Embedded Files
I thought it was going to be straightforward to map the surface temperatures of the various ground covers and calculate the contributions of each and add them up worldwide.
But we are miles off being able to do this, despite the problem being global warming.
“As the globe becomes more urbanised and agricultural land use changes, changes in surface albedo and surface cover are likely to be important contributors to increasing mean soil temperature” (Santos et al 2014)
Albedo
Albedo
Albedo refers to the amount of solar radiation coming in that is reflected away. We should be talking about this much more.
There is a small difference, 3watts cubic metre, between what comes in and what goes out . This is 1% of the total coming in that is absorbed by earth, warming it up. If we could alter that small difference it would make a massive difference. And the soil surface has a major role to play
Soil temperature is strongly dependent on surface cover, which in turn affects the amount of incident shortwave radiation that is reflected by a surface - the albedo. Albedo is a key parameter that is widely used in land surface energy balance studies, mid-to-long-term weather prediction, and global climate change investigation.
Higher surface albedo" refers to the characteristic of a surface or object to reflect a greater amount of incoming solar radiation (sunlight) back into space rather than absorbing it. Albedo is a measure of reflectivity and is expressed as a ratio ranging from 0 to 1, where 0 represents a perfectly absorbing surface (no reflection) and 1 represents a perfectly reflecting surface (complete reflection). The higher the Albedo (towards 1) means less energy being absorbed by the surface, leading to lower surface temperatures.
Globally solar radiation comes in at 342 watts/cubic metre and 339 go back out. This means 3watts cubic metre - stays as energy. If we could alter that, even a little, it would make a massive difference. The soil surface has a major role to play. But we do not hear about that. Water - which transfers 90% of our heat transfer - also has massive role with no mention of carbon.
Albedo is a key parameter that is widely used in land surface energy balance studies, mid-to-long-term weather prediction, and global climate change investigation. An example is open ocean water which has a moderate albedo around 0.06, which means that it absorbs a lot of sunlight and contributes to ocean warming; however the sea has high capacity to absorb heat without temperature increasing, and then conductivity to move it around (Increased ocean heat not related with GHGs)
Again we see heating much faster since 1980, and more than GHGs alone cause.Over land the albedo is much more variable depending on the land surface. Snow has high albedo (reflectivity) but when it melts the brown earth has low albedo so absorbs more heat. . Forest and grassland are cooler than ploughed soil, because of a mixture of albedo and capacity. Can you picture yourself on a nice day lying on the grass, but you probably prefer not to lie on bare soil, and certainly not concrete as it is too warm. ‘Global’ temperatures measure air temperatures not land, so we have few worldwide comparisons of variation of warmth over different farm practices.
Black is nearer 0 as it absorbs more energy than white (nearer 1). Dark-coloured surfaces like asphalt or forests have lower albedo values because they absorb more sunlight. Snow and ice have high albedo values because they reflect a significant amount of sunlight. So when arctic snows melt to give way to trees, there will be more energy absorbed so the earth warms up.
It is not just a matter of colour. Croplands have a higher surface albedo compared with forested soils, but a lot get more sun to start with. Similarly, although brown/black, the surface cover in the form of decaying organic matter (i.e., mulch) can reduce the magnitude of soil temperature fluctuations, often keeping soil cooler than a bare soil surface when the atmosphere is warmer than the soil temperature.
Water & Albedo
Water & Albedo
Adding water decreases the albedo of any soil surface. “Throughout the year there is a constant change in the albedo of a soil surface. Starting with a smooth soil surface with an albedo of 0.20, the addition of water to a soil surface decreases the albedo to 0.15, with a slow return to the original value as the surface dries. Water is an effective absorber of short and longwave radiation and adding water decreases the albedo of any surface. If the same surface is roughened by tillage, there is a further decrease in the albedo of a dry surface to near 0.15. This decrease is due to the change in the soil surface that traps more direct- and diffuse-beam solar radiation because of the change from a smooth to a rough surface. Wetting this tilled surface further decreases the albedo. Adding a fresh crop residue increases the albedo because of the highly reflective nature of the crop residue; however, as the residue ages, the albedo decreases and may be only slightly different from the soil surface in the spring. Soil surfaces are continually undergoing changes that affect their albedo. This will impact the radiation balance and ultimately the evaporation of water from the surface, heating the air, and warming the soil." (Siegert 2014)
Albedo & Crops
Albedo & Crops
Annual albedo was higher with perennial ley and winter-sown crops (0.20) than with spring-sown crops (0.17) and bare soil (0.13). Thus these latter two absorb more heat (Sieber et al 2022) One study found changes in surface cover from woodland and herbaceous vegetation to cultivated land were shown to increase mean annual temperatures (MATs), with cultivated land exhibiting the highest soil temperature variability. Another study reported soil temperatures were reported to have increased by 1.5 and 0.4°C in turfgrass and forest, respectively, when compared to rural areas
The surface temperatures of pasture and arable land in temperate regions are influenced by their albedo, heat capacity, and thermal conductivity. On a sunny day that could lead to a difference where arable is 5-10C hotter than pasture. Here’s how...
1. Albedo (Reflectivity of Solar Radiation):
1. Albedo (Reflectivity of Solar Radiation):
Pasture: Pasture land, which is typically covered with grasses and plants, has a moderate albedo. The vegetation reflects more sunlight compared to bare soil but still absorbs a significant amount, leading to moderate surface heating.
Arable Land: Arable land often undergoes tillage, especially after harvest, which can expose bare soil. Bare soil generally has a lower albedo than vegetated surfaces, meaning it absorbs more sunlight and heats up more quickly. However, if crops are growing, the albedo can increase, similar to pasture, depending on the type of crop and its coverage.
Impact on Temperature: Arable land with exposed soil tends to heat up more due to a lower albedo, while pasture land stays cooler because of vegetation cover.
2. Heat Capacity (Ability to Store Heat):
2. Heat Capacity (Ability to Store Heat):
Pasture: The vegetation and moist soil in pasture areas tend to have a higher heat capacity. The presence of organic matter, root systems, and typically higher soil moisture in pasture land allows it to store more heat without significant changes in surface temperature.
Arable Land: Exposed arable soils, particularly if dry, have a lower heat capacity than pasture because bare soil heats up and cools down more rapidly. The heat stored in the top layer of soil in arable land is typically less, meaning surface temperatures can fluctuate more dramatically.
Impact on Temperature: Pasture land, with its higher heat capacity, tends to have more stable surface temperatures, while arable land exhibits more extreme temperature swings, especially during the day.
3. Thermal Conductivity (Rate of Heat Transfer through Material):
3. Thermal Conductivity (Rate of Heat Transfer through Material):
Pasture: The combination of vegetation and organic-rich, moist soils in pasture has relatively lower thermal conductivity. The insulating effect of the vegetation and root systems reduces the rate of heat transfer to deeper soil layers, keeping the surface cooler.
Arable Land: Arable soils, particularly those that are compacted or dry, tend to have higher thermal conductivity compared to pasture. This means that heat from the surface transfers more efficiently to deeper soil layers, but it also cools down faster at night.
Impact on Temperature: The higher thermal conductivity of arable land allows for quicker heating and cooling, leading to larger daily temperature variations, while pasture land with lower conductivity results in more moderated temperatures.
Pasture: Cooler surface temperatures due to moderate albedo, higher heat capacity, and lower thermal conductivity.
Arable Land: Warmer surface temperatures (especially for bare soil) due to lower albedo, lower heat capacity, and higher thermal conductivity, leading to larger temperature swings.
In temperate regions, these differences mean that pastures are often cooler and more stable in temperature, whereas arable land experiences greater extremes.
On a sunny day with a top air temperature of 30°C, the difference in surface temperature between pasture and arable land would primarily result from the factors discussed earlier: albedo, heat capacity, and thermal conductivity. Here's how this might play out quantitatively:
General Estimate of Surface Temperature Difference:
General Estimate of Surface Temperature Difference:
Pasture Land:
Albedo: Higher than bare soil, reflecting more sunlight and absorbing less heat.
Heat Capacity: Higher due to vegetation and moisture, meaning slower temperature changes.
Thermal Conductivity: Lower, which prevents rapid heating.
On such a day, the surface temperature of pasture land might be 2–6°C warmer than the air temperature, as the heat absorbed is less intense, and the cooling effect of transpiration from the plants also helps regulate surface temperature.
Estimated Surface Temperature: 32–36°C.Arable Land (bare soil or recently tilled soil):
Albedo: Lower, absorbing more heat, leading to more rapid heating.
Heat Capacity: Lower, especially if the soil is dry, meaning it heats up and cools down quickly.
Thermal Conductivity: Higher, allowing for quicker surface heating.
On a sunny day, the surface of arable land could be significantly hotter than the air temperature. Bare soils can absorb a lot of heat, raising surface temperatures by 10–15°C above the air temperature.
Estimated Surface Temperature: 40–45°C.
Expected Difference:
Expected Difference:
Pasture surface temperature: 32–36°C.
Arable surface temperature: 40–45°C.
The temperature difference between pasture and arable land on a sunny day with a 30°C maximum air temperature could be in the range of 5–10°C, with arable land being hotter due to its lower albedo and quicker heat absorption.
Factors That Could Influence This:
Factors That Could Influence This:
Moisture Levels: Wet soils or irrigated crops may moderate temperature rises, making the difference smaller.
Vegetation Cover on Arable Land: If crops or cover crops are present, arable land would behave more like pasture.
Wind: High wind speeds could cool both surfaces, reducing the difference slightly.
What proportion of the global warming over the last 50 years is due to that 'reflected' back by Greenhouse Gases' and that from 'lessened albedo' (heat reflection) across the world, in terms of changes in land use?
Can we measure this better going forward?
See Construction - paving - impacts on water precipitation. Rain changes as soon as land use changes. because grasslands have less evapotranspiration than forests. Paved land has less evapotranspiration than grasslands. Milan Milan makes the case we should be more concerned about water vapour with global warming.
Understanding the relative contributions of greenhouse gas (GHG) emissions and changes in land use (particularly those affecting albedo) to global warming over the past 50 years is crucial for accurately modeling climate change and informing effective policies. There are key factors, data requirements, and methodologies that would be needed to get to a more precise answer to this complex question.
We need to combine data on greenhouse gas concentrations, land use changes, albedo variations, and climate model outputs to quantify and compare their respective contributions to global warming. This involves complex modelling and data integration but can provide crucial insights into the relative roles of these factors in driving recent global warming, and may help us reduce the drametic rises over last 40 or so years. They certainly note be ignored.
Steps needed to answer this complex question:
Steps needed to answer this complex question:
To determine the proportion of global warming attributable to greenhouse gases and to changes in albedo due to land use, we need to analyze the radiative forcing (the change in energy balance) from both sources over the last 50 years. Here’s how we would go about it:
1. Quantify Radiative Forcing from Greenhouse Gases:
Historical Data on GHG Concentrations:
Collect data on atmospheric concentrations of key greenhouse gases (CO₂, CH₄, N₂O, etc.) from the 1970s to the present. This data is typically available from ice cores, direct atmospheric measurements, and satellite observations.
Radiative Forcing Calculations:
Use established formulas for radiative forcing due to each greenhouse gas. For example, the Intergovernmental Panel on Climate Change (IPCC) provides formulas to estimate the radiative forcing for CO₂, CH₄, and N₂O based on their concentrations.
Climate Sensitivity:
Incorporate climate sensitivity factors—how much the global average temperature is expected to increase in response to a doubling of CO₂ concentrations. This factor helps to estimate how the radiative forcing translates into temperature changes.
2. Quantify Radiative Forcing from Changes in Albedo Due to Land Use:
Land Use Change Data:
Obtain historical data on global land use changes over the past 50 years, such as deforestation rates, urban expansion, agricultural development, grassland conversion, and changes in wetland areas. This data can be gathered from satellite imagery, remote sensing databases, national land use inventories, and global land cover datasets (like those from NASA, ESA, or other climate monitoring agencies).
Albedo Change Measurements:
Measure changes in albedo associated with different land uses. For example, forests have a relatively low albedo compared to ice or snow, while urban areas and bare soil have a very low albedo. Satellite-based remote sensing tools (like MODIS, Landsat, and Sentinel missions) provide global albedo data across various surfaces.
Calculate Radiative Forcing Due to Albedo Changes:
Calculate the net change in radiative forcing due to albedo shifts by combining land use change data with surface albedo values. Integrate these changes over time to estimate the cumulative radiative forcing resulting from land use changes.
3. Use Climate Models to Combine and Compare the Impacts:
Coupled Climate Models:
Utilize Earth System Models (ESMs) or Global Climate Models (GCMs) that incorporate both greenhouse gas forcing and land use changes. These models can simulate the Earth's climate over time by factoring in various inputs, such as greenhouse gas emissions, aerosols, albedo changes, and feedback loops.
Isolate Contributions:
Run the models with different scenarios to isolate the impact of greenhouse gases from the impact of albedo changes. For example, one model run could include only greenhouse gas forcings, while another could include only land use changes. A combined run would show the net effect of both.
4. Conduct Attribution Studies:
Attribution Analysis:
Perform attribution studies to separate and quantify the contribution of each factor to observed global warming. These studies use statistical techniques and climate models to identify the specific causes of observed climate changes.
Use Observational Data:
Combine model outputs with observational data (temperature records, satellite observations, ground measurements) to validate model results and refine the estimates of each factor's contribution.
5. Account for Feedback Mechanisms and Interactions:
Feedback Loops:
Consider feedback mechanisms that amplify or dampen warming. For instance, warming due to greenhouse gases may cause ice melt, which further decreases albedo and accelerates warming. Similarly, changes in vegetation due to warming can affect albedo and greenhouse gas emissions.
Nonlinear Interactions:
Recognize that the relationship between greenhouse gases and albedo changes is not always linear. For example, increased temperatures due to GHGs may lead to changes in vegetation cover, which in turn affects albedo.
6. Synthesize Findings and Estimate Proportions:
Integrate and Compare Results:
Integrate all the data and results from models, observations, and attribution studies to estimate the relative contributions of greenhouse gases and land use changes (albedo effects) to global warming over the past 50 years.
Greenhouse Gases Reflecting Heat (Radiative Forcing):
This refers to the amount of heat trapped by greenhouse gases like CO₂, methane (CH₄), and nitrous oxide (N₂O), which absorb infrared radiation and re-emit it back to the Earth's surface, causing warming. This is a well-established driver of global warming.
Challenges and Uncertainties
Challenges and Uncertainties
Data Limitations:
Incomplete or inconsistent historical data on land use changes, GHG concentrations, and albedo measurements can introduce uncertainty.
Model Sensitivities:
Climate models vary in their sensitivity to different inputs, which can affect the results. Ensuring models are well-calibrated and validated against real-world data is crucial.
Feedback Complexity:
Understanding and modeling all the feedback loops and interactions between different factors (like CO₂-induced vegetation changes) adds complexity.
Lessened Albedo Due to Land Use Changes:
This refers to changes in the Earth's surface reflectivity (albedo) caused by human activities, such as deforestation, urbanization, agricultural expansion, and other land use changes. Lower albedo (darker surfaces) leads to more heat absorption and less reflection of solar radiation, contributing to warming.
Datasets
Datasets
Key Datasets and Resources Needed:
Key Datasets and Resources Needed:
Historical Greenhouse Gas Concentration Data:
Data from ice cores, NOAA's Global Monitoring Laboratory, Mauna Loa Observatory, and other atmospheric monitoring networks.
Land Use and Land Cover Data:
Data from satellite remote sensing (e.g., MODIS, Landsat, Copernicus Sentinel), FAO Global Forest Resources Assessment, and other global land cover datasets.
Albedo Data:
Albedo data from satellite sensors, such as MODIS, CERES, and MISR, which provide high-resolution measurements over time.
Climate Model Simulations:
Simulations from the Coupled Model Intercomparison Project (CMIP6) or other major climate modeling efforts that include both greenhouse gas and land use change scenarios.
Data Sources for Land Use and Albedo Alterations:
Data Sources for Land Use and Albedo Alterations:
Satellite-Based Remote Sensing Data:
Satellites are a primary tool for monitoring land use changes and albedo on a global scale. Remote sensing provides high-resolution, repeatable, and consistent data over time, making it a vital source for analyzing changes in land cover and surface reflectivity.
Key Satellite Missions and Sensors:
MODIS (Moderate Resolution Imaging Spectroradiometer):
Description: MODIS sensors, onboard NASA’s Terra and Aqua satellites, provide daily global coverage of the Earth's surface at resolutions of 250m, 500m, and 1km.
Data Products: MODIS offers various products relevant to land use and albedo, such as Land Cover Type (MCD12Q1), Surface Reflectance (MOD09A1), and Albedo (MCD43).
Applications: Used for detecting deforestation, urban expansion, agricultural land use changes, and measuring surface albedo across different land cover types.
Data Access: MODIS Data on NASA's EarthData.
Landsat Program:
Description: The Landsat program, a joint initiative of NASA and the US Geological Survey (USGS), has been providing high-resolution (30m) imagery since 1972, making it one of the longest continuous Earth observation datasets.
Data Products: Landsat data can be used to derive information on land use changes, vegetation cover, urbanization, and changes in surface albedo.
Applications: Ideal for detailed studies of land cover change, such as deforestation, reforestation, and agricultural expansion.
Data Access: Landsat Data on USGS Earth Explorer.
Sentinel-2 (European Space Agency - ESA):
Description: Sentinel-2 provides high-resolution optical imagery (10m to 60m) with a revisit time of 5 days, designed specifically for land monitoring.
Data Products: Includes data on land cover classification, vegetation monitoring, and surface albedo.
Applications: Particularly useful for tracking changes in agricultural fields, forests, urban areas, and surface reflectivity.
Data Access: Copernicus Open Access Hub.
ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer):
Description: ASTER is onboard NASA's Terra satellite and provides high-resolution images (15m to 90m) across 14 spectral bands.
Data Products: Offers data on surface reflectance, temperature, elevation, and surface albedo.
Applications: Suitable for monitoring volcanic activity, forest degradation, urban heat islands, and other land use changes.
Data Access: ASTER Data via NASA’s EarthData.
VIIRS (Visible Infrared Imaging Radiometer Suite):
Description: VIIRS, onboard the NOAA-NASA Suomi NPP satellite, provides high-quality data for monitoring land surface properties.
Data Products: Data on surface reflectance, vegetation indices, and albedo.
Applications: Useful for understanding land use changes and their impact on regional and global albedo.
Data Access: NOAA CLASS.
Global Land Cover and Land Use Databases:
These databases integrate satellite data, aerial photographs, and ground-based observations to provide consistent global datasets on land cover and land use changes.
Key Databases:
GLC (Global Land Cover):
Description: The GLC datasets provide global maps of land cover at various resolutions and classifications. Several organizations, such as the European Space Agency (ESA) and the UN’s Food and Agriculture Organization (FAO), produce these datasets.
Examples: ESA’s Climate Change Initiative (CCI) Land Cover Dataset, FAO's Global Land Cover-SHARE (GLC-SHARE).
Data Access: ESA CCI Land Cover and FAO GLC-SHARE.
HILDA+ (Historical Land-Cover and Land-Use Database):
Description: HILDA+ provides harmonized data on global land use and land cover changes over a 150-year period, combining various data sources.
Applications: Used to assess long-term trends in land use change, such as deforestation, cropland expansion, and urbanization.
Data Access: HILDA+ Database.
Global Forest Watch:
Description: An interactive online platform that provides satellite-based data on global forest cover, loss, and gain.
Applications: Useful for tracking deforestation and reforestation, and analyzing their impact on albedo and carbon sequestration.
Data Access: Global Forest Watch.
HYDE (History Database of the Global Environment):
Description: Provides long-term data on historical land use (croplands, pastures, urban areas) and human population density.
Applications: Useful for understanding the impact of human land use activities on climate over centuries.
Data Access: HYDE Database.
Albedo Data and Products:
Surface Albedo Data from Satellites:
MODIS Albedo Product (MCD43):
Provides global surface albedo at 1 km resolution, updated every 8 days. Available from 2000 to the present.
Data Access: NASA MODIS Albedo Data.
CERES (Clouds and the Earth’s Radiant Energy System):
Provides surface albedo and radiation budget data by measuring reflected sunlight and Earth-emitted radiation.
Applications: Used to understand how changes in land cover affect the Earth’s energy balance.
Data Access: CERES Data.
MISR (Multi-angle Imaging SpectroRadiometer):
Measures surface albedo at multiple angles, providing detailed information about surface reflectance properties.
Applications: Useful for distinguishing between different types of land cover and their respective albedo values.
Data Access: MISR Data.
Regional and National Land Use Databases:
Many countries maintain their own databases for land use and land cover, which may provide more detailed and accurate data at national or regional levels.
Examples:
United States: National Land Cover Database (NLCD) provides detailed data on land cover changes across the U.S.
Europe: CORINE Land Cover (CLC) dataset by the European Environment Agency offers detailed land cover information across Europe.
Brazil: PRODES and DETER datasets provide data on deforestation in the Brazilian Amazon.
Climate Model Data for Land Use Impact Studies:
CMIP6 (Coupled Model Intercomparison Project Phase 6):
Includes models that incorporate land use change scenarios, greenhouse gas forcings, and albedo feedbacks. Data from these models can be used to analyze the impact of land use changes on the climate system.
Data Access: CMIP6 Data on Earth System Grid Federation (ESGF).
How to Use These Data Sources:
How to Use These Data Sources:
Integration with Climate Models:
Combine data on historical land use changes and surface albedo alterations with climate models (like those from CMIP6) to estimate their impacts on radiative forcing and global temperature changes.
Statistical Analysis and Remote Sensing Techniques:
Use statistical techniques to analyze trends and patterns in land use changes. Utilize remote sensing algorithms to derive albedo values from satellite data, assessing changes over time.
Attribution Studies:
Conduct attribution studies to separate the effects of GHGs from those of land use and albedo changes. Use models to simulate different scenarios with only GHGs or only land use changes to understand their relative contributions to warming.
Conclusion:
Conclusion:
To advance our understanding of how much lessened albedo from land use changes contributes to global warming, we need to better integrate these diverse datasets into climate models. This can provide a clearer picture of the complex interactions between land surface changes and the global climate system.
Why Use Proxies Instead of Direct Temperature Data?
Why Use Proxies Instead of Direct Temperature Data?
Indirect Effects on Temperature:
Land use changes and alterations in albedo (surface reflectivity) don't directly measure temperature; rather, they describe the factors that influence how much solar energy is absorbed or reflected by the Earth's surface. These changes affect the Earth's energy balance, which in turn influences global temperatures.
For example, deforestation reduces albedo (making the surface darker and less reflective), causing more solar energy to be absorbed, which can increase localized surface temperatures. But the exact amount of warming resulting from this albedo change depends on several other factors, like local climate, atmospheric circulation, and interactions with other components of the Earth system (such as cloud formation or snow cover).
Understanding Radiative Forcing:
"Radiative forcing" is the term used to describe changes in the balance between incoming and outgoing energy in the Earth’s atmosphere. Proxies like albedo data, greenhouse gas concentrations, and land use data are used to estimate radiative forcing because they tell us how much additional energy is retained or released by the Earth system due to human activities.
These proxies are vital because they help us understand the processes driving temperature changes over time. While direct temperature measurements are critical, they don't tell us the causes of warming without the context provided by these proxies.
Direct Temperature Measurements:
While we do have global temperature records from weather stations, satellites, and ocean buoys, these measurements only show the result of all combined effects on the climate system. They don’t directly tell us how much of the observed warming is due to specific causes, like greenhouse gases versus albedo changes. This is where the need for proxies comes in: to attribute changes in temperature to specific drivers.
How Proxy Data Helps Understand Global Warming:
How Proxy Data Helps Understand Global Warming:
Even though proxy data doesn't measure temperature directly, it is crucial in understanding how various factors contribute to warming. Here's how proxy data like land use changes and albedo modifications provide insights into warming:
Quantifying the Contribution of Land Use Changes:
Proxy data such as land cover changes and albedo variations help estimate the "radiative forcing" attributable to human activities. For example, by measuring how much less sunlight is reflected by urban areas compared to forests, scientists can calculate the additional heat absorbed and estimate its contribution to local and global warming.
Understanding Regional Impacts:
Temperature changes aren't uniform across the globe; they vary significantly based on local factors like land use, vegetation cover, and surface properties. Proxies allow for a detailed understanding of how different regions are affected by specific changes, such as how urban heat islands form or how deforestation in the Amazon influences regional and global temperatures.
Attribution Studies:
To determine how much of the warming is due to greenhouse gases versus changes in albedo, scientists use climate models that incorporate both direct temperature measurements and proxy data. They can run scenarios with different levels of greenhouse gases or various land use patterns to see how each contributes to observed temperature changes.
Why We Still Need Proxy Data for Temperature-Related Studies:
Why We Still Need Proxy Data for Temperature-Related Studies:
While proxies may seem indirect, they are essential for answering key questions about global warming. Here are some reasons why:
Determining Causes and Proportions:
Direct temperature measurements alone can't tell us what portion of the warming is due to greenhouse gases versus land use changes. We need data on the drivers of climate change—like greenhouse gas concentrations, land cover types, and albedo— to attribute the causes correctly.
Incorporating Feedback Mechanisms:
Climate feedbacks, like the melting of ice (which lowers albedo and further warms the planet), are complex processes that require proxy data to understand. The feedback loops between albedo, surface temperature, and greenhouse gas levels are critical to accurately modeling future climate scenarios.
Temporal and Spatial Coverage:
Direct temperature measurements are limited in their spatial and temporal coverage. Proxies like satellite data provide a broader and more detailed picture of changes in the Earth's surface, enabling us to understand how these changes contribute to overall warming across different regions and time periods.
Bridging Proxies and Temperature Data: Integrating Both for understanding global warming
Bridging Proxies and Temperature Data: Integrating Both for understanding global warming
To effectively use proxies in understanding global warming, researchers often integrate direct temperature data with proxy data to create a comprehensive picture of climate change. Here’s how this is done:
Combining Datasets:
Observational Data: Use historical temperature data from weather stations, ocean buoys, and satellites to establish baseline warming trends.
Proxy Data: Integrate data on albedo changes, greenhouse gas concentrations, and land use alterations to quantify radiative forcing from each source.
Climate Modeling:
Climate models (such as those used in CMIP6) are fed both direct temperature data and proxy data to simulate various scenarios. By isolating different factors in these models, scientists can estimate the contribution of each to the observed warming.
Validating Models Against Observations:
Compare model outputs with observed temperature data to ensure that the models accurately capture the observed warming trends. This process helps refine the models and improve their predictive capabilities.
Attribution Analysis:
Use advanced statistical methods to perform "attribution studies," which quantify how much of the observed warming is due to specific causes (like GHGs or albedo changes).
Direct temperature data shows us that the planet is warming, but proxy data helps explain why it's happening, which is crucial for forming effective mitigation and adaptation strategies.
The Need for More Land-Based Temperature Measurements
The Need for More Land-Based Temperature Measurements
Most global temperature datasets primarily rely on air temperature measurements rather than ground-based or land surface temperatures. There are several reasons why increasing land-based temperature measurements could provide valuable insights into global warming:
Local Effects of Land Use Changes:
Changes in land use, such as urbanization, deforestation, and agricultural expansion, can create localized "hot spots" that are not fully captured by air temperature measurements. Ground-based measurements are essential to capture the fine-scale variability of these changes.
For instance, urban heat islands (UHIs) can raise local temperatures significantly compared to surrounding rural areas. Without enough land-based measurements, the full impact of UHIs or similar localized phenomena on global warming estimates may be underestimated.
Understanding Regional Climate Impacts:
Different regions of the world have unique land surface characteristics that can significantly affect local climates. Ground-based temperature data can help quantify how these characteristics (e.g., soil type, vegetation cover) contribute to regional warming or cooling effects.
More granular temperature data could help to identify specific areas where changes in land use have the most significant impact on global temperatures. For example, measuring the warming effects of deforestation in the Amazon versus changes in arable land in temperate regions would require robust, widespread land-based measurements.
Validating and Improving Climate Models:
More comprehensive ground-based data would help improve the accuracy of climate models, which rely on temperature data to calibrate their predictions. With more direct measurements, models can be better validated and refined to reflect real-world conditions.
2. Challenges and Opportunities in Expanding Ground-Based Measurements
2. Challenges and Opportunities in Expanding Ground-Based Measurements
Infrastructure and Coverage:
Setting up a dense network of ground-based temperature sensors requires significant infrastructure and funding, particularly in remote or under-resourced regions. However, modern sensor technology is becoming more affordable, which could help expand these networks.
Citizen Science and Community Involvement:
Encouraging community-based monitoring programs could help expand coverage. Citizen science initiatives where people install low-cost temperature sensors in their communities could provide valuable data to supplement official measurements.
Leveraging Existing Networks:
Utilizing and expanding existing agricultural, hydrological, and meteorological stations could also enhance ground-based temperature data coverage. Many of these stations already collect some form of surface or soil temperature data.
Mapping and Reforesting the Sahara
Mapping and Reforesting the Sahara
The potential role of the Sahara in reducing global warming by reforesting or revegetating is both fascinating, but an opportunity to see what is feasible. This concept ties into "geoengineering" and "natural climate solutions," which explore large-scale interventions to mitigate global warming.
Benefits of Reforesting the Sahara:
Increased Carbon Sequestration:
Trees absorb carbon dioxide from the atmosphere, so large-scale reforestation could act as a significant carbon sink. The Sahara, being vast, presents a substantial area where this could occur.
Albedo Change and Cooling Effects:
Currently, the Sahara has a high albedo because of its light-colored sand, reflecting a significant amount of solar radiation back into space. Planting trees would reduce the albedo, causing the region to absorb more heat in the short term, but this might be offset by increased transpiration from the vegetation, which could have a cooling effect through increased cloud formation and moisture recycling.
Regional Climate Impacts:
Reforestation could change local weather patterns, potentially increasing rainfall in arid areas. More vegetation could also reduce dust storms, impacting global climate by reducing the amount of dust particles that enter the atmosphere and influence cloud formation.
Challenges of Reforesting the Sahara:
Water Scarcity:
The Sahara is one of the driest places on Earth. Reforesting it would require significant amounts of water, which is currently scarce. This could mean needing to desalinate seawater or finding other innovative water solutions, which could be energy-intensive and costly.
Soil Quality:
The soils in the Sahara are not naturally conducive to tree growth. Extensive soil restoration efforts would be needed to support large-scale reforestation.
Impact on Albedo:
There is a delicate balance in terms of albedo changes. While forests sequester carbon, their lower albedo compared to deserts could initially cause some localized warming. The net effect would depend on the extent of reforestation, types of vegetation used, and regional climate feedbacks.
4. Integrating Land-Based Measurements and Mapping Projects:
4. Integrating Land-Based Measurements and Mapping Projects:
To advance these ideas, a comprehensive approach would be needed:
Satellite-Ground Data Integration:
Combine satellite data with expanded ground-based networks to provide a more comprehensive view of surface temperatures and land use impacts. Satellites can cover vast areas like the Sahara to provide an overview, while ground-based sensors provide localized detail.
Pilot Projects and Feasibility Studies:
Conduct small-scale pilot projects to explore the feasibility and potential climate impacts of reforesting areas of the Sahara. These pilots could help understand the challenges of soil restoration, water needs, and local climate effects.
Advanced Climate Modeling:
Use advanced models to simulate various reforestation scenarios in the Sahara, considering different tree species, planting densities, irrigation needs, and potential climate feedbacks.
International Collaboration:
A project of this scale would require international cooperation, significant funding, and coordination between countries, especially those in North Africa and the Sahel region.
Sahara to Savanna
Sahara to Savanna
Converting the Sahara into grasslands or savanna with roaming herbivores is a concept with both potential benefits and significant challenges. Understanding the albedo changes, the specific heat properties of surfaces, and the broader climatic impacts of such an endeavour would require a combination of direct measurements, satellite monitoring, and advanced climate modelling.
1. Albedo of Desert Sand vs. Grassland/Savanna
1. Albedo of Desert Sand vs. Grassland/Savanna
Albedo of Desert Sand:
High Reflectivity but Specific Absorption Characteristics:
Desert sand generally has a high albedo, meaning it reflects a significant portion of incoming solar radiation—typically between 0.3 to 0.4 (or 30% to 40%). This is higher than many natural surfaces like forests or grasslands.
However, the albedo of sand can vary depending on factors like color, grain size, and moisture content. In general, dry, light-colored sands reflect more sunlight, contributing to their higher albedo.
Despite its relatively high albedo, desert sand can still absorb and retain a significant amount of heat due to its material properties. The sandy surface, especially in arid climates, tends to have low moisture content, which means it has a lower specific heat capacity compared to water or moist soil. This means sand can heat up quickly during the day and cool down rapidly at night.
Albedo of Grassland/Savanna:
Moderate Reflectivity:
Grasslands and savannas generally have a lower albedo than deserts, typically ranging from 0.15 to 0.25 (15% to 25%). This means grasslands and savannas absorb more sunlight compared to desert sand.
The albedo of these landscapes can vary seasonally or with the density and type of vegetation. For example, dense green grass reflects less sunlight (has a lower albedo) than dry or sparse grass.
2. Why Does Desert Sand Absorb a Lot of Heat Despite Its High Albedo?
2. Why Does Desert Sand Absorb a Lot of Heat Despite Its High Albedo?
It's true that desert sand has a relatively high albedo compared to darker surfaces, so it reflects a good portion of incoming solar radiation. However, several factors contribute to why deserts still absorb a lot of heat:
Substance Properties (Thermal Conductivity and Heat Capacity):
Sand has low thermal conductivity and a low heat capacity, meaning it doesn’t transfer heat well to its surroundings and can change temperature quickly. During the day, sand heats up very quickly because it doesn't conduct heat away from its surface efficiently. This creates very hot surface temperatures, even if some sunlight is reflected.
Conversely, because sand loses heat rapidly at night, deserts tend to have large diurnal temperature ranges (hot days and cold nights).
Radiative Emission:
Even though desert sand reflects a lot of visible sunlight, it also emits longwave infrared radiation. This heat radiation can still contribute to warming the lower atmosphere, especially since there’s little vegetation or moisture to absorb and moderate the heat.
Absence of Moisture:
Moisture in soils or on surfaces plays a significant role in absorbing and storing heat. In deserts, the lack of moisture means that less solar energy is used for processes like evaporation, and more is available to directly heat the sand.
3. Potential Climate Impacts of Converting the Sahara to Grassland/Savanna with Herbivores
3. Potential Climate Impacts of Converting the Sahara to Grassland/Savanna with Herbivores
If we were to convert parts of the Sahara to grasslands or savanna, there would be several key impacts related to albedo, carbon sequestration, and regional climate:
Albedo Changes:
Converting desert to grassland or savanna would lower the albedo because vegetation generally reflects less sunlight than sand. This means that, in the short term, more solar radiation would be absorbed, potentially leading to localized warming.
However, the introduction of vegetation could also change the energy balance in other ways, such as through evapotranspiration (the process by which plants release water vapor into the air). This can have a cooling effect, especially in regions with sufficient moisture.
Carbon Sequestration:
Grasslands and savannas can sequester carbon in both plant biomass and soil organic matter. Even though trees in forests sequester more carbon overall, grasslands can be effective carbon sinks, especially if combined with practices like managed grazing by herbivores, which can enhance soil health and carbon storage.
Introducing herbivores to roam these grasslands could mimic natural processes seen in ecosystems like the African savanna, where grazing animals help maintain grasslands and even promote carbon sequestration by trampling organic material into the soil.
Local and Regional Climate Changes:
Establishing grasslands or savanna could potentially increase local rainfall by altering the local water cycle. Plants release water vapor through transpiration, which can contribute to cloud formation and potentially increase local precipitation, creating a positive feedback loop that supports further vegetation growth.
The introduction of vegetation could also help stabilize local temperatures by reducing the diurnal temperature range (less extreme temperatures between day and night).
Dust Suppression:
Vegetation would help anchor the soil and reduce the amount of dust released into the atmosphere. Dust from deserts like the Sahara can travel long distances, affecting air quality and cloud formation in other parts of the world. Reducing this dust could have significant regional and even global climate effects.
4. Feasibility and Challenges of Creating Grasslands/Savanna in the Sahara
4. Feasibility and Challenges of Creating Grasslands/Savanna in the Sahara
While the concept is appealing, there are several challenges to consider:
Water Availability:
Grasslands and savannas require a certain amount of water to sustain themselves, especially during dry seasons. The Sahara, being extremely arid, would require substantial water resources to establish and maintain any form of vegetation. This could mean needing to develop large-scale irrigation systems or employ innovative methods like using fog nets, underground water sources, or desalinated seawater.
Soil Fertility and Ecosystem Suitability:
The Sahara’s soil is often low in nutrients and organic matter, which would limit the growth of grasses and other vegetation without substantial soil amendment efforts. Adding organic matter, nutrients, and perhaps even biochar could be necessary to make the soil fertile enough to support grasslands.
The introduction of herbivores would also require careful management to prevent overgrazing, which could quickly degrade the new ecosystem.
Ecological Balance:
Introducing new vegetation and animals could disrupt existing desert ecosystems, which are home to a range of specialized species adapted to extreme conditions. Any conversion efforts would need to carefully consider the ecological impacts on native flora and fauna.
5. The Big Picture: Potential Global Implications
5. The Big Picture: Potential Global Implications
Mitigating Global Warming:
If successful, converting parts of the Sahara into grasslands or savanna could help mitigate global warming by sequestering carbon, changing local albedo, and potentially increasing regional precipitation.
However, any warming effect due to reduced albedo would need to be balanced by the cooling effects of carbon sequestration and increased evapotranspiration. Careful modeling would be needed to assess the net impact on global temperatures.
Potential as a "Natural Climate Solution":
This idea fits within the broader category of "natural climate solutions," which involve using ecosystem-based approaches to mitigate climate change. It would require extensive research, international cooperation, and significant resources but could offer a novel way to both address climate change and provide other co-benefits, like combating desertification and promoting biodiversity.
The idea of converting the Sahara (See Desertification for more.) into grasslands or savanna with roaming herbivores could have monumental impact - not just for the soil, but the people there. Let's explore how this scenario could affect albedo, heat absorption, and broader climate impacts. roaming herbivores is a fascinating concept with both potential benefits and significant challenges. Understanding the albedo changes, the specific heat properties of surfaces, and the broader climatic impacts of such an endeavor would require a combination of direct measurements, satellite monitoring, and advanced climate modelling.
1. Albedo of Desert Sand vs. Grassland/Savanna
1. Albedo of Desert Sand vs. Grassland/Savanna
Albedo of Desert Sand:
High Reflectivity but Specific Absorption Characteristics:
Desert sand generally has a high albedo, meaning it reflects a significant portion of incoming solar radiation—typically between 0.3 to 0.4 (or 30% to 40%). This is higher than many natural surfaces like forests or grasslands.
However, the albedo of sand can vary depending on factors like color, grain size, and moisture content. In general, dry, light-colored sands reflect more sunlight, contributing to their higher albedo.
Despite its relatively high albedo, desert sand can still absorb and retain a significant amount of heat due to its material properties. The sandy surface, especially in arid climates, tends to have low moisture content, which means it has a lower specific heat capacity compared to water or moist soil. This means sand can heat up quickly during the day and cool down rapidly at night.
Albedo of Grassland/Savanna:
Moderate Reflectivity:
Grasslands and savannas generally have a lower albedo than deserts, typically ranging from 0.15 to 0.25 (15% to 25%). This means grasslands and savannas absorb more sunlight compared to desert sand.
The albedo of these landscapes can vary seasonally or with the density and type of vegetation. For example, dense green grass reflects less sunlight (has a lower albedo) than dry or sparse grass.
2. Why Does Desert Sand Absorb a Lot of Heat Despite Its High Albedo?
2. Why Does Desert Sand Absorb a Lot of Heat Despite Its High Albedo?
It's true that desert sand has a relatively high albedo compared to darker surfaces, so it reflects a good portion of incoming solar radiation. However, several factors contribute to why deserts still absorb a lot of heat:
Substance Properties (Thermal Conductivity and Heat Capacity):
Sand has low thermal conductivity and a low heat capacity, meaning it doesn’t transfer heat well to its surroundings and can change temperature quickly. During the day, sand heats up very quickly because it doesn't conduct heat away from its surface efficiently. This creates very hot surface temperatures, even if some sunlight is reflected.
Conversely, because sand loses heat rapidly at night, deserts tend to have large diurnal temperature ranges (hot days and cold nights).
Radiative Emission:
Even though desert sand reflects a lot of visible sunlight, it also emits longwave infrared radiation. This heat radiation can still contribute to warming the lower atmosphere, especially since there’s little vegetation or moisture to absorb and moderate the heat.
Absence of Moisture:
Moisture in soils or on surfaces plays a significant role in absorbing and storing heat. In deserts, the lack of moisture means that less solar energy is used for processes like evaporation, and more is available to directly heat the sand.
3. Potential Climate Impacts of Converting the Sahara to Grassland/Savanna with Herbivores
3. Potential Climate Impacts of Converting the Sahara to Grassland/Savanna with Herbivores
If we were to convert parts of the Sahara to grasslands or savanna, there would be several key impacts related to albedo, carbon sequestration, and regional climate:
Albedo Changes:
Converting desert to grassland or savanna would lower the albedo because vegetation generally reflects less sunlight than sand. This means that, in the short term, more solar radiation would be absorbed, potentially leading to localized warming.
However, the introduction of vegetation could also change the energy balance in other ways, such as through evapotranspiration (the process by which plants release water vapor into the air). This can have a cooling effect, especially in regions with sufficient moisture.
Carbon Sequestration:
Grasslands and savannas can sequester carbon in both plant biomass and soil organic matter. Even though trees in forests sequester more carbon overall, grasslands can be effective carbon sinks, especially if combined with practices like managed grazing by herbivores, which can enhance soil health and carbon storage.
Introducing herbivores to roam these grasslands could mimic natural processes seen in ecosystems like the African savanna, where grazing animals help maintain grasslands and even promote carbon sequestration by trampling organic material into the soil.
Local and Regional Climate Changes:
Establishing grasslands or savanna could potentially increase local rainfall by altering the local water cycle. Plants release water vapor through transpiration, which can contribute to cloud formation and potentially increase local precipitation, creating a positive feedback loop that supports further vegetation growth.
The introduction of vegetation could also help stabilize local temperatures by reducing the diurnal temperature range (less extreme temperatures between day and night).
Dust Suppression:
Vegetation would help anchor the soil and reduce the amount of dust released into the atmosphere. Dust from deserts like the Sahara can travel long distances, affecting air quality and cloud formation in other parts of the world. Reducing this dust could have significant regional and even global climate effects.
4. Feasibility and Challenges of Creating Grasslands/Savanna in the Sahara
4. Feasibility and Challenges of Creating Grasslands/Savanna in the Sahara
While the concept is appealing, there are several challenges to consider:
Water Availability:
Grasslands and savannas require a certain amount of water to sustain themselves, especially during dry seasons. The Sahara, being extremely arid, would require substantial water resources to establish and maintain any form of vegetation. This could mean needing to develop large-scale irrigation systems or employ innovative methods like using fog nets, underground water sources, or desalinated seawater.
Soil Fertility and Ecosystem Suitability:
The Sahara’s soil is often low in nutrients and organic matter, which would limit the growth of grasses and other vegetation without substantial soil amendment efforts. Adding organic matter, nutrients, and perhaps even biochar could be necessary to make the soil fertile enough to support grasslands.
The introduction of herbivores would also require careful management to prevent overgrazing, which could quickly degrade the new ecosystem.
Ecological Balance:
Introducing new vegetation and animals could disrupt existing desert ecosystems, which are home to a range of specialized species adapted to extreme conditions. Any conversion efforts would need to carefully consider the ecological impacts on native flora and fauna.
5. The Big Picture: Potential Global Implications
5. The Big Picture: Potential Global Implications
Mitigating Global Warming:
If successful, converting parts of the Sahara into grasslands or savanna could help mitigate global warming by sequestering carbon, changing local albedo, and potentially increasing regional precipitation.
However, any warming effect due to reduced albedo would need to be balanced by the cooling effects of carbon sequestration and increased evapotranspiration. Careful modeling would be needed to assess the net impact on global temperatures.
Potential as a "Natural Climate Solution":
This idea fits within the broader category of "natural climate solutions," which involve using ecosystem-based approaches to mitigate climate change. It would require extensive research, international cooperation, and significant resources but could offer a novel way to both address climate change and provide other co-benefits, like combating desertification and promoting biodiversity.
Expanding a network of surface measurements would allow us to pinpoint which areas contribute most to warming and help improve climate models and ways to reduce global warming. The idea of reforesting or "greening" the Sahara is challenging (link) but has the potential to offer substantial global benefits and show others of what is achievable .
Check out how soil surfaces interact with Water Temperature
Page updated
Google Sites
Report abuse