Applying big data beyond small problems in climate research

No abstract is available for this paper.

• Publication year

  2019

• Venue

  Nature Climate Change

• Publication date

  2019-03-01

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.1038/s41558-019-0404-1
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• In-Mapper combiner based MapReduce algorithm for processing of big climate data

  2018cited by this paper
• Opinion: Smart farming is key to developing sustainable agriculture

  2017cited by this paper
• Profiling urban vulnerabilities to climate change: An indicator-based vulnerability assessment for European cities

  2017cited by this paper
• A neural network-based local rainfall prediction system using meteorological data on the Internet: A case study using data from the Japan Meteorological Agency

  2017cited by this paper
• Drought monitoring using high resolution soil moisture through multi-sensor satellite data fusion over the Korean peninsula

  2017cited by this paper
• Predicting floods with Flickr tags

  2017cited by this paper
• Spatial cumulative sum algorithm with big data analytics for climate change detection

  2017cited by this paper
• Berechenbarkeit der Welt? Philosophie und Wissenschaft im Zeitalter von Big Data

  2017cited by this paper
• Introduction: Ten Theses on Big Data and Computability

  2017cited by this paper
• Using second-order approximation to incorporate GCM uncertainty in climate change impact assessments

  2017cited by this paper
• Quantitative and detailed spatiotemporal patterns of drought in China during 2001-2013.

  2017cited by this paper
• A strategy to effectively make use of large volumes of climate data for climate change adaptation

  2017cited by this paper
• Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations

  2017cited by this paper
• Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

  2017cited by this paper
• Identification of Critical Flood Prone Areas in Data-Scarce and Ungauged Regions: A Comparison of Three Data Mining Models

  2017cited by this paper
• Building confidence in climate model projections: an analysis of inferences from fit

  2017cited by this paper
• Neural Network-Based Approach for Identification of Meteorological Factors Affecting Regional Sea-Level Anomalies

  2017cited by this paper
• Nowcasting Foehn Wind Events Using the AdaBoost Machine Learning Algorithm

  2017cited by this paper
• Selenium deficiency risk predicted to increase under future climate change

  2017cited by this paper
• Drought sensitivity mapping using two one-class support vector machine algorithms

  2017cited by this paper
• A random forest algorithm for nowcasting of intense precipitation events

  2017cited by this paper
• Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms

  2016cited by this paper
• Rapid assessment of disaster damage using social media activity

  2016cited by this paper
• Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

  2016cited by this paper
• Temperature-related mortality estimates after accounting for the cumulative effects of air pollution in an urban area

  2016cited by this paper
• Opinion: Big data has big potential for applications to climate change adaptation

  2016cited by this paper
• Changes in population susceptibility to heat and cold over time: assessing adaptation to climate change

  2016cited by this paper
• Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants

  2016cited by this paper
• An extreme learning machine approach for modeling evapotranspiration using extrinsic inputs

  2016cited by this paper
• Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen

  2016cited by this paper
• What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets

  2016cited by this paper
• A formal definition of Big Data based on its essential features

  2016cited by this paper
• Modelling economic losses of historic and present-day high-impact winter windstorms in Switzerland

  2016cited by this paper
• Using artificial intelligence to forecast monthly rainfall under present and future climates for the Bowen Basin, Queensland, Australia

  2015cited by this paper
• Extreme learning machine based prediction of daily dew point temperature

  2015cited by this paper
• The Causal Nature of Modeling with Big Data

  2015cited by this paper
• Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

  2015cited by this paper
• A bitter cup: climate change profile of global production of Arabica and Robusta coffee

  2015cited by this paper
• Artificial General Intelligence

  2015cited by this paper
• Deep Learning

  2015cited by this paper
• The future of climate modeling

  2015cited by this paper
• Crowdsourcing for climate and atmospheric sciences: current status and future potential

  2015cited by this paper
• Climate services for society: origins, institutional arrangements, and design elements for an evaluation framework

  2014cited by this paper
• Climate-smart agriculture for food security

  2014cited by this paper
• Veracity Roadmap: Is Big Data Objective, Truthful and Credible?

  2014cited by this paper
• A Big Data Guide to Understanding Climate Change: The Case for Theory-Guided Data Science

  2014cited by this paper
• Input selection and optimisation for monthly rainfall forecasting in Queensland, Australia, using artificial neural networks

  2014cited by this paper
• MPING: Crowd-Sourcing Weather Reports for Research

  2014cited by this paper
• Big data: a revolution that will transform how we live, work, and think

  2014cited by this paper
• Mapping the Data Shadows of Hurricane Sandy: Uncovering the Sociospatial Dimensions of ‘Big Data’

  2014cited by this paper
• Statistical significance of climate sensitivity predictors obtained by data mining

  2014cited by this paper
• Improved statistical downscaling of daily precipitation using SDSM platform and data‐mining methods

  2013cited by this paper
• Multi-variate flood damage assessment: a tree-based data-mining approach

  2013cited by this paper
• Establishing and assessing the Integrated Surface Drought Index (ISDI) for agricultural drought monitoring in mid-eastern China

  2013cited by this paper
• Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

  2013cited by this paper
• Performance assessment of different data mining methods in statistical downscaling of daily precipitation

  2013cited by this paper
• Crowdsourcing urban air temperatures from smartphone battery temperatures

  2013cited by this paper
• Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning

  2013cited by this paper
• Quantifying the Digital Traces of Hurricane Sandy on Flickr

  2013cited by this paper
• Solar forecasting methods for renewable energy integration

  2013cited by this paper
• Big Data: A Revolution That Will Transform How We Live, Work, and Think

  2013cited by this paper
• Predictor Screening, Calibration, and Observational Constraints in Climate Model Ensembles: An Illustration Using Climate Sensitivity

  2013cited by this paper
• Current methods and advances in forecasting of wind power generation

  2012cited by this paper
• CRITICAL QUESTIONS FOR BIG DATA

  2012cited by this paper
• Tornadic Supercell Environments Analyzed Using Surface and Reanalysis Data: A Spatiotemporal Relational Data-Mining Approach

  2012cited by this paper
• Application of artificial neural networks to rainfall forecasting in Queensland, Australia

  2012cited by this paper
• Daily streamflow forecasting by machine learning methods with weather and climate inputs

  2012cited by this paper
• A comparison of three methods for downscaling daily precipitation in the Punjab region

  2011cited by this paper
• Climate Data Challenges in the 21st Century

  2011cited by this paper
• An artificial neural network technique for downscaling GCM outputs to RCM spatial scale

  2011cited by this paper
• Reconstruction of regional mean sea level anomalies from tide gauges using neural networks

  2010cited by this paper
• Statistical downscaling of daily precipitation using support vector machines and multivariate analysis

  2010cited by this paper
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction

  2010cited by this paper
• Temporal downscaling: a comparison between artificial neural network and autocorrelation techniques over the Amazon Basin in present and future climate change scenarios

  2010cited by this paper
• Constructing climate knowledge with computer models

  2010cited by this paper
• Statistical downscaling of GCM simulations to streamflow using relevance vector machine

  2008cited by this paper
• Should we believe model predictions of future climate change?

  2008cited by this paper
• Complex hybrid models combining deterministic and machine learning components for numerical climate modeling and weather prediction

  2006cited by this paper
• Downscaling of precipitation for climate change scenarios: A support vector machine approach

  2006cited by this paper
• A Climate Modelling Primer: McGuffie/A Climate Modelling Primer

  2005cited by this paper
• Industry Report: Amazon.com Recommendations: Item-to-Item Collaborative Filtering

  2003cited by this paper

• Science for a Fragile World

  2025cites this paper
• Various responses of global heterotrophic respiration to variations in soil moisture and temperature enhance the positive feedback on atmospheric warming

  2025cites this paper
• ASSESSMENT OF CLIMATE CHANGE AWARENESS AMONG RURAL FOREST COMMUNITIES

  2025cites this paper
• Convolutional neural network based reconstruction of flow-fields from concentration fields for liquid-droplet coalescence

  2025cites this paper
• Comprehensive Survey of Artificial Intelligence Techniques and Strategies for Climate Change Mitigation

  2024cites this paper
• Neuromorphic Optical Data Storage Enabled by Nanophotonics: A Perspective

  2024cites this paper
• EmpireDB: Data System to Accelerate Computational Sciences

  2024cites this paper
• Big data applications: overview, challenges and future

  2024cites this paper
• Liquid-Droplet Coalescence: CNN-based Reconstruction of Flow Fields from Concentration Fields

  2024cites this paper
• Understanding the variability of ground-level ozone and fine particulate matter over the Tibetan plateau with data-driven approach.

  2024cites this paper
• Generative deep learning for data generation in natural hazard analysis: motivations, advances, challenges, and opportunities

  2024cites this paper
• Gauge-Optimal Approximate Learning for Small Data Classification

  2024cites this paper
• Geospatial modeling of climate change indices at Mexico City using machine learning regression

  2024cites this paper
• Recently emerging trends in big data analytic methods for modeling and combating climate change effects

  2024cites this paper
• A Generative AI Approach to Pricing Mechanisms and Consumer Behavior in the Electric Vehicle Charging Market

  2024cites this paper
• Assessing social contracts for urban adaptation through social listening on Twitter

  2023cites this paper
• Forest microbiome and global change

  2023cites this paper
• HARNESSING XGBOOST 2.0: A LEAP FORWARD IN CLIMATE SCIENCE ANALYTICS

  2023cites this paper
• Deep Learning‐Based Seasonal Forecast of Sea Ice Considering Atmospheric Conditions

  2023cites this paper
• AI for climate impacts: applications in flood risk

  2023cites this paper
• Gauge-optimal approximate learning for small data classification problems

  2023cites this paper
• The Digital Revolution in the Urban Water Cycle and Its Ethical–Political Implications: A Critical Perspective

  2022cites this paper
• Studying the Impact of Health Education on Student Knowledge and Behavior through Big Data and Cloud Computing

  2022cites this paper
• Computational methods for the analysis of climate change communication: Towards an integrative and reflexive approach

  2022cites this paper
• Improving debris flow evacuation alerts in Taiwan using machine learning

  2022cites this paper
• Unveiling spatial patterns of disaster impacts and recovery using credit card transaction fluctuations

  2022cites this paper
• Quantifying causal pathways of teleconnections

  2021cites this paper
• Unveiling Spatial Patterns of Disaster Impacts and Recovery Using Credit Card Transaction Variances

  2021cites this paper
• Orders of Social Science: Understanding Social-Scientific Controversies and Confluence on What “High-Quality” Knowledge and “Good” Adaptation Is

  2021cites this paper
• Greening of the earth does not compensate for rising soil heterotrophic respiration under climate change

  2021cites this paper
• Assessing the representational accuracy of data-driven models: The case of the effect of urban green infrastructure on temperature

  2021cites this paper
• Intelligent Environmental Art Design Combining Big Data and Artificial Intelligence

  2021cites this paper
• The Usage of Big Data and Data Analytics in the Study of Climate Change

  2021cites this paper
• Urban multi-model climate projections of intense heat in Switzerland

  2021cites this paper
• Unraveling the Impact of Land Cover Changes on Climate Using Machine Learning and Explainable Artificial Intelligence

  2021cites this paper
• Artificial intelligence: A powerful paradigm for scientific research

  2021cites this paper
• A balance exists between vegetation recovery and human development over the past 30 years in the Guizhou Plateau, China

  2021cites this paper
• Varieties of Data-Centric

  2021cites this paper
• Big data and prediction: Four case studies.

  2020cites this paper
• Crowdsourcing and IoT Towards More Resilient Flooding Prone Cities

  2020cites this paper
• Toward Data‐Driven Generation and Evaluation of Model Structure for Integrated Representations of Human Behavior in Water Resources Systems

  2020influential citation
• Big Data Architectures for the Climate Change Analysis: A Systematic Mapping Study

  2020cites this paper
• Current needs for climate services in West Africa: Results from two stakeholder surveys

  2020cites this paper
• Predicting global patterns of long-term climate change from short-term simulations using machine learning

  2020cites this paper
• Assessment of Predictive Uncertainty of Data-Driven Environmental Models

  2020cites this paper
• Extended Range Arctic Sea Ice Forecast with Convolutional Long-Short Term Memory Networks

  2020influential citation
• To act or not to act: Warning communication and decision-making in response to weather-related hazards

  2020cites this paper
• Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning

  2020cites this paper
• Big data in agriculture: Does the new oil lead to sustainability?

  2020cites this paper
• The fourth-revolution in the water sector encounters the digital revolution.

  2020cites this paper
• Using remarkability to define coastal flooding thresholds

  2020cites this paper
• Risk Forecasting in the Light of Big Data

  2020cites this paper
• Enhanced Artificial Neural Network with Harris Hawks Optimization for Predicting Scour Depth Downstream of Ski-Jump Spillway

  2020cites this paper
• Climate-induced population displacement in sub-Saharan Africa: A review of resilience-building strategies

  2020cites this paper
• Do intentions indicate actual behaviour? A comparison between scenario‐based experiments and real‐time observations of warning response

  2020cites this paper
• Understanding climate phenomena with data-driven models.

  2020cites this paper
• Argument-based assessment of predictive uncertainty of data-driven environmental models

  2020influential citation
• Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles

  2020cites this paper
• Artificial Intelligence and Machine Learning to Assist Climate Change Monitoring

  2020cites this paper
• A new international initiative for facilitating data-driven Earth science transformation

  2020cites this paper
• Selection of optimal proxy locations for temperature field reconstructions using evolutionary algorithms

  2020cites this paper
• Current needs for climate services in West Africa: Results from two stakeholder surveys

  2020cites this paper
• The Impact of Geographic Scale on Identifying Different Social Media Behavior Extremes in Crisis Research

  2019cites this paper
• Machine learning and artificial intelligence to aid climate change research and preparedness

  2019cites this paper
• Weather Forecasting With Optimization Based Neural Network Classification

  year unknowncites this paper
• Arti fi cial intelligence: A powerful paradigm for scienti fi c research

  year unknowncites this paper
• Artificial intelligence and machine learning for phases and transitions in the Ising model: an overview

  year unknowncites this paper