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Posts from the ‘Micrometeorology’ Category

Top Five Blog Posts in 2016

In case you missed them the first time around, here are the most popular Environmental blog posts in 2016.

Lysimeters Determine if Human Waste Composting can be More Efficient

Top five blog posts Environmental biophysics

In Haiti, untreated human waste contaminating urban areas and water sources has led to widespread waterborne illness.  Sustainable Organic Integrated Livelihoods (SOIL) has been working to turn human waste into a resource for nutrient management by turning solid waste into compost.  Read more

Estimating Relative Humidity in Soil: How to Stop Doing it Wrong

Top five blog posts Environmental biophysics

Estimating the relative humidity in soil?  Most people do it wrong…every time.  Dr. Gaylon S. Campbell shares a lesson on how to correctly estimate soil relative humidity from his new book, Soil Physics with Python, which he recently co-authored with Dr. Marco Bittelli.  Read more.

How Many Soil Moisture Sensors Do You Need?

Top five blog posts Environmental biophysics

“How many soil moisture sensors do I need?” is a question that we get from time to time. Fortunately, this is a topic that has received substantial attention by the research community over the past several years. So, we decided to consult the recent literature for insights. Here is what we learned.

Data loggers: To Bury, or Not To Bury

Top five blog posts Environmental biophysics

Globally, the number one reason for data loggers to fail is flooding. Yet, scientists continue to try to find ways to bury their data loggers to avoid constantly removing them for cultivation, spraying, and harvest.  Chris Chambers, head of Sales and Support at Decagon Devices always advises against it. Read more

Founders of Environmental Biophysics:  Champ Tanner

Top five blog posts Environmental biophysics


We interviewed Gaylon Campbell, Ph.D. about his association with one of the founders of environmental biophysics, Champ Tanner.  Read more

And our three most popular blogs of all time:

Do the Standards for Field Capacity and Permanent Wilting Point Need to Be Reexamined?

Top five blog posts Environmental biophysics

We asked scientist, Dr. Gaylon S. Campbell, which scientific idea he thinks impedes progress.  Here’s what he had to say about the standards for field capacity and permanent wilting point.  Read more

Environmental Biophysics Lectures

Top five blog posts Environmental biophysics

During a recent semester at Washington State University, a film crew recorded all of the lectures given in the Environmental Biophysics course. The videos from each Environmental Biophysics lecture are posted here for your viewing and educational pleasure.  Read more

Soil Moisture Sensors In a Tree?

Top five blog posts Environmental biophysics

Soil moisture sensors belong in the soil. Unless, of course, you are feeling creative, curious, or bored. Then maybe the crazy idea strikes you that if soil moisture sensors measure water content in the soil, why couldn’t they be used to measure water content in a tree?  Read more

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Soil Moisture: An Important Parameter in Weather Monitoring

CoCoRaHS and Weather Monitoring

Each time a rain, hail, or snow storm crosses over your area, volunteers are taking precipitation measurements that are then used to analyze situations ranging from water resource availability to severe storm warnings.  


CoCoRaHS precipitation data is used by many high profile organizations.

CoCoRaHS (Community Collaborative Rain, Hail and Snow Network) is a non-profit community-based network of volunteers of all ages and backgrounds working together to measure and map precipitation (rain, hail, and snow).  Their data is used by the National Weather Service, meteorologists, hydrologists, emergency managers, city utilities, USDA, engineers, farmers, and more.  The organization will soon add another layer to their weather-monitoring efforts:  soil moisture measurement.


In 1997, a localized flooding event in Fort Collins, Colorado was not well-warned due to lack of high-density precipitation observation.

Why Soil Moisture?

CoCoRaHS originated as the brain child of Nolan Doesken, the state climatologist of Colorado,  in 1997 in response to a localized flooding event in Fort Collins, CO that was not well-warned due to lack of high-density precipitation observations.  Ten years ago the Colorado Climate Center began a partnership with the National Integrated Drought Information System to establish the first regional drought early warning system. This particular system would serve the Upper Colorado River Basin and eastern Colorado.

From the beginning, Nolan was thinking about soil moisture.  He says, “When we first started this project, we identified one weakness of the current climate monitoring systems as the inability to quantitatively assess soil moisture.  Soil moisture is critical as it affects both short-term weather forecasts and long-term seasonal forecasts, which are important for drought early warning and avoiding the agricultural consequences of too much or too little soil moisture.”It wasn’t until years later in the drought of 2012, which developed rapidly in the mid and late spring across the intermountain west and central plains that Nolan began planning to use CoCoRaHS as a vehicle for improving the soil moisture aspect of drought early warning.


The organization intends to measure soil moisture using the gravimetric method.

How Will Volunteers Measure Soil Moisture?

Historically, CoCoRaHS has had success using low-cost measurement tools, stressing training and education, and using an interactive website to provide the highest quality data, and soil moisture will be no different.  The organization intends to measure soil moisture using the gravimetric method, where the user will take samples using a soil ring, dry samples in their own oven, and measure sample weight with an electronic scale. Peter Goble, a research assistant at Colorado State, has developed the measurement protocols that volunteers will follow.  He says, “We have installed several different types of soil sensors and tried gravimetric techniques in a field next to the center, and our experience has helped us set up a protocol that gets observers as educated as they can be by the time they take their measurements. The coring device we use is something that came about through trial and error. We were trying to reconcile the fact that we really wanted deeper root zone measurements in order to satisfy drought early-warning-system users, and the need for an inexpensive set of standardized materials that we could send out to observers in a kit.”  Volunteers will take soil samples at each point in a grid pattern, both at the surface and at the 7-9 inch level near the root zone.

What will Happen to the Data?

Initially, while the program is in its test phase, the data will be put in a spreadsheet and shared. However, once CoCoRaHS has finished sending this protocol around the nation to a group of alpha testers, they’ll set up a website infrastructure enabling volunteers to enter their VWC data directly into the CoCoRaHS website.

The need for soil moisture measurement in weather monitoring will outweigh the volunteers’ ability to measure, but there is a solution.

The need for soil moisture measurement in weather monitoring will outweigh the volunteers’ ability to measure, but there is a solution.

Why the Gravimetric Method?

Nolan says the challenge of water content is that soil is highly variable across space.  And if you add issues like sensor performance, improper installation of sensors, problems with soil contact, changes in bulk density, and soil compaction, you end up with inconsistent data.  The gravimetric method will avoid inconsistencies in spatial measurements and ensure higher quality data.

An Overwhelming Task

Nolan says the need for soil moisture measurement in weather monitoring will outweigh the volunteers’ ability to measure, but there is a solution. “People who use soil moisture data in atmospheric applications need high resolution, gridded information in every square kilometer across the country, but it will happen through modeling.  The measurements we take of precipitation and soil moisture will help in the refinement of the weather modules the atmospheric scientists will use as input to their weather prediction models.”

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Unraveling the Effects of Dams in Costa Rica

Thirty years ago, in Costa Rica’s Palo Verde National Park, the wetlands flooded regularly and eco-tourists could view thousands of waterfowl. Today, invasive cattail plants cover portions of the wetland which has subsequently dried up and become colonized by hardwoods. Consequently, the number of birds has fallen dramatically.


The number of birds on Palo Verde National Park has fallen dramatically. (Image:

Some people blame the dams built in the 1970s which introduced hydrological power and created a large irrigation district in the remote region. Dr. Rafael Muñoz-Carpena, Professor and University of Florida Water Institute Faculty Fellow and his research team are performing environmental studies on the wetlands, trying to unravel the effects of the dams and how to revert some of the damage. Rafael explains, “We have a situation where modern engineering brought about social improvements, helpful renewable resources, and irrigation for abundant food production. But the resulting environmental degradation threatens a natural region in a country that depends on eco-tourism.”


“A vast network of mangrove-rich swamp, lagoons, marshes, grassland, limestone outcrops, and forests comprise the 32,266 acre Palo Verde National Park.” (Image and text:

Are The Dams Responsible?

Dr. Muñoz-Carpena says because of lack of historical data it’s difficult to untangle and separate all the factors that have caused the environmental degradation. He adds, “Thirty years ago Palo Verde National Park was part of a large wetland system which was important to all of Central America because it contained many endangered species and was a wintering ground for migratory birds from North America. The Palo Verde field station on the edge of the wetland, operated by the Organization of Tropical Studies (OTS), attracted birdwatchers and wetland scientists from all over the world.”

In the 1970’s, with international funding, a dam was built in the mountains to collect water from the humid side of Costa Rica in order to generate hydroelectric power. It was clean, abundant, and strategically important.  With the water transferred to the dry side of the country, a large irrigation district was created to not only produce important crops to the region like rice and beans, but to distribute the land among small parcel settlers.


“Birding is the principal draw of visitors to the park.” (Image and text:

Over the years, however, the wetland area slowly degraded to the point where its Ramsar Convention wetland classification is under question. Rafael says that understanding the causes of the degradation, the impacts of the human system, and how the natural and human systems are linked, is the big question of his research, and there are many factors to consider. “The release of the water, ground and surface water (over)use, agriculture, human development, and a larger population are all factors that could contribute to this degradation. Everything compounds in the downstream coastal wetlands. In collaboration with OTS and other partner organizations and universities, we are trying to disentangle these different drivers.”


Understanding the causes of the degradation, the impacts of the human system, and how the natural and human systems are linked, is the big question of this research. (Image:

A Lack of Historical Data

One of the challenges the researchers face is to gather a sufficient amount of temporal and spatial information about what happened in the past forty years.  There are no public repositories of data to tap, and the information is spotty and hard to access. Rafael says, “Thanks to the collaboration of many local partners, we have been able to gather enough information to stitch together a large database out of a collection of non-systematic studies. The biggest challenge is to harmonize data that has been collected by different people in non-consistent ways.” This large database now contains the best long-term record possible for key hydrologic variables: river flow, groundwater stage, precipitation, and evapotranspiration.

The team is also using remote sensing sources to try to obtain time-series data for land-use and vegetation change, and will have those data ground-truthed through instruments that are collecting similar time-series data. Rafael says, “The idea is to build a network that will allow us to overlap some of the previous data sources with our own, validate and upscale the ground data with remote sensing sources, enabling us to put together a detailed picture of what happened.”

Next Week:  Find out how the researchers established connectivity in such a remote area,  some of the problems associated with the research, and how the team has addressed those issues.

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Can Canopy Measurements Determine Soil Moisture? (Part 2)

Dr. Y. Osroosh, now a researcher at Washington State University, believes that plants are the best soil moisture sensors (see part 1).  He and his team have developed a new model for interpreting plant canopy signals to indirectly determine soil moisture in a Fuji apple orchard.  Below are the results of their efforts and what he sees as the future of this research.


Could plants be the best indicators of soil moisture?

The Results

Osroosh says they expected to see correlations, but such strong relationships were unexpected. The team found that soil water deficit was highly correlated with thermal-based water stress indices in drip-irrigated apple orchard in the mildly-stressed range. The relationships were time-sensitive, meaning that they were valid only at a specific time of day. The measurements taken between 10:00am and 11:00am (late morning, time of maximum transpiration) were highly correlated with soil water deficit, but the “coefficient of determination” decreased quickly and significantly beyond this time window (about half in just one hour, and reached zero in the afternoon hours).  Osroosh says this is a very important finding because researchers still think midday is the best time to measure canopy water stress index (CWSI). He adds, “The apple trees showed an interesting behavior which was nothing like what we are used to seeing in row crops. They regulate their stomata in a way that transpiration rate is intense late in the morning (maximum) and late in the afternoon. During the hot hours of afternoon, they close their stomata to minimize water loss.”


Researchers have found good relationships between CWSI and soil water content in the root zone near the end of the season at high soil water deficits in row crops.

Other Research

Osroosh points to other efforts which have tried to correlate remotely-sensed satellite-based thermal or NIR measurements to soil water content. He says, “The closest studies to ours have been able to find good relationships between CWSI and soil water content in the root zone near the end of the season at high soil water deficits in row crops. Paul Colaizzi, a research agricultural engineer did his PhD research in part on the relationship between canopy temperature, CWSI, and soil water status in Maricopa, Arizona; also motivated by Jackson et al. (1981). Steve Evett and his team at Bushland, Texas are continuing that research as they try to develop a relationship between CWSI and soil water status that will hold up. They are using a CWSI that is integrated over the daylight hours and have found good relationships between CWSI and soil water content in the root zone near the end of the season when plots irrigated at deficits begin to develop big deficits.”


Osroosh wants to study other apple cultivars, tree species, and perhaps even row crops, under other irrigation systems and climates.

What’s The Future?

In the future, Osroosh hopes to study the limitations of this approach and to find a better way to monitor a large volume of soil in the root zone in real-time (as reference). He says, “We would like to see how universal these equations can be. Right now, I suspect they are crop and soil-specific, but by how much we don’t know. We want to study other apple cultivars, tree species, and perhaps even row crops, under other irrigation systems and climates. We need to monitor crops for health, as well, to make sure what we are measuring is purely a water stress signal. One of our major goals is to develop a sensor-based setup which, after calibration, can be used for “precise non-contact sensing of soil water content” and “stem water potential” in real-time by measuring canopy temperature and micrometeorological parameters.”

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Can Canopy Measurements Determine Soil Moisture?

As a young university student, Dr. Y. Osroosh, now a researcher at Washington State University, wanted to design the most accurate soil moisture sensor.  Over the years, however, he began to realize the complexity and difficulty of the task.  Inspired by the work of Jackson et al. (1981) and researchers in Bushland, TX, he now believes that plants are the best soil moisture sensors.  He and his team developed a new model for interpreting plant canopy signals to indirectly determine soil moisture.

Apple tree canopy

The team measured microclimatic data in an apple orchard.

How Can Plants Indicate Water in Soil?

Osroosh and his team wanted to use plant stress instead of soil sensors to make irrigation decisions in a drip-irrigated Fuji apple tree orchard. But, the current practice of using the crop water stress index (CWSI) for detecting water stress presented some problems, Osroosh comments, “Currently, scientists use either an empirical CWSI or a theoretical one developed using equations from FAO-56, but the basis for FAO-56 equations is alfalfa or grass, which isn’t similar to apple trees.”  One of the main differences between grass and apple trees is that apple tree leaves are highly linked to atmospheric conditions. They control their stomata to avoid water loss.  

Apple tree canopy

There is high degree of coupling between apple leaves and the humidity of the surrounding air.

So Osroosh borrowed a leaf porometer to measure the stomatal conductance of apple trees, and he developed his own crop water stress index, based on what he found.  He explains,We developed a new theoretical crop water stress index specifically for apple trees. It accounts for stomatal regulations in apple trees using a canopy conductance sub-model. It also estimates average actual and potential transpiration rates for the canopy area which is viewed by a thermal infrared sensor (IRT).”

Fuji apple orchard (Roza Farm, Prosser, WA).

Fuji apple orchard (Roza Farm, Prosser, WA) where Osroosh performed his research.

What Data Was Used?

Osroosh says they established their new “Apple Tree” CWSI based on the energy budget of a single apple leaf, so “soil heat flux” was not a component in their modeling. He and his team measured soil water deficit using a neutron probe in the top 60 cm of the profile, and they collected canopy surface temperature data using thermal infrared sensors. The team also measured microclimatic data in the orchard.  

apple tree canopy

Neutron probes were problematic, as they did not allow collection of data in real time.

Osroosh comments, “The accuracy of this approach greatly depends on the accuracy of reference soil moisture measurement methods.  To establish a relationship between CWSI and soil water, we needed to measure soil water content in the root zone precisely. We used a neutron probe, which provides enough precision and volume of influence to meet our requirements.  However, it was a labor and time intensive method which did not allow for real-time measurements, posing a serious limitation.”

Next week: Learn the results of Dr. Osroosh’s experiments, the future of this research, and about other researchers who are trying to achieve similar goals.

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Improving Drought Tolerance in Soybean

Limited water availability is a significant issue threatening the agricultural productivity of soybean, reducing yields by as much as 40 percent. Due to climate change, varieties with improved drought tolerance are needed, but phenotyping drought tolerance in the field is challenging, mainly because field drought conditions are unpredictable both spatially and temporally.  This has led to the genetic mechanisms governing drought tolerance traits to be poorly understood. Researcher Clinton Steketee at the University of Georgia is trying to improve soybean drought tolerance by using improved screening techniques for drought tolerance traits, identifying new drought tolerant soybean germplasm, and clarifying which genomic regions are responsible for traits that help soybeans cope with water deficit.

drought tolerance

Researchers are trying to improve soybean drought tolerance by using better screening techniques for drought tolerance traits.

Which Traits Are Important?

Clinton and his colleagues are evaluating a genetically diverse panel of 211 soybean lines in two different states, Kansas and Georgia, for over two years to help him accomplish his research objectives. These 211 lines come from 30 countries and were selected from geographical areas with low annual precipitation and newly developed soybean lines with enhanced drought-related traits, along with drought susceptible checks. The researchers are looking at traits such as canopy wilting.  Some plants will take a few days longer to wilt, allowing these plants to continue their photosynthetic ability to produce biomass for seed production. Other traits that he is interested in evaluating are stomatal conductance, canopy temperature with thermal imaging, relative water content, and carbon isotope discrimination.

drought tolerance

The scientists want to monitor traits such as canopy wilting.

Use of Microclimate Stations to Monitor Environmental Conditions

Clinton says to make selection of drought-tolerant lines easier and more predictable, knowledge of field environmental conditions is critical. He says, “You can phenotype all you want, but you need the true phenotype of the plant to be observed under real drought conditions so you can discover the genes for drought tolerance and improve resistance down the line in a breeding program.”

In addition to soil moisture sensors, the team used microclimate weather stations to help monitor water inputs at their two field research sites and determine ideal time periods for phenotyping drought-related traits.  Steketee says, “We put microenvironment monitors in the field next to where we were growing our experimental materials.  Both locations use those monitors to keep an eye on weather conditions throughout the growing season, measuring temperature, humidity, and precipitation. Since we could access the data remotely, we used that information to help us determine when it was time to go out to the field and look at the plots. We wanted to see big differences between soybean plants if possible, especially in drought conditions. By monitoring the conditions we could just go back to our weather data to show we didn’t get rain for 3 weeks before we took this measurement, proving that we were actually experiencing drought conditions.”

drought tolerance

The team identified some lines that performed well.

Results So Far

Though 2015 wasn’t a great year for drought in Georgia, Clinton says there was a period in late July when he was able to measure canopy wilting, and they identified some lines that performed well.  He says, “We compared our data to the data collected by our collaborator in Kansas, and there are a few lines that did well in both locations.  Hopefully, another year of data will confirm that these plants have advantageous drought tolerance traits, and we’ll be able to probe the advantageous traits out of those lines and integrate them into our breeding program.”

Future Plans

The team will use what’s called a genome-wide association study approach to identify genomic regions responsible for drought tolerance traits of interest. This approach uses phenotypic information collected from the field experiments along with DNA markers throughout the soybean genome to see if that marker is associated with the trait they are interested in.  If the scientists find the spot in the genome that is associated with the desired trait, they will then develop genomic tools to be used for selection, integrate that trait into elite germplasm, and ultimately improve the drought tolerance of soybeans.

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Is Average Relative Humidity A Meaningless Measurement? (Part II)

Scientists often misunderstand average relative humidity (see part I).  In fact, it’s not uncommon to encounter average relative humidity being misused in scientific literature.  This week, learn which measurement should be used instead.

Average Relative Humidity

Humid conditions in a pine forest.

What is Wrong with Average Relative Humidity?

We often use average values to illustrate the behavior of parameters over time.  One of the most common is air temperature, where we effectively graph average half-hourly temperature across a day or daily temperature across a year to show important details about the environment. But, consider what average relative humidity would look like.  

As noted above, a general rule, though not consistent everywhere, is that the temperature at night cools down to the point where the air is saturated and the relative humidity is 100% (1).  During the day, depending on the climate and weather, the saturated vapor pressure may increase roughly two to five times ea and relative humidity would be between 0.2 to 0.5. If we calculated an average for the day, it would most likely be between 0.6 and 0.75, no matter what environment was being measured.  Of course, if it were raining or in the winter with low incoming radiation, this would be higher.  Still, it is easy to see that an average relative humidity does not do much to define meteorological conditions.  


The title of this chart is misleading because they were not averaging across the day, but only daily at noon. Image:

What Should We Use Instead?

The measurement that should be reported is vapor pressure. Not only is it independent of temperature, but it can also be effectively averaged over time to show ecosystem behavior.  However, this value will not be helpful to scientists who are identifying the pull generated by the atmosphere for water vapor in the plant or soil. This quantity is called vapor deficit and is calculated by taking the difference between the saturation vapor pressure and ea.

boy-drinking-from-bottle-738210_640 (1)

We sense water deficit in the atmosphere through our skin.

As humans, we intuitively sense the deficit when we feel that the atmosphere is dry through drying of our lips or our skin.  The same is true for plants. The dry atmosphere will exert a higher pull on the water, pulling it out through the leaves.  The higher the difference between the vapor pressure and the saturation vapor pressure, the more pull for water. Although sometimes reported in literature, the most common use for vapor pressure is as a standard input to evapotranspiration models like FAO56 or Penman-Monteith.

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Is Average Relative Humidity A Meaningless Measurement?

Relative humidity is one of the most widely reported weather parameters and is familiar to most people.

Relative Humidity

Scientists sometimes misunderstand relative humidity.

Still, it is not uncommon to encounter it being misused.  Here are two examples:  

  1. My sister recently stated that her son was experiencing 45℃ and 100% humidity while walking around during the day in the Philippines.
  2. In scientific literature, I often find figures displaying daily average relative humidity over a period of weeks or months.  

Both of these examples show a misunderstanding of what relative humidity is and how it can be used.

What is relative humidity?

Relative humidity (hr) is the ratio of the vapor pressure (ea) in the air over how much vapor pressure there could be if the air were saturated at that air temperature (saturated vapor pressure, es(Ta)).

Relative Humdity

While vapor pressure is a reasonably conservative quantity, meaning it doesn’t change drastically with time (i.e.hours), es(Ta) is solely tied to temperature, shown by the empirical Tetens equation:

Relative Humidity

where Ta is air temperature, and b =17.502 and c = 240.97℃ (constants).  As the equation shows, saturated vapor pressure is only a function of temperature, so relative humidity in natural conditions will simply show a sinusoidal pattern that is inverse to air temperature.  

Relative Humidity

When humidity is higher, the vapor concentration difference is smaller so we lose less water, reducing our ability to cool.

Why do we estimate it poorly?

When temperatures are elevated above our comfort zone, we begin to feel hot. Our bodies, which are adept at keeping us cool, evaporate water from our skin to return us to a comfortable skin temperature.  When humidity is higher, the vapor concentration difference is smaller so we lose less water, thus reducing our ability to cool.  In an attempt to balance the humidity, our body moistens the skin surface with sweat, leaving us feeling damp and sticky. This makes us feel like the air is nearly saturated, but in reality, the higher humidity has simply limited our ability to cool ourselves.

It is a relatively simple thing to convince ourselves that daytime humidities are never 100% unless it’s raining. We know that daytime temperatures are almost always higher than nighttime, due to solar radiation. And, we are familiar with dew that forms on surfaces as nighttime temperatures cool to the point that they begin to condense water out of the air (dew point temperature). If we assume that the vapor pressure of the air (ea) is the same as the saturation vapor pressure when the dew began to form (nighttime low temperature), then any air temperature throughout the day (Ta, which we assume would be higher) generates a saturation vapor pressure (es(Ta)) that is higher than ea and thus, relative humidity would be less than 1.

So, what about my nephew in the Philippines? Right now, a typical low temperature is 24℃ with a high of 34℃ (when it’s not raining).  Under that scenario, the relative humidity, although it would feel quite high, would only be around 56% at midday.

Next Week: Learn what’s wrong with using average relative humidity in scientific papers and what measurement should be used instead.

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The Quest for Accurate Air Temperature (Part 2)

In the conclusion to last week’s blog, Mark Blonquist, chief scientist at Apogee Instruments and air temperature measurement expert, explains the complexities of some proposed solutions to the problems that challenge accurate air temperature measurement.

accurate air temperature

An aspirated radiation shield manufactured by Apogee Instruments in Logan, Utah. Multiple models of passive and active shields are available from several manufacturers.

Solution:  Passive Radiation Shield

In addition to an accurate sensor, accurate air temperature measurement requires proper shielding and ventilation of the sensor.  Passive shields do not require power, making them simple and low-cost, but they warm above air temperature in low wind or high solar radiation. Warming is increased when there is snow on the ground due to increased solar radiation load from higher albedo and increased reflected solar radiation. Errors as high as 10 degrees C have been reported in passive shields over snow (Genthon et al., 2011; Huwald et al., 2009).  The figure below shows the differences in error for the two conditions.

Accurate Air Temperature

Corrections for Passive Shields

Equations to correct air temperature measurements in passive shields have been proposed, but often require measurement of wind speed and solar radiation, and are applicable to a specific shield design.  Corrections that don’t require additional meteorological measurements have also been proposed, such as air temperature adjustment based on the difference between air temperature and interior plate temperature differences. Others have suggested modifying traditional multi-plate passive shields to include a small fan that can be operated under specific conditions, but using natural aspiration when wind speeds are above an established threshold.

Solution: Active Shields

Warming of air temperature sensors above actual air temperature is minimized with active shields, which are more accurate than passive shields under conditions of high solar radiation load or low wind, but power is required for the fan. The power requirement for active shields ranges from one to six watts (80-500 mA). For solar-powered weather stations, this can be a major fraction of power usage for the entire station and has typically required a large solar panel and large battery. Power requirement and cost are disadvantages of active shields (Table 3), and they have led to the use of less accurate passive shields on many solar-powered stations.

Also, the fan motor can heat air as it passes by. Active shields should be constructed to avoid recirculation of heated air back into the shield.  There is no reference standard for the elimination of radiation-induced temperature increase of a sensor for air temperature measurement, but well-designed active shields minimize this effect.

Accurate Air Temperature

Table 3: Advantages and disadvantages of passive (naturally-aspirated) and active (fan-aspirated) radiation shields.

There is no reference standard for the elimination of radiation-induced temperature increase of a sensor for air temperature measurement, but well-designed active shields minimize this effect. Radiation-induced temperature increase was analyzed in long-term experiments over snow and grass surfaces by comparing temperature measurements from three models of active radiation shields (the same temperature sensor was used in all shields and were matched before deployment). Continuous measurements for one year indicated that mean differences among shield models were less than 0.1 C over grass and less than 0.3 C over snow. Differences increased with increasing solar radiation, particularly during winter months when there was snow (high reflectivity) on the ground.

Air Temperature: a Complex Measurement

The properties of materials and nearly all biological, chemical, and physical processes are temperature dependent. As a result, air temperature is perhaps the most widely measured environmental variable. Accurate air temperature measurement is essential for weather monitoring and climate research worldwide. The road to accuracy is complex, however, and will continue to be challenging given the trade-off between accuracy and power consumption with passive and active shields.

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The Quest for Accurate Air Temperature (Part 1)

Mark Blonquist, chief scientist at Apogee Instruments and air temperature measurement expert, explains the difficulties of obtaining accurate air temperature.

air temperature

The accuracy of air temperature has come a long way.

Accurate air temperature measurements are challenging, despite decades of research and development aimed at improving instruments and methods. People assume that they can use a static louvered radiation shield along with a temperature sensor and start measuring accurate air temperature.  That assumption is good if you are at a site where the wind blows all the time (roughly greater than 3 m/s).  However, if the wind at your field site is below that, you’re going to see errors due to solar heating (See Figure 1).

air temperature

Figure 1: Passive Shield Error: Data for 3 different models are graphed.

Challenge 1:  Accurate Sensors

Over the years, thermocouples, thermistors, and platinum resistance thermometers (PRTs) have been used for air temperature measurement, each with associated advantages and disadvantages. PRTs have the reputation as the preferred sensor for air temperature measurement due to high accuracy and stability. However, thermistors have high signal-to-noise ratio, are easy to use and low cost, and have similar accuracy and stability to PRTs. Thermocouples are becoming less commonly used for air temperature measurement because of the requirement of accurate measurement of reference temperature (i.e., meter temperature, data logger panel temperature).

air temperature

Challenge 2: Housing Air Temperature Sensors

The challenge of accurate air temperature measurement is far greater than having an accurate sensor, as temperature measured by an air temperature sensor is not necessarily equal to air temperature. Temperature sensors must be kept in thermal equilibrium with air through proper shielding in order to provide accurate measurements. To do this, housings should minimize heat gains and losses due to conduction and radiation, and enhance coupling to air via convective currents. They must shield it from shortwave (solar) radiant heating and longwave radiant cooling. A temperature sensor should also be thermally isolated from the housing to minimize heat transport to and from the sensor by conduction. The housing should provide ventilation so the temperature sensor is in thermal equilibrium with the air. Also, the housing should keep precipitation off the sensor, which is necessary to minimize evaporative cooling of the sensor. Conversely, condensation on sensors can cause warming. When condensed water subsequently evaporates, it cools the sensor via removal of latent heat (evaporational cooling).

Challenge 3: Size of Sensor

The magnitude of wind speed effects on air temperature measurement in passive shields is highly dependent on the thermal mass (size) of the sensor. Many weather stations have combined relative humidity and temperature sensors, which are much larger than a stand-alone air temperature sensor.  Air temperature errors from larger probes are greater than those from smaller sensors. One study, Tanner (2001), reported results where a common temperature/RH probe was approximately 0.5 degrees C warmer than a common thermistor in a weather-proof housing.

Thermal mass of temperature sensors also has a major impact on sensor response time. Sensors with small thermal mass equilibrate and respond to changes quicker and are necessary for applications requiring high-frequency air temperature measurements.

air temperature

Challenge 4:  Proper Shielding

In addition to an accurate sensor, accurate air temperature measurement requires proper shielding and ventilation of the sensor. Active, fan aspiration improves accuracy under conditions of low wind but requires power to operate the fan. Passive, natural aspiration minimizes power use but can reduce accuracy in conditions of high solar load or low wind speed.  Radiation shields for air temperature sensors should be placed in an environment where air temperature is representative. For example, air temperature sensors and radiation shields should not be deployed on the tops of buildings or in areas where they will be shaded by structures or trees. Conditions in microenvironments have that potential to be very different from surrounding conditions. Typical mounting heights for air temperature sensors are 1.2 to 2.0 meters above the ground. Typically, radiation shields should be mounted over vegetation.

Up next: Mark Blonquist explains the complexities of some of the proposed solutions to the above challenges in part 2.

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