@article{StraussKulpLevermann2015,
  author    = {Strauss, Benjamin H. and Kulp, Scott and Levermann, Anders},
  title     = {Carbon choices determine US cities committed to futures below sea level},
  series = {Proceedings of the National Academy of Sciences of the United States of America},
  volume    = {112},
  journal   = {Proceedings of the National Academy of Sciences of the United States of America},
  number    = {44},
  publisher = {National Acad. of Sciences},
  address   = {Washington},
  issn      = {0027-8424},
  doi       = {10.1073/pnas.1511186112},
  pages     = {13508 -- 13513},
  year      = {2015},
  abstract  = {Anthropogenic carbon emissions lock in long-term sea-level rise that greatly exceeds projections for this century, posing profound challenges for coastal development and cultural legacies. Analysis based on previously published relationships linking emissions to warming and warming to rise indicates that unabated carbon emissions up to the year 2100 would commit an eventual global sea-level rise of 4.3-9.9 m. Based on detailed topographic and population data, local high tide lines, and regional long-term sea-level commitment for different carbon emissions and ice sheet stability scenarios, we compute the current population living on endangered land at municipal, state, and national levels within the United States. For unabated climate change, we find that land that is home to more than 20 million people is implicated and is widely distributed among different states and coasts. The total area includes 1,185-1,825 municipalities where land that is home to more than half of the current population would be affected, among them at least 21 cities exceeding 100,000 residents. Under aggressive carbon cuts, more than half of these municipalities would avoid this commitment if the West Antarctic Ice Sheet remains stable. Similarly, more than half of the US population-weighted area under threat could be spared. We provide lists of implicated cities and state populations for different emissions scenarios and with and without a certain collapse of the West Antarctic Ice Sheet. Although past anthropogenic emissions already have caused sea-level commitment that will force coastal cities to adapt, future emissions will determine which areas we can continue to occupy or may have to abandon.},
  language  = {en}
}
@article{SchultesPiontekSoergeletal.2021,
  author    = {Schultes, Anselm and Piontek, Franziska and Soergel, Bjoern and Rogelj, Joeri and Baumstark, Lavinia and Kriegler, Elmar and Edenhofer, Ottmar and Luderer, Gunnar},
  title     = {Economic damages from on-going climate change imply deeper near-term emission cuts},
  series = {Environmental research letters},
  volume    = {16},
  journal   = {Environmental research letters},
  number    = {10},
  publisher = {IOP Publishing},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/ac27ce},
  pages     = {11},
  year      = {2021},
  abstract  = {Pathways toward limiting global warming to well below 2 ∘C, as used by the IPCC in the Fifth Assessment Report, do not consider the climate impacts already occurring below 2 ∘C. Here we show that accounting for such damages significantly increases the near-term ambition of transformation pathways. We use econometric estimates of climate damages on GDP growth and explicitly model the uncertainty in the persistence time of damages. The Integrated Assessment Model we use includes the climate system and mitigation technology detail required to derive near-term policies. We find an optimal carbon price of \$115 per tonne of CO2 in 2030. The long-term persistence of damages, while highly uncertain, is a main driver of the near-term carbon price. Accounting for damages on economic growth increases the gap between the currently pledged nationally determined contributions and the welfare-optimal 2030 emissions by two thirds, compared to pathways considering the 2 ∘C limit only.},
  language  = {en}
}
@phdthesis{Willner2018,
  author    = {Willner, Sven N.},
  title     = {Global economic response to flood damages under climate change},
  school      = {Universit{\"a}t Potsdam},
  pages     = {v, 247},
  year      = {2018},
  abstract  = {Climate change affects societies across the globe in various ways. In addition to gradual changes in temperature and other climatic variables, global warming is likely to increase intensity and frequency of extreme weather events. Beyond biophysical impacts, these also directly affect societal and economic activity. Additionally, indirect effects can occur; spatially, economic losses can spread along global supply-chains; temporally, climate impacts can change the economic development trajectory of countries. This thesis first examines how climate change alters river flood risk and its local socio-economic implications. Then, it studies the global economic response to river floods in particular, and to climate change in general. Changes in high-end river flood risk are calculated for the next three decades on a global scale with high spatial resolution. In order to account for uncertainties, this assessment makes use of an ensemble of climate and hydrological models as well as a river routing model, that is found to perform well regarding peak river discharge. The results show an increase in high-end flood risk in many parts of the world, which require profound adaptation efforts. This pressure to adapt is measured as the enhancement in protection level necessary to stay at historical high-end risk. In developing countries as well as in industrialized regions, a high pressure to adapt is observed - the former to increase low protection levels, the latter to maintain the low risk levels perceived in the past. Further in this thesis, the global agent-based dynamic supply-chain model acclimate is developed. It models the cascading of indirect losses in the global supply network. As an anomaly model its agents - firms and consumers - maximize their profit locally to respond optimally to local perturbations. Incorporating quantities as well as prices on a daily basis, it is suitable to dynamically resolve the impacts of unanticipated climate extremes. The model is further complemented by a static measure, which captures the inter-dependencies between sectors across regions that are only connected indirectly. These higher-order dependencies are shown to be important for a comprehensive assessment of loss-propagation and overall costs of local disasters. In order to study the economic response to river floods, the acclimate model is driven by flood simulations. Within the next two decades, the increase in direct losses can only partially be compensated by market adjustments, and total losses are projected to increase by 17\% without further adaptation efforts. The US and the EU are both shown to receive indirect losses from China, which is strongly affected directly. However, recent trends in the trade relations leave the EU in a better position to compensate for these losses. Finally, this thesis takes a broader perspective when determining the investment response to the climate change damages employing the integrated assessment model DICE. On an optimal economic development path, the increase in damages is anticipated as emissions and consequently temperatures increase. This leads to a significant devaluation of investment returns and the income losses from climate damages almost double. Overall, the results highlight the need to adapt to extreme weather events - local physical adaptation measures have to be combined with regional and global policy measures to prepare the global supply-chain network to climate change.},
  language  = {en}
}
@phdthesis{Fuessel2003,
  author    = {F{\"u}ssel, Hans-Martin},
  title     = {Impacts analysis for inverse integrated assessments of climate change},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0001089},
  school      = {Universit{\"a}t Potsdam},
  year      = {2003},
  abstract  = {Diese Dissertation beschreibt die Entwicklung und Anwendung des Klimawirkungsmoduls des ICLIPS-Modells, eines integrierten Modells des Klimawandels ('Integrated Assessment'-Modell). Vorangestellt ist eine Diskussion des gesellschaftspolitischen Kontexts, in dem modellbasiertes 'Integrated Assessment' stattfindet, aus der wichtige Anforderungen an die Spezifikation des Klimawirkungsmoduls abgeleitet werden. Das 'Integrated Assessment' des Klimawandels umfasst eine weiten Bereich von Aktivit{\"a}ten zur wissenschaftsbasierten Unterst{\"u}tzung klimapolitischer Entscheidungen. Hierbei wird eine Vielzahl von Ans{\"a}tzen verfolgt, um politikrelevante Informationen {\"u}ber die erwarteten Auswirkungen des Klimawandels zu ber{\"u}cksichtigen. Wichtige Herausforderungen in diesem Bereich sind die große Bandbreite der relevanten r{\"a}umlichen und zeitlichen Skalen, die multifaktorielle Verursachung vieler 'Klimafolgen', erhebliche wissenschaftliche Unsicherheiten sowie die Mehrdeutigkeit unvermeidlicher Werturteile. Die Entwicklung eines hierarchischen Konzeptmodells erlaubt die Strukturierung der verschiedenen Ans{\"a}tze sowie die Darstellung eines mehrstufigen Entwicklungsprozesses, der sich in der Praxis und der zu Grunde liegenden Theorie von Studien zur Vulnerabilit{\"a}t hinsichtlich des Klimawandels wiederspiegelt. 'Integrated Assessment'-Modelle des Klimawandels sind wissenschaftliche Werkzeuge, welche eine vereinfachte Beschreibung des gekoppelten Mensch-Klima-Systems enthalten. Die wichtigsten entscheidungstheoretischen Ans{\"a}tze im Bereich des modellbasierten 'Integrated Assessment' werden im Hinblick auf ihre F{\"a}higkeit zur ad{\"a}quaten Darstellung klimapolitischer Entscheidungsprobleme bewertet. Dabei stellt der 'Leitplankenansatz' eine 'inverse' Herangehensweise zur Unterst{\"u}tzung klimapolitischer Entscheidungen dar, bei der versucht wird, die Gesamtheit der klimapolitischen Strategien zu bestimmen, die mit einer Reihe von zuvor normativ bestimmten Mindestkriterien (den sogenannten 'Leitplanken') vertr{\"a}glich sind. Dieser Ansatz verbindet bis zu einem gewissen Grad die wissenschaftliche Strenge und Objektivit{\"a}t simulationsbasierter Ans{\"a}tze mit der F{\"a}higkeit von Optimierungsans{\"a}tzen, die Gesamtheit aller Entscheidungsoptionen zu ber{\"u}cksichtigen. Das ICLIPS-Modell ist das erste 'Integrated Assessment'-Modell des Klimawandels, welches den Leitplankenansatz implementiert. Die Darstellung von Klimafolgen ist eine wichtige Herausforderung f{\"u}r 'Integrated Assessment'-Modelle des Klimawandels. Eine Betrachtung bestehender 'Integrated Assessment'-Modelle offenbart große Unterschiede in der Ber{\"u}cksichtigung verschiedener vom Klimawandel betroffenen Sektoren, in der Wahl des bzw. der Indikatoren zur Darstellung von Klimafolgen, in der Ber{\"u}cksichtigung nicht-klimatischer Entwicklungen einschließlich gezielter Anpassungsmaßnahmen an den Klimawandel, in der Behandlung von Unsicherheiten und in der Ber{\"u}cksichtigung von 'singul{\"a}ren' Ereignissen. 'Integrated Assessment'-Modelle, die auf einem Inversansatz beruhen, stellen besondere Anforderungen an die Darstellung von Klimafolgen. Einerseits muss der Detaillierungsgrad hinreichend sein, um Leitplanken f{\"u}r Klimafolgen sinnvoll definieren zu k{\"o}nnen; andererseits muss die Darstellung effizient genug sein, um die Gesamtheit der m{\"o}glichen klimapolitischen Strategien erkunden zu k{\"o}nnen. Großr{\"a}umige Singularit{\"a}ten k{\"o}nnen h{\"a}ufig durch vereinfachte dynamische Modelle abgebildet werden. Diese Methode ist jedoch weniger geeignet f{\"u}r regul{\"a}re Klimafolgen, bei denen die Bestimmung relevanter Ergebnisse in der Regel die Ber{\"u}cksichtigung der Heterogenit{\"a}t von klimatischen, naturr{\"a}umlichen und sozialen Faktoren auf der lokalen oder regionalen Ebene erfordert. Klimawirkungsfunktionen stellen sich als die geeignetste Darstellung regul{\"a}rer Klimafolgen im ICLIPS-Modell heraus. Eine Klimawirkungsfunktion beschreibt in aggregierter Form die Reaktion eines klimasensitiven Systems, wie sie von einem geographisch expliziten Klimawirkungsmodell f{\"u}r eine repr{\"a}sentative Teilmenge m{\"o}glicher zuk{\"u}nftiger Entwicklungen simuliert wurde. Die in dieser Arbeit vorgestellten Klimawirkungsfunktionen nutzen die globale Mitteltemperatur sowie die atmosph{\"a}rische CO2-Konzentration als Pr{\"a}diktoren f{\"u}r global und regional aggregierte Auswirkungen des Klimawandels auf nat{\"u}rliche {\"O}kosysteme, die landwirtschaftliche Produktion und die Wasserverf{\"u}gbarkeit. Die Anwendung einer 'Musterskalierungstechnik' erm{\"o}glicht hierbei die Ber{\"u}cksichtigung der regionalen und saisonalen Muster des Klima{\"a}nderungssignals aus allgemeinen Zirkulationsmodellen, ohne die Effizienz der dynamischen Modellkomponenten zu beeintr{\"a}chtigen. Bem{\"u}hungen zur quantitativen Absch{\"a}tzung zuk{\"u}nftiger Klimafolgen sehen sich bei der Wahl geeigneter Indikatoren in der Regel einem Zielkonflikt zwischen der Relevanz eines Indikators f{\"u}r Entscheidungstr{\"a}ger und der Zuverl{\"a}ssigkeit, mit der dieser bestimmt werden kann, gegen{\"u}ber. Eine Reihe von nichtmonet{\"a}ren Indikatoren zur aggregierten Darstellung von Klimafolgen in Klimawirkungsfunktionen wird pr{\"a}sentiert, welche eine Balance zwischen diesen beiden Zielen anstreben und gleichzeitig die Beschr{\"a}nkungen ber{\"u}cksichtigen, die sich aus anderen Komponenten des ICLIPS-Modells ergeben. Klimawirkungsfunktionen werden durch verschiedene Typen von Diagrammen visualisiert, welche jeweils unterschiedliche Perspektiven auf die Ergebnismenge der Klimawirkungssimulationen erlauben. Die schiere Anzahl von Klimawirkungsfunktionen verhindert ihre umfassende Darstellung in dieser Arbeit. Ausgew{\"a}hlte Ergebnisse zu Ver{\"a}nderungen in der r{\"a}umlichen Ausdehnung von Biomen, im landwirtschaftlichen Potential verschiedener L{\"a}nder und in der Wasserverf{\"u}gbarkeit in mehreren großen Einzugsgebieten werden diskutiert. Die Gesamtheit der Klimawirkungsfunktionen wird zug{\"a}nglich gemacht durch das 'ICLIPS Impacts Tool', eine graphische Benutzeroberfl{\"a}che, die einen bequemen Zugriff auf {\"u}ber 100.000 Klimawirkungsdiagramme erm{\"o}glicht. Die technischen Aspekte der Software sowie die zugeh{\"o}rige Datenbasis wird beschrieben. Die wichtigste Anwendung von Klimawirkungsfunktionen ist im 'Inversmodus', wo sie genutzt werden, um Leitplanken zur Begrenzung von Klimafolgen in gleichzeitige Randbedingungen f{\"u}r Variablen aus dem optimierenden ICLIPS-Klima-Weltwirtschafts-Modell zu {\"u}bersetzen. Diese {\"U}bersetzung wird erm{\"o}glicht durch Algorithmen zur Bestimmung von Mengen erreichbarer Klimazust{\"a}nde ('reachable climate domains') sowie zur parametrisierten Approximation zul{\"a}ssiger Klimafenster ('admissible climate windows'), die aus Klimawirkungsfunktionen abgeleitet werden. Der umfassende Bestand an Klimawirkungsfunktionen zusammen mit diesen Algorithmen erm{\"o}glicht es dem integrierten ICLIPS-Modell, in flexibler Weise diejenigen klimapolitischen Strategien zu bestimmen, welche bestimmte in biophysikalischen Einheiten ausgedr{\"u}ckte Begrenzungen von Klimafolgen explizit ber{\"u}cksichtigen. Diese M{\"o}glichkeit bietet kein anderes intertemporal optimierendes 'Integrated Assessment'-Modell. Eine Leitplankenanalyse mit dem integrierten ICLIPS-Modell unter Anwendung ausgew{\"a}hlter Klimawirkungsfunktionen f{\"u}r Ver{\"a}nderungen nat{\"u}rlicher {\"O}kosysteme wird beschrieben. In dieser Analyse werden so genannte 'notwendige Emissionskorridore' berechnet, die vorgegebene Beschr{\"a}nkungen hinsichtlich der maximal zul{\"a}ssigen globalen Vegetationsver{\"a}nderungen und der regionalen Klimaschutzkosten ber{\"u}cksichtigen. Dies geschieht sowohl f{\"u}r eine 'Standardkombination' der drei gew{\"a}hlten Kriterien als auch f{\"u}r deren systematische Variation. Eine abschließende Diskussion aktueller Entwicklungen in der 'Integrated Assessment'-Modellierung stellt diese Arbeit mit anderen einschl{\"a}gigen Bem{\"u}hungen in Beziehung.},
  language  = {en}
}
@phdthesis{Siegmund2018,
  author    = {Siegmund, Jonatan Frederik},
  title     = {Quantifying impacts of climate extreme events on vegetation},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407095},
  school      = {Universit{\"a}t Potsdam},
  pages     = {129},
  year      = {2018},
  abstract  = {Together with the gradual change of mean values, ongoing climate change is projected to increase frequency and amplitude of temperature and precipitation extremes in many regions of Europe. The impacts of such in most cases short term extraordinary climate situations on terrestrial ecosystems are a matter of central interest of recent climate change research, because it can not per se be assumed that known dependencies between climate variables and ecosystems are linearly scalable. So far, yet, there is a high demand for a method to quantify such impacts in terms of simultaneities of event time series. In the course of this manuscript the new statistical approach of Event Coincidence Analysis (ECA) as well as it's R implementation is introduced, a methodology that allows assessing whether or not two types of event time series exhibit similar sequences of occurrences. Applications of the method are presented, analyzing climate impacts on different temporal and spacial scales: the impact of extraordinary expressions of various climatic variables on tree stem variations (subdaily and local scale), the impact of extreme temperature and precipitation events on the owering time of European shrub species (weekly and country scale), the impact of extreme temperature events on ecosystem health in terms of NDVI (weekly and continental scale) and the impact of El Ni{\~n}o and La Ni{\~n}a events on precipitation anomalies (seasonal and global scale). The applications presented in this thesis refine already known relationships based on classical methods and also deliver substantial new findings to the scientific community: the widely known positive correlation between flowering time and temperature for example is confirmed to be valid for the tails of the distributions while the widely assumed positive dependency between stem diameter variation and temperature is shown to be not valid for very warm and very cold days. The larger scale investigations underline the sensitivity of anthrogenically shaped landscapes towards temperature extremes in Europe and provide a comprehensive global ENSO impact map for strong precipitation events. Finally, by publishing the R implementation of the method, this thesis shall enable other researcher to further investigate on similar research questions by using Event Coincidence Analysis.},
  language  = {en}
}
@article{KuhlaWillnerOttoetal.2021,
  author    = {Kuhla, Kilian and Willner, Sven N. and Otto, Christian and Geiger, Tobias and Levermann, Anders},
  title     = {Ripple resonance amplifies economic welfare loss from weather extremes},
  series = {Environmental research letters : ERL / Institute of Physics},
  volume    = {16},
  journal   = {Environmental research letters : ERL / Institute of Physics},
  number    = {11},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/ac2932},
  pages     = {8},
  year      = {2021},
  abstract  = {The most complex but potentially most severe impacts of climate change are caused by extreme weather events. In a globally connected economy, damages can cause remote perturbations and cascading consequences-a ripple effect along supply chains. Here we show an economic ripple resonance that amplifies losses when consecutive or overlapping weather extremes and their repercussions interact. This amounts to an average amplification of 21\% for climate-induced heat stress, river floods, and tropical cyclones. Modeling the temporal evolution of 1.8 million trade relations between >7000 regional economic sectors, we find that the regional responses to future extremes are strongly heterogeneous also in their resonance behavior. The induced effect on welfare varies between gains due to increased demand in some regions and losses due to demand or supply shortages in others. Within the current global supply network, the ripple resonance effect of extreme weather is strongest in high-income economies-an important effect to consider when evaluating past and future economic climate impacts.},
  language  = {en}
}
@article{KalkuhlWenz2020,
  author    = {Kalkuhl, Matthias and Wenz, Leonie},
  title     = {The impact of climate conditions on economic production},
  series = {Journal of Environmental Economics and Management},
  volume    = {103},
  journal   = {Journal of Environmental Economics and Management},
  publisher = {Elsevier},
  address   = {San Diego},
  issn      = {0095-0696},
  doi       = {10.1016/j.jeem.2020.102360},
  pages     = {20},
  year      = {2020},
  abstract  = {We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7-14\% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73-142\$/tCO2 in 2020, rising to 92-181\$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.},
  language  = {en}
}
@article{LevermannClarkMarzeionetal.2013,
  author    = {Levermann, Anders and Clark, Peter U. and Marzeion, Ben and Milne, Glenn A. and Pollard, David and Radic, Valentina and Robinson, Alexander},
  title     = {The multimillennial sea-level commitment of global warming},
  series = {Proceedings of the National Academy of Sciences of the United States of America},
  volume    = {110},
  journal   = {Proceedings of the National Academy of Sciences of the United States of America},
  number    = {34},
  publisher = {National Acad. of Sciences},
  address   = {Washington},
  issn      = {0027-8424},
  doi       = {10.1073/pnas.1219414110},
  pages     = {13745 -- 13750},
  year      = {2013},
  abstract  = {Global mean sea level has been steadily rising over the last century, is projected to increase by the end of this century, and will continue to rise beyond the year 2100 unless the current global mean temperature trend is reversed. Inertia in the climate and global carbon system, however, causes the global mean temperature to decline slowly even after greenhouse gas emissions have ceased, raising the question of how much sea-level commitment is expected for different levels of global mean temperature increase above preindustrial levels. Although sea-level rise over the last century has been dominated by ocean warming and loss of glaciers, the sensitivity suggested from records of past sea levels indicates important contributions should also be expected from the Greenland and Antarctic Ice Sheets. Uncertainties in the paleo-reconstructions, however, necessitate additional strategies to better constrain the sea-level commitment. Here we combine paleo-evidence with simulations from physical models to estimate the future sea-level commitment on a multimillennial time scale and compute associated regional sea-level patterns. Oceanic thermal expansion and the Antarctic Ice Sheet contribute quasi-linearly, with 0.4 m degrees C-1 and 1.2 m degrees C-1 of warming, respectively. The saturation of the contribution from glaciers is overcompensated by the nonlinear response of the Greenland Ice Sheet. As a consequence we are committed to a sea-level rise of approximately 2.3 m degrees C-1 within the next 2,000 y. Considering the lifetime of anthropogenic greenhouse gases, this imposes the need for fundamental adaptation strategies on multicentennial time scales.},
  language  = {en}
}