Joaquín Bedia
YOU?
Author Swipe
View article: Challenges in assessing Fire Weather changes in a warming climate
Challenges in assessing Fire Weather changes in a warming climate Open
The Canadian Fire Weather Index (FWI), widely used to assess wildfire danger, typically relies on noon-specific meteorological data. However, climate models often provide only daily aggregated values, posing a challenge for accurate FWI ca…
View article: Deep Learning Emulation of Multivariate Climate Indices: A Case Study of the Fire Weather Index in the Iberian Peninsula
Deep Learning Emulation of Multivariate Climate Indices: A Case Study of the Fire Weather Index in the Iberian Peninsula Open
The Fire Weather Index (FWI) is an essential multivariate climate index for assessing wildfire risk and the associated impacts of climate change, as it provides a quantitative measure of wildfire danger by integrating different critical ne…
View article: Global Extra-tropical Circulation Database based on the Jenkinson-Collison Classification calculated with 6-hourly mean sea-level pressure fields from various reanalysis datasets
Global Extra-tropical Circulation Database based on the Jenkinson-Collison Classification calculated with 6-hourly mean sea-level pressure fields from various reanalysis datasets Open
Dataset Description Global Extra-tropical Circulation Database based on the Jenkinson-Collison Classification calculated with 6-hourly mean sea-level pressure fields from several reanalysis datasets. This dataset is the result of an extens…
View article: Projected changes of tourism comfort in northern Spain under climate change
Projected changes of tourism comfort in northern Spain under climate change Open
Cantabria, a region in the north of Spain, known for offering the possibility of skiing and enjoying the beach in less than an hour, has experienced a remarkable growth in tourism in the last 15 years. Although the region only accounts for…
View article: Daily Data-Driven Emulation of the Fire Weather Index: Deep Learning Solutions for Wildfire Risk Prediction
Daily Data-Driven Emulation of the Fire Weather Index: Deep Learning Solutions for Wildfire Risk Prediction Open
Wildfires are an intensifying global challenge, driven by climate change, which increases their frequency, severity, and spatial extent. Accurate wildfire risk assessment and forecasting are essential for effective mitigation, resource all…
View article: Skillful seasonal predictions of extended summer drought and fire risk from southern Europe to the Middle East
Skillful seasonal predictions of extended summer drought and fire risk from southern Europe to the Middle East Open
The present study uncovers the capability of the ECMWF SEAS5 seasonal forecasting system to skillfully forecast the May-to-September Standardized Precipitation Evapotranspiration and Fire Weather indices (SPEI, FWI) in southern Europe and …
View article: Overestimating Fire Weather Trends: Challenges in Using Daily Climate Data
Overestimating Fire Weather Trends: Challenges in Using Daily Climate Data Open
The Fire Weather Index (FWI) is a widely used metric for assessing wildfire danger, relying on sub-daily meteorological data, typically recorded at local noon. However, most climate models and observational datasets only provide daily-aggr…
View article: Refining remote sensing precipitation datasets in the South Pacific with an adaptive multi-method calibration approach
Refining remote sensing precipitation datasets in the South Pacific with an adaptive multi-method calibration approach Open
Calibration techniques refine numerical model outputs for climate research, often preferred for their simplicity and suitability in many climate impact applications. Atmospheric pattern classifications for conditioned transfer function cal…
View article: Toward Spatio‐Temporally Consistent Multi‐Site Fire Danger Downscaling With Explainable Deep Learning
Toward Spatio‐Temporally Consistent Multi‐Site Fire Danger Downscaling With Explainable Deep Learning Open
This study introduces a novel Convolutional Long Short‐Term Memory neural networks (ConvLSTM)‐based multi‐site downscaling approach for fire danger prediction, that leverages the properties of Long‐Short Term Memory (LSTM) Recursive Neural…
View article: The signature of the main modes of climatic variability as revealed by the Jenkinson‐Collison classification over Europe
The signature of the main modes of climatic variability as revealed by the Jenkinson‐Collison classification over Europe Open
The Jenkinson‐Collison Weather Typing (JC‐WT) method uses sea‐level pressure gradients to create 27 types based on the geostrophic flow and vorticity around any extratropical target location. Typically, JC‐WTs are applied over specific loc…
View article: Multi-Site Fire Danger Prediction Using a Spatially Coherent Convolutional Neural Network Model
Multi-Site Fire Danger Prediction Using a Spatially Coherent Convolutional Neural Network Model Open
Weather stations can represent local weather variability and extremes more reliably than gridded products and are therefore better suited for local climate impact applications like calculation of the Fire Weather Index (FWI), a multivariat…
View article: The Interannual Variability of Global Burned Area Is Mostly Explained by Climatic Drivers
The Interannual Variability of Global Burned Area Is Mostly Explained by Climatic Drivers Open
Better understanding how fires respond to climate variability is an issue of current interest in light of ongoing climate change. However, evaluating the global‐scale temporal variability of fires in response to climate presents a challeng…
View article: Global changes in low-level circulation types under future anthropogenic forcing
Global changes in low-level circulation types under future anthropogenic forcing Open
Large-scale atmospheric circulation determines regional near-surface climate and, ultimately, causes diverse impacts on ecosystems and societies. Possible modifications of such large-scale features due to global warming would inevitably le…
View article: Spatially Consistent Fire Weather Index Predictions using Convolutional Neural Networks in Diverse Iberian Locations
Spatially Consistent Fire Weather Index Predictions using Convolutional Neural Networks in Diverse Iberian Locations Open
The accurate prediction of the Fire Weather Index (FWI) is vital for effective wildfire management and climate-resilient planning. Multisite fire hazard forecasts are crucial for resource allocation, early intervention in high-risk areas, …
View article: Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions
Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions Open
The accurate prediction of the Fire Weather Index (FWI), a multivariate climate index for wildfire risk characterization, is crucial for both wildfire management and climate-resilient planning. Moreover, consistent multisite fire danger pr…
View article: Data --- "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions"
Data --- "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions" Open
Data to reproduce the results of the manuscript entitled "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions" submitted to Geophysical Research Letters. The companion jupyter noteb…
View article: Data --- "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions"
Data --- "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions" Open
Data to reproduce the results of the manuscript entitled "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions" submitted to Geophysical Research Letters. The companion jupyter noteb…
View article: Fire Season Multi-Resolution Database
Fire Season Multi-Resolution Database Open
In the realm of wildfire research and analysis, the need for comprehensive and adaptable datasets has never been more critical. To address this imperative, we introduce the "Fire Season Multi-Resolution Database." This meticulously curated…
View article: Fire Season Multi-Resolution Database
Fire Season Multi-Resolution Database Open
In the realm of wildfire research and analysis, the need for comprehensive and adaptable datasets has never been more critical. To address this imperative, we introduce the "Fire Season Multi-Resolution Database." This meticulously curated…
View article: Fire Season Multi-Resolution Database
Fire Season Multi-Resolution Database Open
In the realm of wildfire research and analysis, the need for comprehensive and adaptable datasets has never been more critical. To address this imperative, we introduce the "Fire Season Multi-Resolution Database." This meticulously curated…
View article: Data supporting manuscript "Regional scaling of sea surface temperature with global warming levels in the CMIP6 ensemble"
Data supporting manuscript "Regional scaling of sea surface temperature with global warming levels in the CMIP6 ensemble" Open
Data supporting the results presented in the article Milovac et al: "Regional scaling of sea surface temperature with global warming levels in the CMIP6 ensemble". 1. data_raw.tar contains annual and seasonal, global and regional (i.e. ove…
View article: Data supporting manuscript "Regional scaling of sea surface temperature with global warming levels in the CMIP6 ensemble"
Data supporting manuscript "Regional scaling of sea surface temperature with global warming levels in the CMIP6 ensemble" Open
Data supporting the results presented in the article Milovac et al: "Regional scaling of sea surface temperature with global warming levels in the CMIP6 ensemble". 1. data_raw.tar contains annual and seasonal, global and regional (i.e. ove…
View article: A monthly gridded burned area database of national wildland fire data (ONFIRE)
A monthly gridded burned area database of national wildland fire data (ONFIRE) Open
We assembled the first gridded burned area (BA) database of national wildfire data (ONFIRE), a comprehensive and integrated resource for researchers, non-government organisations, and government agencies analysing wildfires in various regi…
View article: Refining Remote Sensing precipitation Datasets in the South Pacific: An Adaptive Multi-Method Approach for Calibrating the TRMM Product
Refining Remote Sensing precipitation Datasets in the South Pacific: An Adaptive Multi-Method Approach for Calibrating the TRMM Product Open
Calibration techniques are gaining popularity in climate research for refining numerical model outputs, favored for their relative simplicity and fitness-for-purpose in many climate impact applications. Their range of applicability goes be…
View article: A Global Climate Model Performance Atlas for the Southern Hemisphere Extratropics Based on Regional Atmospheric Circulation Patterns
A Global Climate Model Performance Atlas for the Southern Hemisphere Extratropics Based on Regional Atmospheric Circulation Patterns Open
The performance of 61 global climate models participating in CMIP5 and 6 is evaluated for the Southern Hemisphere extratropics in terms of typical regional‐scale atmospheric circulation patterns. These patterns are known to be linked with …
View article: Southern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses
Southern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses Open
This dataset comprises six-hourly Lamb Weather Type (LWT) time series covering the period 1979-2005 for a) historical experiments run with 61 distinct GCMs from CMIP5 and 6 (specified in "get_historical_metadata.py" published at https://do…
View article: Southern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses
Southern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses Open
This dataset comprises six-hourly Lamb Weather Type (LWT) time series covering the period 1979-2005 for a) historical experiments run with 61 distinct GCMs from CMIP5 and 6 (specified in "get_historical_metadata.py" published at https://do…