health risks remains understudied. Using Distributed Lag Non-Linear Models (DLNM), we explored the link between EHEs, defined by various temperature thresholds, and mortality risk in Ahmedabad, India, from 2002 to 2018, considering a 21-day lag. We observed a ‘J'-shaped exposure-response curve, identifying a Minimum Mortality Temperature (MMT) of 26 °C for Ahmedabad. Notably, a higher and sustained risk of all-cause mortality was associated with Tmax > 35 °C. EHEs definition of Tmax ∼ 40 °C (95th percentile) increased all-cause mortality risk by 30% (Relative Risk (RR): 1.30, 95% Confidence Interval (95% CI): 1.26–1.35), with substantially higher risk at Tmax of 45 °C (RR: 3.08, 95% CI: 2.47–3.83). Analysis of attributable fractions (AF) indicated Tmax ≥ 85th percentile contributed most to total mortalities, with an AF of 3.58% (95% CI: 3.20–3.96). Gender-stratified analysis revealed higher risk of EHE-related deaths for females. The highest mortality risk was identified on the same day of exposure and persisted longer during more intense EHEs. The activation of city's heat action plans should consider the significantly elevated mortality risk below the current threshold (∼40 °C) and the persistent risk during high-intensity EHEs.
|
|
| 10. |
- Toftum, Jørn, et al.
(författare)
-
Prediction of indoor air temperature for assessment of people's thermal stress
- 2021
-
Ingår i: 8th International Building Physics Conference IBPC2021.
-
Konferensbidrag (refereegranskat)abstract
- Climate change is expected to increase the frequency and intensity of extreme weather events. Individualized and timely advice on how to cope with thermal stress is therefore needed to encourage protective strategies and reduce morbidity and even mortality among vulnerable populations. Such advice can be based on integration of human thermal models, weather forecasts and individual user characteristics. The current study focused on development of an algorithm to predict indoor air temperature and assess indoor thermal exposure with incomplete knowledge of the actual thermal conditions. The algorithm provides discrete predictions of temperature through a decision tree classification with six simple building descriptors and three parameters harvested from weather forecast services. The data used to train and test the algorithm was obtained from field measurements in seven Danish households and from building simulations considering three different climate regions ranging from temperate to hot and humid. The approach was able to correctly predict approximately 68% of the most frequent temperature levels. The findings suggest that it is possible to develop a simple method that predicts indoor air temperature with reasonable accuracy.
|
|
