The Data Imaginaries of Climate Art: The Manifest Data Project

Leonardo ◽  
2021 ◽  
pp. 1-10
Author(s):  
Tom Corby ◽  
Gavin Baily ◽  
Jonathan Mackenzie ◽  
Giles Lane ◽  
Erin Dickson ◽  
...  
Keyword(s):  
Climate Change ◽  
Southern Ocean ◽  
Climate Models ◽  
Methodological Approach ◽  
Ways Of Knowing ◽  
Data Driven ◽  
Ocean Studies

Abstract We discuss a series of artworks produced since 2009 including The Southern Ocean Studies (2012), The Northern Polar Studies (2014) and Carbon Topographies (2020). Through this work we explore how climate models can be employed to develop data driven imaginaries of climate change, its impacts and causes. We argue for the experiential potential of this information for producing differently situated ways of knowing climate, framing this through a methodological approach described as ‘data manifestation’.

scholarly journals Engaging Transformation: Using Seasonal Rounds to Anticipate Climate Change

Human Ecology ◽  
2021 ◽  
Author(s):  
Karim-Aly Kassam ◽  
Morgan Ruelle ◽  
Isabell Haag ◽  
Umed Bulbulshoev ◽  
Daler Kaziev ◽  
...  
Keyword(s):  
Climate Change ◽  
Rural Communities ◽  
Communities Of Practice ◽  
Seasonal Change ◽  
Methodological Approach ◽  
Ways Of Knowing ◽  
Ecological Relations ◽  
Biophysical Indicators ◽  
Context Specific ◽  
The Relationship

AbstractSeasonal rounds are deliberative articulations of a community’s sociocultural relations with their ecological system. The process of visualizing seasonal rounds informs transdisciplinary research. We present a methodological approach for communities of enquiry to engage communities of practice through context-specific sociocultural and ecological relations driven by seasonal change. We first discuss historical précis of the concept of seasonal rounds that we apply to assess the spatial and temporal communal migrations and then describe current international research among Indigenous and rural communities in North America and Central Asia by the creation of a common vocabulary through mutual respect for multiple ways of knowing, validation of co-generated knowledge, and insights into seasonal change. By investigating the relationship between specific biophysical indicators and livelihoods of local communities, we demonstrate that seasonal rounds are an inclusive and participatory methodology that brings together diverse Indigenous and rural voices to anticipate anthropogenic climate change.

Towards multi-method and multi-scale attribution of global wildfire danger

2020 ◽  
Author(s):  
Zhongwei Liu ◽  
Jonathan Eden ◽  
Bastien Dieppois ◽  
Matthew Blackett
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Methodological Approach ◽  
Multi Scale ◽  
Attribution Analysis ◽  
Event Attribution ◽  
Large Fires ◽  
Future Risk ◽  
Warming World

<p>Wildfires constitute a major natural hazard and pose huge risk to many regions of the world. The series of large fires across both hemispheres in recent years have led to inevitable questions about how human-induced climate change may be altering the character of such events. Providing answers to these questions is a crucial step to increasing resilience to major wildfires.</p><p>Long-term projections produced by state-of-the-art climate models, even when reliable, are not always a suitable means of communicating risk. Methodologies to attribute trends in meteorological phenomena associated with high-impact events to anthropogenic influence have the potential to better communicate risk and guide adaptation strategies. While the link between a warming world and heat-related extremes (e.g. heatwaves and droughts) is reasonably well-understood, there is a lack of consensus on the most appropriate and effective methodological approach for many variables, potentially impacted by warming climate, such as wildfire attribution. The link with climate change remains poorly understood and wildfires have been largely ignored by attribution studies to date.</p><p>As a first step towards the development of a seamless, globally-applicable framework for assessing past, present and future risk in wildfire danger, we present a global attribution analysis of wildfire danger. With initial focus on observational records, we use both established and novel empirical-statistical methods to attribute historical trends in episodes of extreme weather and climate conducive to wildfire ignition and spread. Particular consideration is given to the sensitivity of attribution findings to the spatial scale upon which the analysis is conducted. We also draw attention to a series of important, often overlooked, conceptual and technical challenges in event attribution, including validation and bias-correction of climate models and discuss the value of linking attribution of recent wildfire events with future risk assessment.</p>

scholarly journals Evaluation of data-driven models to downscale rainfall parameters from global climate models outputs: the case study of Latyan watershed

2018 ◽  
Vol 11 (1) ◽  
pp. 200-216 ◽  
Author(s):  
Reza Haji Hosseini ◽  
Saeed Golian ◽  
Jafar Yazdi
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Fuzzy Inference ◽  
Global Climate ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Data Driven ◽  
Observation Data ◽  
Inference System

Abstract Assessment of climate change in future periods is considered necessary, especially with regard to probable changes to water resources. One of the methods for estimating climate change is the use of the simulation outputs of general circulation models (GCMs). However, due to the low resolution of these models, they are not applicable to regional and local studies and downscaling methods should be applied. The purpose of the present study was to use GCM models' outputs for downscaling precipitation measurements at Amameh station in Latyan dam basin. For this purpose, the observation data from the Amameh station during the 1980–2005 period, 26 output variables from two GCM models, namely, HadCM3 and CanESM2 were used. Downscaling was performed by three data-driven methods, namely, artificial neural network (ANN), nonparametric K-nearest neighborhood (KNN) method, and adaptive network-based fuzzy inference system method (ANFIS). Comparison of the monthly results showed the superiority of KNN compared to the other two methods in simulating precipitation. However, all three, ANN, KNN, and ANFIS methods, showed satisfactory results for both HadDCM3 and CanESM2 GCM models in downscaling precipitation in the study area.

Objective deviation of Climate Indices for the assessment of altered risk-landscapes driven by accelerated climate change

2020 ◽  
Author(s):  
Nikta Madjdi ◽  
Katharina Enigl ◽  
Christoph Matulla
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Methodological Approach ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Indices ◽  
European Alps ◽  
Catchment Areas ◽  
Damage Processes

<p><span>Floodings are amongst the most devastating damage-processes worldwide. Along with the increase in climate change induced extreme events, research devoted to the identification of so-called Climate Indices (CIs) describing weather phenomena triggering hazard-occurrences gains rising emphasis. CIs have a wide potential for further investigation in both research and application as e.g. in public protection and the transport and logistic industry. The appearance of specific CIs in regional climate models (i.e., ‘hazard development corridors’) can serve as an input in decision-theoretic concepts aiming to sustain current safety levels in climate change induced altering risk landscapes (Matulla et al, submitted). Enigl et al, 2019 first objectively derived hazard-triggering precipitation totals for six process-categories and three climatologically as well as geomorphologically distinct regions in the Austrian part of the European Alps.  This study aims at investigating a slightly different methodological approach for the objective determination of Climate Indices in the catchment area of the River Danube in Austria depending on catchment areas. </span></p>

REGIONAL METHOD FOR DETERMINATION THE MAXIMUM RUNOFF OF THE SPRING FLOOD IN SUB-BASIN THE DESNA RIVER UNDER THE CLIMATE CHANGE

2020 ◽  
pp. 15-25
Author(s):  
V.A Ovcharuk ◽  
S.V. Ivashchenko
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Methodological Approach ◽  
Statistical Processing ◽  
Water Runoff ◽  
Spring Flood ◽  
Operator Model ◽  
Calculation Technique ◽  
Air Temperatures ◽  
Maximum Runoff

The results of development of the regional methodology for calculating the maximum water runoff of the rare probability of exceedance for the rivers of the sub-basin the Desna River under the conditions of modern climate change are presented. As basic for calculation authors used a modern modified version of the operator model of runoff formation developed at the Odessa State Environmental University to determine the characteristics of spring flood, which allows taking into account the influence of climate change on the calculated characteristics of the maximal runoff modules. The advantage of the proposed method is that it is based on the theory of channel isochrones, which allows describing the natural process of formation of runoff in the form of the operator “slope tide – channel runoff”. To substantiate the basic calculation parameters of the author’s methodology, was used the data of direct observations on the hydrological characteristics of the maximum waterrunoff of the spring flood (water discharges, depth of runoff and duration of the influx) and meteorological factors of its formation (maximum snow supply and precipitation during spring flood) for the period since its beginning to 2015, including. In the process of standardization of the main components of the proposed methodology, methods of statistical processing, spatial generalization, numerical problem solving and mathematical modeling were used. To account for possible climate change, the original author’s scientific and methodological approach is proposed, which is to determine “climate corrections” on the basis of modern baseline data – maximum of the water snow supply and precipitation during spring flood and runoff coefficients of the water, taking into account their dependence from long-term annual air temperatures that are projected according to the developed climate models and scenarios. The modified version of the operator model is proposed to be used as a regional calculation technique for determining maximum runoff modules of the rare probability of exceeding for ungauged rivers in the Desna sub-basin during the passage of the spring flood.

scholarly journals Influence of the Southern Annular Mode on Projected Weakening of the Atlantic Meridional Overturning Circulation

2013 ◽  
Vol 26 (20) ◽  
pp. 8017-8036 ◽  
Author(s):  
Peter T. Spooner ◽  
Helen L. Johnson ◽  
Tim J. Woollings
Keyword(s):  
Climate Change ◽  
Southern Ocean ◽  
Greenhouse Gas ◽  
Climate Models ◽  
Atlantic Meridional Overturning Circulation ◽  
Southern Annular Mode ◽  
Meridional Overturning Circulation ◽  
Overturning Circulation ◽  
Annular Mode ◽  
Meridional Overturning

Abstract Coupled climate models predict density-driven weakening of the Atlantic meridional overturning circulation (AMOC) under greenhouse gas forcing, with considerable spread in the response between models. There is also a large spread in the predicted increase of the southern annular mode (SAM) index across these models. Regression analysis across model space using 11 non-eddy-resolving models suggests that up to 35% of the intermodel spread in the AMOC response may be associated with uncertainty in the magnitude of the increase in the SAM. Models with a large, positive SAM index response generally display a smaller weakening of the AMOC under greenhouse gas forcing. The initial AMOC strength is also a major cause of intermodel spread in its response to climate change. The increase in the SAM acts to reduce the weakening of the AMOC over the next century by around ⅓, through increases in wind stress over the Southern Ocean, northward Ekman transport, and upwelling around Antarctica. The SAM response is also related to an increase in the northward salt flux across 30°S and to salinity anomalies in the high-latitude North Atlantic. These provide a positive feedback by further reinforcement of the AMOC. The results suggest that, compared with the real ocean where eddies oppose wind-driven changes in Southern Ocean circulation, climate models underestimate the effects of anthropogenic climate change on the AMOC.

scholarly journals Surface Water Temperature Predictions at a Mid-Latitude Reservoir under Long-Term Climate Change Impacts Using a Deep Neural Network Coupled with a Transfer Learning Approach

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Temperature ◽  
Transfer Learning ◽  
Air Temperature ◽  
Climate Models ◽  
Temporal Variations ◽  
Training Data ◽  
Surface Water Temperature

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.

scholarly journals Ventilation of the abyss in the Atlantic sector of the Southern Ocean

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Camille Hayatte Akhoudas ◽  
Jean-Baptiste Sallée ◽  
F. Alexander Haumann ◽  
Michael P. Meredith ◽  
Alberto Naveira Garabato ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Bottom Water ◽  
Climate Models ◽  
Deep Ocean ◽  
Analytical Framework ◽  
Weddell Sea ◽  
Global Ocean ◽  
Shelf Water ◽  
Antarctic Bottom Water ◽  
Atlantic Sector

AbstractThe Atlantic sector of the Southern Ocean is the world’s main production site of Antarctic Bottom Water, a water-mass that is ventilated at the ocean surface before sinking and entraining older water-masses—ultimately replenishing the abyssal global ocean. In recent decades, numerous attempts at estimating the rates of ventilation and overturning of Antarctic Bottom Water in this region have led to a strikingly broad range of results, with water transport-based calculations (8.4–9.7 Sv) yielding larger rates than tracer-based estimates (3.7–4.9 Sv). Here, we reconcile these conflicting views by integrating transport- and tracer-based estimates within a common analytical framework, in which bottom water formation processes are explicitly quantified. We show that the layer of Antarctic Bottom Water denser than 28.36 kg m$$^{-3}$$ - 3 $$\gamma _{n}$$ γ n is exported northward at a rate of 8.4 ± 0.7 Sv, composed of 4.5 ± 0.3 Sv of well-ventilated Dense Shelf Water, and 3.9 ± 0.5 Sv of old Circumpolar Deep Water entrained into cascading plumes. The majority, but not all, of the Dense Shelf Water (3.4 ± 0.6 Sv) is generated on the continental shelves of the Weddell Sea. Only 55% of AABW exported from the region is well ventilated and thus draws down heat and carbon into the deep ocean. Our findings unify traditionally contrasting views of Antarctic Bottom Water production in the Atlantic sector, and define a baseline, process-discerning target for its realistic representation in climate models.

scholarly journals Interrogating Climate Adaptation Financing in Zimbabwe: Proposed Direction

2021 ◽  
Vol 13 (12) ◽  
pp. 6517
Author(s):  
Innocent Chirisa ◽  
Trynos Gumbo ◽  
Veronica N. Gundu-Jakarasi ◽  
Washington Zhakata ◽  
Thomas Karakadzai ◽  
...  
Keyword(s):  
Climate Change ◽  
Developing Countries ◽  
Climate Adaptation ◽  
Global Climate ◽  
Methodological Approach ◽  
Extreme Weather Events ◽  
Infrastructure Development ◽  
Low Carbon ◽  
Coastal Zones ◽  
Resource Base

Reducing vulnerability to climate change and enhancing the long-term coping capacities of rural or urban settlements to negative climate change impacts have become urgent issues in developing countries. Developing countries do not have the means to cope with climate hazards and their economies are highly dependent on climate-sensitive sectors such as agriculture, water, and coastal zones. Like most countries in Southern Africa, Zimbabwe suffers from climate-induced disasters. Therefore, this study maps critical aspects required for setting up a strong financial foundation for sustainable climate adaptation in Zimbabwe. It discusses the frameworks required for sustainable climate adaptation finance and suggests the direction for success in leveraging global climate financing towards building a low-carbon and climate-resilient Zimbabwe. The study involved a document review and analysis and stakeholder consultation methodological approach. The findings revealed that Zimbabwe has been significantly dependent on global finance mechanisms to mitigate the effects of climate change as its domestic finance mechanisms have not been fully explored. Results revealed the importance of partnership models between the state, individuals, civil society organisations, and agencies. Local financing institutions such as the Infrastructure Development Bank of Zimbabwe (IDBZ) have been set up. This operates a Climate Finance Facility (GFF), providing a domestic financial resource base. A climate change bill is also under formulation through government efforts. However, numerous barriers limit the adoption of adaptation practices, services, and technologies at the scale required. The absence of finance increases the vulnerability of local settlements (rural or urban) to extreme weather events leading to loss of life and property and compromised adaptive capacity. Therefore, the study recommends an adaptation financing framework aligned to different sectoral policies that can leverage diverse opportunities such as blended climate financing. The framework must foster synergies for improved impact and implementation of climate change adaptation initiatives for the country.

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