scholarly journals Improving prediction and assessment of global fires using multilayer neural networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jaideep Joshi ◽  
Raman Sukumar
Keyword(s):  
Global Climate ◽  
Grid Cell ◽  
Temporal Correlation ◽  
Environmental Drivers ◽  
Future Climate Change ◽  
Burned Area ◽  
Climate Change Scenarios ◽  
Data Driven Approach ◽  
Climate Interactions ◽  
Fire Climate Interactions

AbstractFires determine vegetation patterns, impact human societies, and are a part of complex feedbacks into the global climate system. Empirical and process-based models differ in their scale and mechanistic assumptions, giving divergent predictions of fire drivers and extent. Although humans have historically used and managed fires, the current role of anthropogenic drivers of fires remains less quantified. Whereas patterns in fire–climate interactions are consistent across the globe, fire–human–vegetation relationships vary strongly by region. Taking a data-driven approach, we use an artificial neural network to learn region-specific relationships between fire and its socio-environmental drivers across the globe. As a result, our models achieve higher predictability as compared to many state-of-the-art fire models, with global spatial correlation of 0.92, monthly temporal correlation of 0.76, interannual correlation of 0.69, and grid-cell level correlation of 0.60, between predicted and observed burned area. Given the current socio-anthropogenic conditions, Equatorial Asia, southern Africa, and Australia show a strong sensitivity of burned area to temperature whereas northern Africa shows a strong negative sensitivity. Overall, forests and shrublands show a stronger sensitivity of burned area to temperature compared to savannas, potentially weakening their status as carbon sinks under future climate-change scenarios.

scholarly journals Improving prediction and assessment of global wildfires using neural networks

2020 ◽  
Author(s):  
Jaideep Joshi ◽  
Raman Sukumar
Keyword(s):  
Global Climate ◽  
Grid Cell ◽  
Temporal Correlation ◽  
Environmental Drivers ◽  
Future Climate Change ◽  
Burned Area ◽  
Climate Change Scenarios ◽  
Data Driven Approach ◽  
Fire Climate Interactions ◽  
In Fire

ABSTRACTFires determine vegetation patterns, impact human societies, and provide complex feedbacks into the global climate system. Empirical and process-based models differ in their scale and mechanistic assumptions, giving divergent predictions of fire drivers and extent. Especially, the role of anthropogenic drivers remains less understood. Taking a data-driven approach, we use an artificial neural network to learn region-specific relationships between fire and its socio-environmental drivers across the globe. As a result, our models achieve higher predictability than previously reported, with global spatial correlation of 0.92, temporal correlation of 0.76, interannual correlation of 0.69, and grid-cell level correlation of 0.6, between predicted and observed burned area. Our analysis reveals universal global patterns in fire-climate interactions, coupled with strong regional differences in fire-human relationships. Given the current socio-anthropogenic conditions, Equatorial Asia, southern Africa, and Australia show a strong sensitivity of fire extent to temperature whereas northern Africa shows a strong negative sensitivity. Overall, forests and shrublands, show a stronger sensitivity of burned area to temperature compared to savannas, potentially weakening their status as carbon sinks under future climate-change scenarios.

scholarly journals Downscale of future climate change scenarios applied to Recife-PE

2020 ◽  
Vol 9 (6) ◽  
pp. 361
Author(s):  
Rafaela Lisboa Costa ◽  
Heliofábio Barros Gomes ◽  
Fabrício Daniel Dos Santos Silva ◽  
Rodrigo Lins Da Rocha Júnior
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Future ◽  
Maximum Temperatures

The objective of this work was to analyze and compare results from two generations of global climate models (GCMs) simulations for the city of Recife-PE: CMIP3 and CMIP5. Differences and similarities in historical and future climate simulations are presented for four GCMs using CMIP3 scenarios A1B and A2 and for seven CMIP5 scenarios RCP4.5 and RCP8.5. The scale reduction technique applied to GCMs scenarios is statistical downscaling, employing the same set of large-scale atmospheric variables as predictors for both sets of scenarios, differing only in the type of reanalysis data used to characterize surface variables precipitation, maximum and minimum temperatures. For CMIP3 scenarios the simulated historical climate is 1961-1990 and CMIP5 is 1979-2000, and the validation period is ten years, 1991-2000 for CMIP3 and 2001-2010 for CMIP5. However, for both the future period analyzed is 2021-2050 and 2051-2080. Validation metrics indicated superior results from the historical simulations of CMIP5 over those of CMIP3 for precipitation and minimum and similar temperatures for maximum temperatures. For the future, both CMIP3 and CMIP5 scenarios indicate reduced precipitation and increased temperatures. The potencial evapotranspiration was calculated, projected to increase in scenarios A1B and A2 of CMIP3 and with behavior similar to that observed historically in scenarios RCP4.5 and 8.5.

Understanding and predicting climate extremes on land: The new frontier

2021 ◽  
Author(s):  
Sonia Seneviratne
Keyword(s):  
Global Climate ◽  
Land Use Changes ◽  
Carbon Capture And Storage ◽  
Grid Cell ◽  
Climate Extremes ◽  
Future Research ◽  
Climate Mitigation ◽  
Climate Interactions ◽  
Warming World ◽  
Land Water

<p>We live on land and are daily affected by land climate variations, but early climate pioneers often focused on ocean-climate interactions and ice-covered regions. With good reasons, since oceans cover two third of the Earth and are thus critical for the global climate, and because ice sheets have strongly varied over millennia and include key indices on past climate. However, recent research has increasingly shown that land climate, where we live, displays specific climate characteristics, which cannot be simply inferred from global climate responses. This is particularly the case for climate extremes, such as heatwaves and droughts. I will present recent evidence for these properties and some avenues for future research.</p><p>Land-climate interactions, which are modulated by vegetation, play a key role for climate variability on continents. This implies a fascinating interface between biological processes and climate physics. The limitation of water on continents, and the role of vegetation in the land water input to the atmosphere, implies very different water-cycle responses compared to what is seen on oceans: For instance, dry regions do not necessarily get drier, nor wet regions wetter under increasing greenhouse gas forcing. In addition, land climate can strongly deviate from global climate in other ways: During the so-called “hiatus period” in the early 2000s, changes in temperature extremes on land actually showed an amplified increase. Furthermore, key land processes are still insufficiently captured in state-of-the art Earth System Models (ESMs), such as land water effects on the global carbon cycle, and climate response to irrigation or land management.</p><p>Land processes are playing an increasingly central role in the development of pathways for climate mitigation consistent with the aims of the Paris Agreement, for instance related to afforestation or the development of bioenergy use in combination with carbon capture and storage. However, these scenarios often overlook biological and physical constraints for these land cover and land use changes, such as risks from climate extremes, including fire, in a warming world. ESM emulators for grid-cell responses may help to proof such scenarios in the needed rapid and safe transition to a net-zero CO<sub>2 </sub>world.</p>

scholarly journals Determinants and predictability of global wildfire emissions

2012 ◽  
Vol 12 (15) ◽  
pp. 6845-6861 ◽  
Author(s):  
W. Knorr ◽  
V. Lehsten ◽  
A. Arneth
Keyword(s):  
Biomass Burning ◽  
Trace Gases ◽  
Ecosystem Dynamics ◽  
Future Climate Change ◽  
Burned Area ◽  
Climate Change Scenarios ◽  
Radiative Balance ◽  
Terrestrial Ecosystem Model ◽  
Fuel Loads ◽  
Simulated Fuel

Abstract. Biomass burning is one of the largest sources of atmospheric trace gases and aerosols globally. These emissions have a major impact on the radiative balance of the atmosphere and on air quality, and are thus of significant scientific and societal interest. Several datasets have been developed that quantify those emissions on a global grid and offered to the atmospheric modelling community. However, no study has yet attempted to systematically quantify the dependence of the inferred pyrogenic emissions on underlying assumptions and input data. Such a sensitivity study is needed for understanding how well we can currently model those emissions and what the factors are that contribute to uncertainties in those emission estimates. Here, we combine various satellite-derived burned area products, a terrestrial ecosystem model to simulate fuel loads and the effect of fire on ecosystem dynamics, a model of fuel combustion, and various emission models that relate combusted biomass to the emission of various trace gases and aerosols. We carry out simulations with varying parameters for combustion completeness and fuel decomposition rates within published estimates, four different emissions models and three different global burned-area products. We find that variations in combustion completeness and simulated fuel loads have the largest impact on simulated global emissions for most species, except for some with highly uncertain emission factors. Variation in burned-area estimates also contribute considerably to emission uncertainties. We conclude that global models urgently need more field-based data for better parameterisation of combustion completeness and validation of simulated fuel loads, and that further validation and improvement of burned area information is necessary for accurately modelling global wildfire emissions. The results are important for chemical transport modelling studies, and for simulations of biomass burning impacts on the atmosphere under future climate change scenarios.

scholarly journals Climate Change Impact Assessment on the Precipitation over the Ghataprabha Sub-Basin, India under Future Climate Change Scenarios

2021 ◽  
Author(s):  
Nagendra Reddy ◽  
Nagraj S Patil ◽  
Rajashekhar S Laddimath
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Global Climate Model ◽  
Percentage Change ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Climate Variables ◽  
Rcp Scenarios ◽  
Increasing Trend

Abstract The present study has been taken up to quantify the possible impacts of the climate change on the climate variables using the outputs of global climate models datasets over the Ghataprabha Sub-basin. The climate variables (precipitation, maximum and minimum temperature) data from the five selected global climate model dataset were downscaled using change factor method under four representative concentration pathway (RCP 2.6, 4.5, 6.0, and 8.5) scenarios for future periods near-century (2010-2039), mid-century (2040-2069), and end-century (2070-2099). The downscaled results of all the five models were ensembled using multi-model ensembling method to reduce the uncertainty in the projected results and the percentage change in the climate variables were shown with respect to the historical/baseline period (1961-1990) using spatial plots and histograms. The future projected results shows that percentage change in the annual mean precipitation with respect to the historical (1961-1990), is decreasing for most of the grids in the study area during the near-century while during mid and end centuries it shows an increasing trend across all the four RCP scenarios. The average daily minimum and maximum temperature with respect to the historical (1961-1990) values were showing an increasing trend in the study area during the near, mid, and end centuries across all the four RCP scenarios. Further, study also analysed the percentage change in 100-year return level over the study area.

Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina

Zootaxa ◽  
2017 ◽  
Vol 4237 (1) ◽  
pp. 91 ◽  
Author(s):  
IGNACIO MINOLI ◽  
LUCIANO JAVIER AVILA
Keyword(s):  
Climate Change ◽  
Habitat Use ◽  
Global Climate ◽  
Co2 Concentration ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Future Scenarios ◽  
Lizard Species ◽  
Restricted Use

The consequences of global climate change can already be seen in many physical and biological systems and these effects could change the distribution of suitable areas for a wide variety of organisms to the middle of this century. We analyzed the current habitat use and we projected the suitable area of present conditions into the geographical space of future scenarios (2050), to assess and quantify whether future climate change would affect the distribution and size of suitable environments in two Pristidactylus lizard species. Comparing the habitat use and future forecasts of the two studied species, P. achalensis showed a more restricted use of available resource units (RUs) and a moderate reduction of the potential future area. On the contrary, P. nigroiugulus uses more available RUs and has a considerable area decrease for both future scenarios. These results suggest that both species have a moderately different trend towards reducing available area of suitable habitats, the persistent localities for both 2050 CO2 concentration models, and in the available RUs used. We discussed the relation between size and use of the current habitat, changes in future projections along with the protected areas from present-future and the usefulness of these results in conservation plans. This work illustrates how ectothermic organisms might have to face major changes in their availability suitable areas as a consequence of the effect of future climate change.  

scholarly journals Determinants and predictability of global wildfire emissions

2012 ◽  
Vol 12 (2) ◽  
pp. 4243-4278 ◽  
Author(s):  
W. Knorr ◽  
V. Lehsten ◽  
A. Arneth
Keyword(s):  
Biomass Burning ◽  
Trace Gases ◽  
Combustion Process ◽  
Fuel Combustion ◽  
Ecosystem Dynamics ◽  
Future Climate Change ◽  
Burned Area ◽  
Climate Change Scenarios ◽  
Data Set ◽  
Terrestrial Ecosystem Model

Abstract. Biomass burning is one of the largest sources of atmospheric trace gases and aerosols globally. These emissions have a major impact on the radiative balance of the atmosphere and on air quality, and are thus of significant scientific and societal interest. Several datasets have been developed that quantify those emissions on a global grid and offered to the atmospheric modelling community. However, no study has yet attempted to systematically quantify the dependence of the inferred pyrogenic emissions on underlying assumptions and input data. Such a sensitivity study is needed for understanding how well we can currently model those emissions and what the factors are that contribute to uncertainties in those emissions estimates. Here, we combine various satellite-derived burned area products, a terrestrial ecosystem model to simulate fuel loads and the effect of fire on ecosystem dynamics, a model of fuel combustion, and various emission models that relate combusted biomass to the emission of various trace gases and aerosols. We vary one key parameter of a simple fuel combustion model, the emission model, and the burned area product and assess its impact on the computed emissions fields and their uncertainties. We find that choice of burned area data set has by far the largest impact on interannual variability of simulated emissions. For total global emissions, burned area and combustion completeness have the largest impact on emissions for most species. We conclude that reliable information on burned area is key for accurately modelling spatial and interannual variations of wildfire emissions, but uncertainties about the combustion process have a similar impact on the magnitude of global emission estimates. The results are important for chemical transport modelling studies, and for simulations of biomass burning impacts on the atmosphere under future climate change scenarios.

Suitable regions for date palm cultivation in Iran are predicted to increase substantially under future climate change scenarios

2013 ◽  
Vol 152 (4) ◽  
pp. 543-557 ◽  
Author(s):  
F. SHABANI ◽  
L. KUMAR ◽  
S. TAYLOR
Keyword(s):  
Climate Change ◽  
Date Palm ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Soil Types ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Soil Taxonomy ◽  
Palm Distribution

SUMMARYThe objective of the present paper is to use CLIMEX software to project how climate change might impact the future distribution of date palm (Phoenix dactylifera L.) in Iran. Although the outputs of this software are only based on the response of a species to climate, the CLIMEX results were refined in the present study using two non-climatic parameters: (a) the location of soils containing suitable physicochemical properties and (b) the spatial distribution of soil types having suitable soil taxonomy for dates, as unsuitable soil types impose problems in air permeability, hydraulic conductivity and root development. Here, two different Global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H (MR), were employed with the A2 emission scenario to model the potential date palm distribution under current and future climates in Iran for the years 2030, 2050, 2070 and 2100. The results showed that only c. 0·30 of the area identified as suitable by CLIMEX will actually be suitable for date palm cultivation: the rest of the area comprises soil types that are not favourable for date palm cultivation. Moreover, the refined outputs indicate that the total area suitable for date palm cultivation will increase to 31·3 million ha by 2100, compared with 4·8 million ha for current date palm cultivation. The present results also indicate that only heat stress will have an impact on date palm distribution in Iran by 2100, with the areas currently impacted by cold stress diminishing by 2100.

What we can learn from the parallels between the COVID-19 and the future climate change crises

2020 ◽  
Author(s):  
Rubén D. Manzanedo ◽  
Peter Manning
Keyword(s):  
Climate Change ◽  
Global Economy ◽  
Global Climate ◽  
Future Climate Change ◽  
Substantial Portion ◽  
Preventative Measures ◽  
The Future ◽  
Behavioral Norm ◽  
Climate Crisis ◽  
Global Population

The ongoing COVID-19 outbreak pandemic is now a global crisis. It has caused 1.6+ million confirmed cases and 100 000+ deaths at the time of writing and triggered unprecedented preventative measures that have put a substantial portion of the global population under confinement, imposed isolation, and established ‘social distancing’ as a new global behavioral norm. The COVID-19 crisis has affected all aspects of everyday life and work, while also threatening the health of the global economy. This crisis offers also an unprecedented view of what the global climate crisis may look like. In fact, some of the parallels between the COVID-19 crisis and what we expect from the looming global climate emergency are remarkable. Reflecting upon the most challenging aspects of today’s crisis and how they compare with those expected from the climate change emergency may help us better prepare for the future.

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