ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Collection
Publisher
Language
Years
  • 1
    facet.materialart.
    Unknown
    Data and code for the publication "Day-to-day temperature variability reduces economic growth" (Version 1) (2020)
    CERN / Zenodo
    Details
    Publication Date: 2022-03-21
    Description: This repository contains code and data for the reproduction of analysis and figures from: Kotz, Wenz, Stechemesser, Kalkuhl and Levermann (2020).
    Type: info:eu-repo/semantics/other
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 2
    facet.materialart.
    Unknown
    Data and code for the publication "The effect of rainfall changes on economic production" (2021)
    Zenodo
    Details
    Publication Date: 2022-03-21
    Description: The zipped file of this repository contains code and data to reproduce the results of the publication: Kotz et al, Nature, The effect of rainfall changes on economic production. (2021). https://doi.org/10.1038/s41586-021-04283-8
    Type: info:eu-repo/semantics/workingPaper
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 3
    facet.materialart.
    Unknown
    Strong increase of racist tweets outside of climate comfort zone in Europe (2021)
    In:  Environmental Research Letters
    Details
    Publication Date: 2022-03-21
    Description: Ambient temperature has been identified as a potential cause for human conflict in a variety of studies. Conflict is no longer limited to the physical space but exists in the form of hate and discrimination on social media. Here we provide evidence that the amount of racist and xenophobic content posted to the social media platform Twitter is nonlinearly influenced by temperature. Exploiting the linguistic plurality of Europe, we statistically analyse daily temperature data and more than 10 million racist tweets from six different countries spanning several climate zones for the years 2012-2018. Using a fixed-effects panel regression model that utilizes exogenous variation in local weather and controls for unobserved omitted variables, we identify the effect of population-weighted daily average temperature on the daily number of racist tweets and likes. We find a quasi-quadratic temperature response of racist tweets that is inversely proportional to the temperature distribution. Fewest racist tweets and likes are found for daily average temperatures between 5°C and 11°C, i.e. temperatures that are frequently experienced. Temperatures warmer or colder than that are associated with steep, nonlinear increases. Analyses at the country-level confirm this climate comfort zone of 5°C to 11°C across different European climatic zones. In the Southern European countries this is colder than the most frequently experienced temperatures, pointing to possible limits of adaptation. Within the next 30 years, the number of days outside this climate comfort zone, weighted by the identified temperature-racist-tweet response curve, will increase across parts of Europe, indicating that rising temperatures could aggravate xenophobia and racism in social media.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 4
    facet.materialart.
    Unknown
    Footprint of greenhouse forcing in daily temperature variability (2021)
    In:  Proceedings of the National Academy of Sciences of the United States of America (PNAS)
    Details
    Publication Date: 2022-07-20
    Description: Changes in mean climatic conditions will affect natural and societal systems profoundly under continued anthropogenic global warming. Changes in the high-frequency variability of temperature exert additional pressures, yet the effect of greenhouse forcing thereon has not been fully assessed or identified in observational data. Here, we show that the intramonthly variability of daily surface temperature changes with distinct global patterns as greenhouse gas concentrations rise. In both reanalyses of historical observations and state-of-the-art projections, variability increases at low to mid latitudes and decreases at northern mid to high latitudes with enhanced greenhouse forcing. These latitudinally polarized daily variability changes are identified from internal climate variability using a recently developed signal-to-noise-maximizing pattern-filtering technique. Analysis of a multimodel ensemble from the Coupled Model Intercomparison Project Phase 6 shows that these changes are attributable to enhanced greenhouse forcing. By the end of the century under a business-as-usual emissions scenario, daily temperature variability would continue to increase by up to a further 100% at low latitudes and decrease by 40% at northern high latitudes. Alternative scenarios demonstrate that these changes would be limited by mitigation of greenhouse gases. Moreover, global changes in daily variability exhibit strong covariation with warming across climate models, suggesting that the equilibrium climate sensitivity will also play a role in determining the extent of future variability changes. This global response of the high-frequency climate system to enhanced greenhouse forcing is likely to have strong and unequal effects on societies, economies, and ecosystems if mitigation and protection measures are not taken.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Format: application/pdf
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 5
    facet.materialart.
    Unknown
    DOSE - The MCC-PIK Database Of Subnational Economic output (2021)
    CERN / Zenodo
    Details
    Publication Date: 2022-10-25
    Description: A collaboration between the Mercator Research Institute on Global Commons and Climate Change (MCC) and the Potsdam Institute for Climate Impact Research (PIK), DOSE v.1 comprises a global data-base of sub-national economic output.
    Type: info:eu-repo/semantics/workingPaper
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 6
    facet.materialart.
    Unknown
    The effect of rainfall changes on economic production (2022)
    In:  Nature
    Details
    Publication Date: 2023-07-27
    Description: Macro-economic assessments of climate impacts lack an analysis of the distribution of daily rainfall, which can resolve both complex societal impact channels and anthropogenically forced changes. Here, using a global panel of subnational economic output for 1,554 regions worldwide over the past 40 years, we show that economic growth rates are reduced by increases in the number of wet days and in extreme daily rainfall, in addition to responding nonlinearly to the total annual and to the standardized monthly deviations of rainfall. Furthermore, high-income nations and the services and manufacturing sectors are most strongly hindered by both measures of daily rainfall, complementing previous work that emphasized the beneficial effects of additional total annual rainfall in low-income, agriculturally dependent economies4,7. By assessing the distribution of rainfall at multiple timescales and the effects on different sectors, we uncover channels through which climatic conditions can affect the economy. These results suggest that anthropogenic intensification of daily rainfall extremes will have negative global economic consequences that require further assessment by those who wish to evaluate the costs of anthropogenic climate change.
    Type: info:eu-repo/semantics/article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 7
    facet.materialart.
    Unknown
    Day-to-day temperature variability reduces economic growth (2021)
    In:  Nature Climate Change
    Details
    Publication Date: 2023-07-27
    Description: Elevated annual average temperature has been found to impact macro-economic growth. However, various fundamental elements of the economy are affected by deviations of daily temperature from seasonal expectations which are not well reflected in annual averages. Here we show that increases in seasonally adjusted day-to-day temperature variability reduce macro-economic growth independent of and in addition to changes in annual average temperature. Combining observed day-to-day temperature variability with subnational economic data for 1,537 regions worldwide over 40 years in fixed-effects panel models, we find that an extra degree of variability results in a five percentage-point reduction in regional growth rates on average. The impact of day-to-day variability is modulated by seasonal temperature difference and income, resulting in highest vulnerability in low-latitude, low-income regions (12 percentage-point reduction). These findings illuminate a new, global-impact channel in the climate–economy relationship that demands a more comprehensive assessment in both climate and integrated assessment models.
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 8
    facet.materialart.
    Unknown
    Prolonged exposure weakens risk perception and behavioral mobility response: Empirical evidence from Covid-19 (2023)
    In:  Transportation Research Interdisciplinary Perspectives
    Details
    Publication Date: 2023-11-22
    Description: Understanding the behavioral response dynamics to risks is important for informed policy-making at times of crises. Here we elucidate two response channels to Covid-19 risk and show that they weakened over time, prior to the availability of vaccines. We employ fixed-effects panel regression models to empirically assess the relationship between actual Covid-19 risk (daily case numbers), the perceived risk (attention paid to the pandemic via related Google search requests) and the resulting behavioral response (personal mobility choices) over two pandemic phases for 113 cities in eight countries, while accounting for government interventions. Prolonged exposure to Covid-19 reduces risk perception which in turn leads to a weakened behavioral response. Attention responses and mobility reductions across all three mobility types are weaker in the second phase, given the same levels of actual and perceived risk, respectively. Our results provide evidence that the risk response attenuates over time with implications for other crises evolving over long timescales.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 9
    facet.materialart.
    Unknown
    Constraining the Pattern and Magnitude of Projected Extreme Precipitation Change in a Multimodel Ensemble (2024)
    In:  Journal of Climate
    Details
    Publication Date: 2024-01-02
    Description: Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
  • 10
    facet.materialart.
    Unknown
    The impact of global warming on inflation: averages, seasonality and extremes (2023)
    European Central Bank (ECB)
    In:  ECB Working Paper Series
    Details
    Publication Date: 2024-01-03
    Description: Understanding of the macroeconomic effects of climate change is developing rapidly, but the implications for past and future inflation remain less well understood. Here we exploit a global dataset of monthly consumer price indices to identify the causal impacts of changes in climate on inflation, and to assess their implications under future warming. Flexibly accounting for heterogenous impacts across seasons and baseline climatic and socio-economic conditions, we find that increased average temperatures cause non-linear upwards inflationary pressures which persist over 12 months in both higher- and lower-income countries. Projections from state-of- the-art climate models show that in the absence of historically un-precedented adaptation, future warming will cause global increases in annual food and headline inflation of 0.92-3.23 and 0.32-1.18 percentage-points per year respectively, under 2035 projected climate (uncertainty range across emission scenarios, climate models and empirical specifications), as well as altering the seasonal dynamics of inflation. Moreover, we estimate that the 2022 summer heat extreme increased food inflation in Europe by 0.67 (0.43-0.93) percentage-points and that future warming projected for 2035 would amplify the impacts of such extremes by 50%. These results suggest that climate change poses risks to price stability by having an upward impact on inflation, altering its seasonality and amplifying the impacts caused by extremes.
    Language: English
    Type: info:eu-repo/semantics/report
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION PIK
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...