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Pyranometer
Pyranometer
Pyranometer
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A pyranometer (from Greek πῦρ (pyr) 'fire' and ἄνω (ano) 'above, sky') is a type of actinometer used for measuring solar irradiance on a planar surface and it is designed to measure the solar radiation flux density (W/m2) from the hemisphere above within a wavelength range 0.3 μm to 3 μm.

A typical pyranometer does not require any power to operate. However, recent technical development includes use of electronics in pyranometers, which do require (low) external power (see heat flux sensor).

Explanation

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Spectrum and spectral response
Spectrum and spectral response

The solar radiation spectrum that reaches Earth's surface extends its wavelength approximately from 300 nm to 2800 nm. Depending on the type of pyranometer used, irradiance measurements with different degrees of spectral sensitivity will be obtained.

To make a measurement of irradiance, it is required by definition that the response to "beam" radiation varies with the cosine of the angle of incidence. This ensures a full response when the solar radiation hits the sensor perpendicularly (normal to the surface, sun at zenith, 0° angle of incidence), zero response when the sun is at the horizon (90° angle of incidence, 90° zenith angle), and 0.5 at a 60° angle of incidence. It follows that a pyranometer should have a so-called "directional response" or "cosine response" that is as close as possible to the ideal cosine characteristic.

Types

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Following the definitions noted in the ISO 9060,[1] three types of pyranometer can be recognized and grouped in two different technologies: thermopile technology and silicon semiconductor technology.

The light sensitivity, known as 'spectral response', depends on the type of pyranometer. The figure here above shows the spectral responses of the three types of pyranometer in relation to the solar radiation spectrum. The solar radiation spectrum represents the spectrum of sunlight that reaches the Earth's surface at sea level, at midday with A.M. (air mass) = 1.5.
The latitude and altitude influence this spectrum. The spectrum is influenced also by aerosol and pollution.

Thermopile pyranometers

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A thermopile pyranometer (also called thermo-electric pyranometer) is a sensor based on thermopiles designed to measure the broad band of the solar radiation flux density from a 180° field of view angle. A thermopile pyranometer thus usually measures from 300 to 2800 nm with a largely flat spectral sensitivity (see the spectral response graph) The first generation of thermopile pyranometers had the active part of the sensor equally divided in black and white sectors. Irradiation was calculated from the differential measure between the temperature of the black sectors, exposed to the sun, and the temperature of the white sectors, sectors not exposed to the sun or better said in the shades.

In all thermopile technology, irradiation is proportional to the difference between the temperature of the sun exposed area and the temperature of the shadow area.

Design

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Linedrawing of a pyranometer, showing essential parts: (1) cable, (3) pyranometer and (5) glass domes, (4) black detector surface, (6) sun screen, (7) desiccant indicator, (9) levelling feet, (10) bubble level, (11) connector

In order to attain the proper directional and spectral characteristics, a thermopile pyranometer is constructed with the following main components:

  • A thermopile sensor with a black coating. It absorbs all solar radiation, has a flat spectrum covering the 300 to 50,000 nanometer range, and has a near-perfect cosine response.
  • A glass dome. It limits the spectral response from 300 to 2,800 nanometers (cutting off the part above 2,800 nm), while preserving the 180° field of view. It also shields the thermopile sensor from convection. Many, but not all, first-class and secondary standard pyranometers (see ISO 9060 classification of thermopile pyranometers) include a second glass dome as an additional "radiation shield", resulting in a better thermal equilibrium between the sensor and inner dome, compared to some single dome models by the same manufacturer. The effect of having a second dome, in these cases, is a strong reduction of instrument offsets. Class A, single dome models, with low zero-offset (+/- 1 W/m2) are available.

In the modern thermopile pyranometers the active (hot) junctions of the thermopile are located beneath the black coating surface and are heated by the radiation absorbed from the black coating.[2] The passive (cold) junctions of the thermopile are fully protected from solar radiation and in thermal contact with the pyranometer housing, which serves as a heat-sink. This prevents any alteration from yellowing or decay when measuring the temperature in the shade, thus impairing the measure of the solar irradiance.

The thermopile generates a small voltage in proportion to the temperature difference between the black coating surface and the instrument housing. This is of the order of 10 μV (microvolts) per W/m2, so on a sunny day the output will be around 10 mV (millivolts). Each pyranometer has a unique sensitivity, unless otherwise equipped with electronics for signal calibration.

Usage

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Thermopile pyranometer as part of a meteorological station
Photovoltaic pyranometer on a plane of arrays
Photovoltaic pyranometer on a plane of arrays

Thermopile pyranometers are frequently used in meteorology, climatology, climate change research, building engineering physics, photovoltaic systems, and monitoring of photovoltaic power stations.

The solar energy industry, in a 2017 standard, IEC 61724-1:2017,[3] has defined the type and number of pyranometers that should be used depending on the size and category of solar power plant. That norm advises to install thermopile pyranometers horizontally (GHI, Global Horizontal Irradiation), and to install photovoltaic pyranometers in the plane of PV modules (POA, Plane Of Array) to enhance accuracy in Performance Ratio calculation.

To use the data measured by a pyranometer (horizontal or in-plane), quality assessment (QA) of the raw measured data is necessary.[4] This is because the pyranometer measurements typically suffer from environment-induced errors but also handling and neglect errors, such as:

  • Pollution of the glass dome (e.g. deposition of atmospheric dust, bird droppings, snowfall), which reduces the measured irradiance
  • Issues with positioning, resulting in measurements in a different plane (i.e. not horizontal or in-plane with PV modules) than expected
  • Data logger errors resulting in e.g. static values, oscillations, or data capped to a certain value
  • Reflections and shading from the surrounding objects resulting in inaccurate measurements (i.e. not corresponding to solar irradiance)
  • Calibration issues of the instrument, leading to measurement errors, offset, or drift over time
  • Dew, snow, or frost on the glass dome on lower-end pyranometers not equipped with heating units

Each of the above issues appears as a specific pattern in the measured time series. Thanks to this, the issues can be identified, the erroneous records flagged, and excluded from the dataset. The methods employed for data QA can be either manual, relying on an expert to identify the patterns, or automated, where an algorithm does the job. As many of the patterns are complex, not easily described, and require a particular context, manual QA is very common. A specialist software with suitable tools is required to perform the QA.

After the QA procedure, the remaining ‘clean’ dataset reflects the solar irradiance at the measurement site to within the uncertainty of measurement of the instrument. The ‘clean’ measured dataset can be optionally enhanced with data from a satellite-based solar irradiance model. This data is available globally for a much longer time period (typically decades into the past) than the data measured by the pyranometer. The satellite model data can be correlated (or site adapted) to the pyranometer-measured data to produce a dataset with a long time period of data accurate for the specific site, with a defined uncertainty. Such data can be used to perform bankable solar resource studies or produce Solar potential maps.

For monitoring of operational PV power plants, pyranometers play an essential role in verifying the solar irradiance available at any given time or over a certain time period. Due to weather variability, redundancy, and the spatial scale of contemporary solar plants (above 100MWp), multiple pyranometers are installed to provide accurate solar irradiation for each section of the PV power plant. IEC 61724-1:2017[5] international standard for example calls for at least 4 Class A thermopile pyranometers to be installed at 100MWp PV power plant at all times.

Solar measurements that were QA’d could be used to derive Key Performance Indicators (KPI) such as Performance ratio* - metrics used in asset health monitoring or various contractual scenarios relating to energy produced (billing) or asset management (i.e. O&M). In these calculations, the measured sum of in-plane irradiation over a certain period is used as the determinant to which normalized produced PV electricity is compared to. Due to the difficulty of obtaining reliable in-plane measurements, especially in operational power plants, Energy Performance Index is increasingly being used instead of the older Performance ratio metric.

Some secondary standard pyranometers are equipped with integrated dome heating systems designed to reduce measurement errors caused by dew, frost, or snow accumulation on the sensor. These heating mechanisms help maintain the optical clarity of the dome surface in cold or humid environments, ensuring uninterrupted and accurate solar irradiance readings. For example, the MS-80SH model by EKO Instruments incorporates such a heating system in compliance with the ISO 9060:2018 Class A standard, and is used in high-latitude or alpine regions where frost-related interference is common. [1]


Photovoltaic pyranometer – silicon photodiode

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Also known as a photoelectric pyranometer in the ISO 9060,[6] a photodiode-based pyranometer can detect the portion of the solar spectrum between 400 nm and 1100 nm. The photodiode converts the aforementioned solar spectrum frequencies into current at high speed, thanks to the photoelectric effect. The conversion is influenced by the temperature with a raise in current produced by the raise in temperature (about 0,1% • °C)

Design

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A photodiode pyranometer, model Quantum

A photodiode-based pyranometer is composed by a housing dome, a photodiode, and a diffuser or optical filters. The photodiode has a small surface area and acts as a sensor. The current generated by the photodiode is proportional to irradiance; an output circuit, such as a transimpedance amplifier, generates a voltage directly proportional to the photocurrent. The output is usually on the order of millivolts, the same order of magnitude as thermopile-type pyranometers.

Usage

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Photodiode-based pyranometers are implemented where the quantity of irradiation of the visible solar spectrum, or of certain portions such as UV, IR or PAR (photosynthetically active radiation), needs to be calculated. This is done by using diodes with specific spectral responses. Photodiode-based pyranometers are the core of luxmeters used in photography, cinema and lighting technique. Sometimes they are also installed close to modules of photovoltaic systems.

Photovoltaic pyranometer – photovoltaic cell

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Built around the 2000s concurrently with the spread of photovoltaic systems, the photovoltaic pyranometer is an evolution of the photodiode pyranometer. It answered the need for a single reference photovoltaic cell when measuring the power of cell and photovoltaic modules.[7] Specifically, each cell and module is tested through flash tests by their respective manufacturers, and thermopile pyranometers do not possess the adequate speed of response nor the same spectral response of a cell. This would create obvious mismatch when measuring power, which would need to be quantified.[8][9] In the technical documents, this pyranometer is also known as "reference cell".

A photovoltaic pyranometer, SM1

The active part of the sensor is composed of a photovoltaic cell working in near short-circuit condition. As such, the generated current is directly proportionate to the solar radiation hitting the cell in a range between 350 nm and 1150 nm. When invested by a luminous radiation in the mentioned range, it produces current as a consequence of the photovoltaic effect. Its sensitivity is not flat, but it is same as that of Silicon photovoltaic cell. See the Spectral Response graph.

Design

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A photovoltaic pyranometer is essentially assembled with the following parts:

  • A metallic container with a fixing staff
  • A small photovoltaic cell
  • Signal conditioning electronics

Silicon sensors such as the photodiode and the photovoltaic cell vary the output in function of temperature. In the more recent models, the electronics compensate the signal with the temperature, therefore removing the influence of temperature out of the values of solar irradiance. Inside several models, the case houses a board for the amplification and conditioning of the signal.

Usage

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Solar Irradiance Sensor, Model: Seven Sensor

Photovoltaic pyranometers are used in solar simulators and alongside photovoltaic systems for the calculation of photovoltaic module effective power and system performance. Because the spectral response of a photovoltaic pyranometer is similar to that of a photovoltaic module, it may also be used for preliminary diagnosis of malfunction in photovoltaic systems.

Reference PV Cell or Solar Irradiance Sensor may have up to 5 inputs ensuring the connection of Module Temperature Sensor, Ambient Temperature Sensor, Wind speed sensor, Wind Direction Sensor, and Relative Humidity, with only one Modbus RTU output connected directly to the Datalogger. This combination is called “weather station” which is suitable for monitoring the Solar PV Plants. This feature is one of the main differences between the Thermopile Pyranometer and the Reference Cell Solar Irradiance Sensor.

PV Reference Cell

Standardization and calibration

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Both thermopile-type and photovoltaic pyranometers are manufactured according to standards.

Thermopile pyranometers

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MS-80 Class A Fast Response & Spectrally Flat Pyranometer

Thermopile pyranometers follow the ISO 9060 standard, which is also adopted by the World Meteorological Organization (WMO). This standard discriminates three classes.

The latest version of ISO 9060, from 2018 uses the following classification: Class A for best performing, followed by Class B and Class C, while the older ISO 9060 standard from 1990 used ambiguous terms as "secondary standard", "first class" and "second class".,[10]

Differences in classes are due to a certain number of properties in the sensors: response time, thermal offsets, temperature dependence, directional error, non-stability, non-linearity, spectral selectivity and tilt response. These are all defined in ISO 9060. For a sensor to be classified in a certain category, it needs to fulfill all the minimum requirements for these properties.

‘Fast response’ and ‘spectrally flat’ are two sub-classifications, included in ISO 9060:2018. They help to further distinguish and categorise sensors. To gain the ‘fast response’ classification, the response time for 95% of readings must be less than 0.5 seconds; while ‘spectrally flat’ can apply to sensors with a spectral selectivity of less than 3% in the 0,35 to 1,5 μm spectral range. While most Class A pyranometers are ‘spectrally flat’, sensors in the ‘fast response’ sub-classification are much rarer. Most Class A pyranometers have a response time of 5 seconds or more.

The calibration is typically done having the World Radiometric Reference[11] (WRR) as an absolute reference. It is maintained by PMOD[12] in Davos, Switzerland.[13] In addition to the World Radiometric Reference, there are private laboratories such as ISO-Cal North America[14] who have acquired accreditation for these unique calibrations. For the Class A pyranometer, calibration is done following ASTM G167,[15] ISO 9847[16] or ISO 9846.[17][18] Class B and class C pyranometers are usually calibrated according to ASTM E824[19] and ISO 9847.[20]

SEVEN Class A Thermopile Pyranometer

Photovoltaic pyranometer

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Photovoltaic pyranometers are standardized and calibrated under IEC 60904-4 for primary reference samples and under IEC 60904-2 for secondary reference samples and the instruments intended for sale.

In both standards, their respective traceability chain starts with the primary standard known as the group of cavity radiometer by the World Radiometric Reference (WRR).[21]

Signal conditioning

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The natural output value of these pyranometers does not usually exceed tens of millivolt (mV). It is considered a "weak" signal, and as such, rather vulnerable to electromagnetic interferences, especially where the cable runs across decametrical distances or lies in photovoltaic systems. Thus, these sensors are frequently equipped with signal conditioning electronics, giving an output of 4-20 mA or 0-1 V.

Another solution implies greater immunities to noises, like Modbus over RS-485, suitable for ambiances with electromagnetic interferences typical of medium-large scale photovoltaic power stations, or SDI-12 output, where sensors are part of a low power weather station. The equipped electronics often concur to easy integration in the system's SCADA.

Additional information can also be stored in the electronics of the sensor, like calibration history, serial number.

See also

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References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia

Pyranometer

View on Grokipedia
from Grokipedia
A pyranometer is a scientific instrument used to measure the total solar irradiance incident on a horizontal surface from a 180-degree hemispherical field of view, capturing both direct beam and diffuse sky radiation in units of watts per square meter (W/m²). It is classified as a type of actinometer specifically designed for broadband solar radiation flux within the spectral range of approximately 0.3 to 3.0 micrometers, providing essential data for global horizontal irradiance (GHI), diffuse horizontal irradiance (DHI), or plane-of-array measurements. The working principle of a pyranometer relies on either or technology. In thermopile-based models, solar radiation passes through a transparent dome and is absorbed by a black-painted surface, generating heat that creates a temperature differential across thermoelectric junctions via the Seebeck effect; this differential produces a voltage output proportional to the , with the instrument featuring a white inner surface to minimize convection losses. Photodiode-based pyranometers, often using silicon sensors, convert incident photons directly into an electrical current through the , offering lower cost and faster response but narrower spectral sensitivity (typically 0.35 to 1.1 micrometers). Both types are calibrated against reference standards, such as those traceable to the (WMO), with classifications under ISO 9060:2018 as spectrally flat Class A (secondary reference, highest precision), Class B (first class), or Class C (second class) instruments. Pyranometers have evolved since their early development in the late , with foundational contributions from instruments like the Ångström pyrheliometer in 1893 and proposals for total irradiance measurement by in , leading to modern standardized designs essential for accurate solar monitoring. They play a critical role in applications such as meteorological and climatological research, where they quantify availability for and modeling; solar energy systems, including photovoltaic (PV) performance monitoring and site assessment; and specialized fields like building energy efficiency and agricultural optimization. High-quality pyranometers achieve accuracies of ±1-5% under varying sky conditions, with response times under 20 seconds, ensuring reliable for global networks like the Baseline Surface Radiation Network (BSRN).

Introduction

Definition and Purpose

A pyranometer is a type of designed to measure the of solar received by a plane surface, typically oriented horizontally, integrating both direct beam and across a 180° . This instrument quantifies broadband solar in units of watts per square meter (W/m²), capturing the total energy from the sun incident on the surface. The primary purpose of a pyranometer is to evaluate total shortwave within the wavelength range of approximately 0.3 to 3 μm, supporting applications such as monitoring, solar resource assessment for photovoltaic systems, and studies of Earth's energy balance. Unlike pyrheliometers, which measure only direct beam , pyranometers provide a comprehensive measure of global horizontal , making them essential for meteorological networks and environmental research. Key components of a pyranometer include a transparent dome made of or to ensure hemispherical acceptance of incoming , a black absorbing surface that uniformly captures the energy, and an output that converts the absorbed into an electrical signal, such as voltage or current. The design incorporates a cosine response, which maintains accuracy by responding proportionally to the cosine of the , allowing reliable quantification across varying incidence angles. Pyranometers are available in types such as thermopile-based models for high spectral coverage and accuracy, and photovoltaic or variants for cost-effective applications with narrower spectral response.

Historical Development

The development of the pyranometer traces its origins to early efforts in measuring solar radiation, building on pioneering work by in the , who devised the heliothermometer to quantify the rise from solar heating, demonstrating an increase in solar radiation with altitude. This laid foundational principles for radiation instruments, though de Saussure's device focused on thermal effects rather than direct . The first dedicated pyranometer emerged in 1919, developed by Swedish Anders Knutsson Ångström as an improvement over his father's 1893 for direct beam radiation; Ångström's design employed a detector to measure global horizontal , incorporating absorption elements to capture both direct and diffuse components. Early commercialization of thermopile-based pyranometers began shortly thereafter, with Dutch firm Kipp & Zonen initiating production in 1913 of sensitive sensors for measurement, which were adapted into full pyranometers by the using multiple thermocouples to enhance sensitivity and accuracy in detecting solar flux. These models marked a shift from rudimentary calorimetric approaches to electrical detection, enabling more reliable field deployments in meteorological stations. By the mid-20th century, advancements included the application of blackbody coatings such as Parsons Optical Black Lacquer in the 1930s, which improved across 1–40 µm wavelengths to better approximate ideal blackbody behavior and reduce errors. In the early 1930s, F. Albrecht proposed a pyrradiometer for measuring total , bridging the gap between direct and global measurements. The (WMO) formalized pyranometer use in the 1950s, integrating them into global observation networks during the (1957–1958) to standardize solar radiation data for climate monitoring. In the late 20th and early 21st centuries, pyranometer technology diversified with the rise of photovoltaic (PV) systems, leading to the emergence of silicon photodiode-based models in the 1980s and s for cost-effective irradiance monitoring in applications. These sensors, leveraging 's spectral response similar to PV modules, facilitated widespread adoption in performance assessment. efforts culminated in ISO 9060 (), which classified pyranometers by accuracy for use, with an update in 2018 introducing spectral error metrics to address modern calibration needs. A further advancement appeared in ISO 9846 (2025), specifying three methods for calibrating pyranometers against pyrheliometers to enhance in field and laboratory settings. Contemporary innovations focus on environmental robustness, such as ventilated and heated pyranometer designs introduced in the , exemplified by the Apogee SP-510 model, which incorporates airflow and low-power heating to minimize errors from , , and on the dome. This evolution aligns with the expansion of infrastructure since the 2000s, where pyranometers now integrate with IoT networks for transmission in large-scale solar farms, improving operational efficiency and .

Operating Principles

Thermoelectric Detection

In thermoelectric detection, solar radiation is absorbed by a blackened surface, which heats up and creates a across the junctions of a sensor. This gradient generates an through the Seebeck effect, where dissimilar metals or semiconductors produce a voltage proportional to the difference between the hot absorbing surface and a cooler . The resulting output voltage is directly related to the incident , enabling precise measurement of global horizontal radiation without spectral selectivity issues common in other detection methods. The key relationship is given by the equation for output voltage: V=αΔTV = \alpha \Delta T where VV is the generated voltage, α\alpha is the (typically 10–50 μV/K for thermopile materials), and ΔT\Delta T is the difference between the hot and cold junctions. A multi-junction , consisting of 20–100 thermocouples connected in series, amplifies this signal for enhanced sensitivity while maintaining linearity. The absorbing surface is coated with a highly emissive black material, such as or gold-black, achieving absorptivity greater than 95% across the solar from 0.3 to 3 μm, ensuring efficient capture of incoming . These sensors exhibit a spectral response from 300 to 3000 nm, capturing nearly all without significant bias, unlike photovoltaic detectors limited to specific bands. The design incorporates that provides cosine correction, ensuring accurate response to at varying angles. The thermal time constant is approximately 1–5 seconds, allowing reliable tracking of changes in typical atmospheric conditions. Thermoelectric detection offers high accuracy, with uncertainties of ±1–2% in Class A instruments, minimal spectral dependence, and good stability across ambient temperature variations due to the principle.

Photovoltaic Detection

In photovoltaic detection, incident photons from solar radiation are absorbed by a material, typically , exciting electrons from the valence band to the conduction band and generating electron-hole pairs. These charge carriers are separated by the built-in of a p-n junction, producing a that is directly proportional to the incident . The short-circuit current or diffusion voltage across the junction is measured to quantify the solar flux, enabling real-time monitoring without relying on thermal effects. The photocurrent II generated in the detector follows the relation I=ηqΦA,I = \eta q \Phi A, where η\eta is the quantum efficiency of the , qq is the (1.6×10−191.6 \times 10^{-19} C), Φ\Phi is the photon flux density (photons per unit area per second), and AA is the active area of the detector. This equation captures the linear conversion of photon flux—derived from divided by —to electrical current, with typical values for yielding responsivities around 0.3–0.6 A/W under standard conditions. Key components include a p-n junction or photovoltaic cell as the core detector, often paired with a diffuser (such as or Teflon) to ensure a cosine angular response for accurate hemispherical integration of . Anti-reflective coatings on the surface minimize light loss, while integrated temperature compensation elements, like thermistors or resistors, adjust for sensitivity variations with ambient conditions. These elements collectively enable stable operation in field environments. Photovoltaic detectors exhibit a spectral response, typically spanning 400–1100 nm for , with peak sensitivity around 900 nm, aligning partially but not fully with the solar (300–4000 nm). Their is fast, often less than 1 μs for the bare , though instrument-level response remains under 1 second due to and diffusers. Sensitivity is representative at 0.05–0.1 μA per W/m² for calibrated sensors, providing high up to 2000 /m². A primary limitation is spectral mismatch, as the detector underestimates (<400 nm) and infrared (>1100 nm) contributions, leading to errors up to 3–5% under non-standard atmospheric conditions compared to references. Additionally, dependence introduces a coefficient of approximately 0.08–0.1% per °C, requiring compensation to maintain accuracy across environmental variations. Compared to methods, photovoltaic detection offers lower cost but trades off fidelity for speed.

Types of Pyranometers

Thermopile Pyranometers

Thermopile pyranometers represent the reference standard for high-precision solar radiation measurements due to their broadband spectral response and thermal detection mechanism, which relies on the Seebeck effect to generate a voltage proportional to temperature differences induced by absorbed radiation. The core sensor consists of a central thermopile with a black absorbing coating that captures incoming solar irradiance across a 180° field of view, converting it to heat while the instrument's body acts as a white-painted heat sink to maintain thermal equilibrium and minimize offsets. A hemispherical glass dome, typically made of high-quality glass transmitting from approximately 300 to 3000 nm; advanced models use fused silica or quartz domes to extend the range to as low as 200 nm and up to 4000 nm in some cases (e.g., Hukseflux SR22), protects the sensor; these domes are typically 2–5 mm thick to ensure durability and optical clarity without distorting the cosine response. Modern designs, such as the Hukseflux SR20, incorporate ventilation ports or compatibility with active ventilation units to reduce convection-related errors from air currents or condensation. Operationally, these instruments require precise horizontal leveling using integrated bubble levels and adjustable mounts to achieve accuracy within 0.1°, ensuring reliable cosine-weighted measurements of global horizontal irradiance. Passive or active ventilation systems minimize offsets, with unventilated models exhibiting zero offsets below 5 W/m² and ventilated ones under 2.5 W/m² during nighttime shading for baseline corrections. The thermopile's sensitivity typically ranges from 7 to 15 μV/W/m², providing an analog voltage output that scales linearly with up to 2000 W/m², though individual certificates specify exact values. These pyranometers excel in high-precision applications, serving as reference instruments in meteorological stations within the Baseline Surface Radiation Network (BSRN) for long-term climate monitoring. They are also essential for solar resource assessment in photovoltaic (PV) yield modeling, where accurate irradiance data informs energy production forecasts and system performance analysis. Performance meets ISO 9060:2018 Class A standards, offering ±1.8% uncertainty for daily totals and non-stability below ±0.5% per year, with expected longevity exceeding 10 years when recalibrated every 2 years.

Silicon Photodiode Pyranometers

Silicon photodiode pyranometers employ a p-n junction photodiode as the core sensing element, which produces a voltage output proportional to the flux in the visible and near-infrared spectrum, typically spanning 400–1100 nm. The photodiode is integrated with an optical diffuser, such as a machined Teflon layer angled at 45° or a holographic element, to achieve cosine correction that closely approximates the ideal angular response for hemispherical measurements. Encapsulation in durable materials like black or protects the from environmental factors, while a built-in or regulation system compensates for variations, maintaining stability across operating ranges from -40°C to +60°C. Typical sensitivity for these devices is around 0.2 mV/W/m², enabling outputs up to several hundred millivolts under full solar conditions. Operationally, these pyranometers feature low power consumption, often under 1 , with self-powered variants drawing from the photodiode's own generation for remote deployments. A spectral filter or the inherent response is tuned to mimic the solar spectrum under 1.5 conditions, though deviations occur under non-standard spectra like skies, necessitating error correction factors based on angle and atmospheric composition. This photovoltaic detection mechanism ensures rapid response times below 100 ms, far exceeding the speed of alternatives. These instruments find typical use in continuous monitoring for , such as input to crop evapotranspiration models like the Penman-Monteith equation, where their affordability supports large-scale field networks. They also serve educational laboratories for hands-on solar radiation experiments and as secondary references in solar farms to validate primary sensors without high costs. Performance aligns with ISO 9060:2018 Class B specifications, offering ±3% in measurements under standard conditions, with cosine errors under 2% up to 75° angle and temperature dependencies below 4% over wide ranges. Their cost-effectiveness, often under $500 per unit, makes them ideal for expansive monitoring networks in mid-range precision applications.

Photovoltaic Cell Pyranometers

Photovoltaic cell pyranometers employ multicrystalline or cells akin to those in standard photovoltaic panels, incorporating diffusers for cosine response correction across a wide . These sensors operate without an external power source, generating output directly as short-circuit current from the , with an active sensing area of approximately 1 cm². Their operational design ensures a response closely matched to commercial PV modules, covering the range of 400–1100 nm to accurately reflect conditions relevant for . Integrated on-board allows for selective measurement of diffuse components, while the rugged enclosure supports direct mounting on outdoor PV arrays in varied environmental conditions. These pyranometers are commonly deployed for real-time performance ratio monitoring in large-scale solar power plants, enabling ongoing assessment of yield against expected outputs. They also facilitate fault detection within PV strings by identifying deviations in exposure and support portable scouting for site evaluations prior to installation. Performance characteristics include classification as ISO Class C instruments with a typical uncertainty of ±5% under standard conditions, emphasizing their suitability for practical PV applications. High durability against harsh weather ensures reliable operation, with expected lifespans aligned to those of PV systems at around 25 years.

Calibration and Standardization

Calibration Methods

Pyranometer calibration ensures accurate measurement of by determining the instrument's sensitivity, typically expressed in μV/(W/m²), under standardized conditions such as 1000 W/m² , 20°C , horizontal orientation, and a clear-sky . Common methods include outdoor comparisons using natural , indoor simulations with artificial sources, and transfer calibrations from reference instruments, each selected based on required uncertainty and environmental constraints. These procedures maintain to the World Radiometric Reference (WRR), the international standard for measurements. Outdoor calibration often employs the shade-unshade technique, specified in ISO 9846:2025, where a measures direct beam under clear-sky conditions, and a shading disk alternately blocks the sun to isolate global horizontal irradiance components. The alternating sun and shade method involves repeated unshaded and shaded measurements with position exchanges between the test pyranometer and reference, minimizing directional errors, while the continuous sun and shade variant uses a shaded reference pyranometer alongside the for simultaneous comparisons. The collimation tube method, another ISO 9846 approach, mounts the test pyranometer on a with a tube to align its precisely with the 's direct beam. These outdoor methods are performed on sunny days with zenith angles typically between 15° and 75° to ensure stable . Indoor calibration, outlined in ISO 9847:2023 for component tests, uses an and halogen lamps to simulate uniform , transferring sensitivity from a reference pyranometer previously calibrated outdoors. The Type A procedure involves unshaded and shaded measurements under the lamp beam (approximately 3000 K ) at 1000 /, with instrument position exchanges to average out spatial nonuniformities, and requires identical models to limit and errors. This method provides weather-independent results but demands verification of beam stability and of the reference to natural sunlight spectra. Transfer calibration, also per ISO 9847:2023 (Type B method), compares the test pyranometer to a reference instrument under field conditions or in a controlled setup, deriving the sensitivity ratio from simultaneous readings over clear-sky periods. The reference pyranometer must itself be traceable to the WRR, ensuring the chain of comparisons yields uncertainties below 1.8% for second-class instruments. This approach is commonly used for field recalibrations, with data averaged over multiple days to reduce variability from atmospheric conditions. Traceability to the WRR is achieved through calibrations at the Physikalisch-Meteorologisches Observatorium /World Radiation Center (PMOD/WRC), where the WRR is realized by the World Standard Group of six cavity , with factors assigned during International Pyrheliometer Comparisons every five years. ISO 9846:2025 methods using directly link to WRR-traceable direct beam measurements, while ISO 9847:2023 indoor and transfer methods rely on references calibrated via ISO 9846. PMOD/WRC issues certificates for over 100 instruments annually, supporting global networks like the Baseline Surface Radiation Network. Key error sources in calibration include thermal offsets, angular response deviations, and spectral mismatch, each requiring specific corrections for accuracy. Thermal offsets, arising from imbalances between the detector and domes (typically -10 to +5 W/m² in unventilated instruments), are corrected using the shading disk method, where the disk blocks solar input at night or low angles (>105°) to measure baseline offsets, often limited to below 10 W/m² with ventilation. Angular response deviations, caused by cosine errors in the instrument's , are characterized during by rotating the pyranometer under collimated light, with corrections applied to limit deviations to <10 W/m² for a 1000 W/m² beam up to 80° angle. The spectral mismatch factor KK, defined as the ratio of the instrument's integrated response under actual spectrum to the reference spectrum, accounts for non-flat spectral sensitivities (e.g., in silicon vs. thermopile types), calculated as K=∫E(λ)S(λ)dλ∫Er(λ)Sr(λ)dλK = \frac{\int E(\lambda) S(\lambda) d\lambda}{\int E_r(\lambda) S_r(\lambda) d\lambda}, where EE and SS are irradiance and responsivity, ensuring errors below 1% for matched conditions. Calibration frequency depends on instrument class per ISO 9060:2018, with all classes requiring recalibration at least every two years or after exposure to conditions that may affect calibration to maintain performance within class limits (typically ≤1.8% overall uncertainty at 95% confidence for Class A). Uncertainty budgets for outdoor methods, including pyrheliometer traceability (±0.3%), stability (±0.5%), and angular effects (±0.5%), typically yield overall values of ±1.5% at 95% confidence (k=2). Indoor methods achieve similar or lower uncertainties (<1.5%) when spectral matching is verified.

Classification and Standards

Pyranometers are classified according to the international standard ISO 9060:2018, which categorizes them into three performance-based classes—A, B, and C—based on their accuracy and suitability for various applications. Class A represents secondary standards with the highest precision, achieving performance limits that allow uncertainties typically ≤1.8% (k=2) under reference conditions, suitable for scientific research and reference measurements; Class B denotes first-class instruments with limits allowing ≤3% uncertainty, appropriate for general meteorological monitoring; and Class C indicates second-class devices with ≤5% uncertainty, used for less demanding routine observations. This classification is determined through rigorous testing of spectral selectivity (ensuring flat response across 0.3–3 μm wavelengths), directional response (cosine error under varying solar angles), and thermal characteristics (including zero offsets due to temperature changes). Governing standards extend beyond classification to specific sectors, such as IEC 61724-1:2021 for photovoltaic (PV) system performance monitoring, which mandates Class A or B pyranometers for high-accuracy irradiance measurements in solar energy assessments. The World Meteorological Organization (WMO) provides guidelines in its Guide to Instruments and Methods of Observation (WMO-No. 8, 2024 edition), recommending at least Class B for national meteorological networks and Class A for baseline stations like those in the Baseline Surface Radiation Network (BSRN). Additionally, ISO 9846:2025 specifies three methods for calibrating pyranometers using a pyrheliometer as reference: alternating sun and shade, continuous sun and shade, and collimation tube. Calibration serves as a prerequisite for assigning these classes, verifying compliance with the standard's performance thresholds. Compliance testing for classification involves evaluating key parameters, including zero offsets (thermal radiation ≤7 W/m² for Class A, non-zero tilt ≤1 W/m²), temperature response (≤±1% change from -10°C to 40°C), and linearity (deviation ≤0.5% across 0–1000 W/m² irradiance levels). These tests ensure reliable operation under real-world conditions, such as varying solar spectra and environmental temperatures. The adoption of these standards facilitates global interoperability, particularly in networks like the Global Energy Balance Archive (GEBA), where Class A pyranometers are mandatory for establishing accurate research baselines on surface radiation budgets.

Applications and Usage

Meteorological and Research Applications

Pyranometers play a central role in meteorological observations by providing measurements of global solar radiation, which are essential for global radiation networks such as the Baseline Surface Radiation Network (BSRN). Established in 1992 under the World Climate Research Programme, BSRN comprises over 50 stations worldwide that utilize high-precision pyranometers to record continuous, high-quality data on downward shortwave radiation, enabling the detection of long-term trends and validation of satellite-derived irradiances; as of 2025, there are approximately 51 operational stations. These measurements serve as critical inputs to numerical weather prediction models, where observed insolation data from pyranometers improve short-term forecasts of surface solar irradiance by assimilating real-time radiation observations into model initialization processes. Additionally, pyranometers facilitate studies of cloud properties through the analysis of the diffuse fraction of global radiation, as the ratio of diffuse to total irradiance correlates strongly with cloud optical thickness and coverage, allowing retrospective estimation of cloud types and amounts from ground-based records. In scientific research, pyranometers contribute to understanding surface energy balance in ecological systems, particularly within networks like FLUXNET, where they measure incoming shortwave radiation as a key component of the energy budget alongside eddy covariance fluxes of CO2, water vapor, and heat. This integration helps quantify how solar forcing influences carbon uptake and ecosystem productivity, with radiation data essential for closing the energy balance and partitioning net radiation into latent, sensible, and ground heat fluxes. Pyranometers also support the derivation of UV index values by providing broadband solar irradiance data that, when combined with ozone and aerosol models, estimate erythemal UV doses for public health assessments. For long-term climate records, pyranometer observations from extended monitoring sites reveal trends in solar forcing, such as decadal variations in surface irradiance linked to changes in cloudiness and aerosols, informing reconstructions of historical solar variability over periods spanning decades. Thermopile pyranometers, valued for their spectral response matching the solar spectrum, are preferred in these research baselines for their accuracy in capturing total hemispherical irradiance. Standard setup for pyranometer deployment in these applications involves horizontal mounting at approximately 1.5 meters above a uniform surface like short-cut grass to minimize terrain effects and ensure representative sampling of incident radiation, as recommended by World Meteorological Organization guidelines. To distinguish direct and diffuse components, pyranometers are often collocated with pyrheliometers on solar trackers, where the global reading minus the direct normal irradiance yields the diffuse fraction, enhancing the utility of data for atmospheric analyses. Data logging occurs at 1-minute intervals to capture diurnal and short-term variability, with high-frequency sampling (up to 1 Hz) averaged to this resolution for archival in networks like BSRN. Pyranometer data have informed key case studies, including their integration into Intergovernmental Panel on Climate Change (IPCC) assessments for evaluating radiative forcing and surface energy budgets, where ground-based irradiance records validate model simulations of solar radiation trends. Measurement errors in pyranometers, such as a ±2% uncertainty in irradiance, can propagate to approximately 5% discrepancies in surface energy balance calculations, particularly affecting albedo-derived estimates of reflected radiation and thus the partitioning of net radiation in climate models.

Solar Energy Systems

In photovoltaic (PV) systems, pyranometers provide critical irradiance measurements as input for yield forecasting, particularly through plane-of-array (POA) irradiance on tilted planes that match module orientations. These measurements enable accurate prediction of energy output by accounting for site-specific solar resource variations, supporting system design and operational planning. For instance, POA data from pyranometers is essential for validating expected performance against actual generation in utility-scale installations. Pyranometers also facilitate soiling detection in PV systems by comparing output ratios, such as the soiling ratio defined as the actual output of soiled modules divided by the expected output from clean references under equivalent irradiance conditions. This approach quantifies dust accumulation effects on transmittance, allowing operators to schedule cleanings that mitigate performance degradation. Soiling-induced losses can reach up to 20% in dusty arid regions, underscoring the need for routine monitoring to maintain efficiency. Compliance with IEC 61724-1 standards requires high-accuracy pyranometer deployments in Class A monitoring systems to ensure bankable data for financing and insurance, specifying uncertainty limits below 2% for irradiance measurements. This standardization enhances investor confidence by providing verifiable performance metrics throughout a PV plant's lifecycle. Silicon photodiode pyranometers, matched to PV spectral response, offer direct correlation for precise yield assessments in these setups. In solar thermal systems, pyranometers monitor incident heat flux to evaluate collector efficiency, serving as the primary input for calculating thermal output relative to absorbed solar energy. For concentrating solar power (CSP) plants, pyranometers measure global horizontal irradiance (GHI) and diffuse horizontal irradiance (DHI), enabling separation models to derive direct normal irradiance (DNI) essential for heliostat and trough performance optimization. Accurate GHI and DHI data ensure reliable assessment of optical and thermal losses in CSP operations. Integration of pyranometers in solar energy systems often involves multi-pyranometer arrays to capture global, diffuse, and tilted irradiance components simultaneously, improving spatial resolution across large installations. These arrays, such as cubic multi-directional configurations, estimate beam and global tilted irradiance without additional shading mechanisms. Wireless networks of pyranometers enable farm-scale mapping of irradiance variability, supporting real-time grid integration and resource allocation in utility-scale solar farms. Accurate irradiance data from such systems can reduce levelized cost of energy (LCOE) by minimizing yield prediction uncertainties and lowering financial risks through enhanced operational efficiency. Challenges in pyranometer deployment for solar energy include soiling losses, which can accumulate to 20% in dusty environments and distort irradiance readings if unaddressed. Real-time correction methods employ reference cells alongside pyranometers to detect and adjust for soiling discrepancies, ensuring reliable data for performance evaluation and maintenance scheduling.

Signal Processing

Analog Signal Conditioning

Analog signal conditioning in pyranometers involves the initial electronic processing of raw sensor outputs to enhance signal quality, amplify low-level signals, and mitigate environmental interferences before further acquisition. This step is essential for thermopile and photovoltaic-based sensors, which produce microvolt or nanoampere-level signals proportional to solar irradiance, typically requiring conversion to measurable voltage levels in the millivolt to volt range. For thermopile pyranometers, the output is a low-level differential voltage, often in the range of 5–20 µV per W/m², necessitating voltage amplification with gains of 100–1000 using operational amplifiers or instrumentation amplifiers to scale signals to 0–5 V or 0–10 V for compatibility with data systems. A nominal gain of 500 is common for bipolar inputs from floating thermopile sources, ensuring sufficient resolution for irradiance up to 1400 W/m². Photovoltaic pyranometers, employing silicon photodiodes, generate photocurrents on the order of nanoamperes to microamperes, which are converted to voltage via transimpedance amplifiers featuring feedback resistors typically around 1 MΩ to produce outputs of several volts at full-scale irradiance. This current-to-voltage conversion maintains linearity while providing a high-impedance input to prevent loading the sensor. Noise reduction is achieved through low-pass RC filters with cutoff frequencies of 0.1–1 Hz, tailored to the sensor's response time constant of several seconds, effectively attenuating high-frequency electromagnetic interference and amplifier noise without distorting the slowly varying irradiance signal. Offset nulling circuits, often integrated with chopper-stabilized op-amps, compensate for thermal drifts in amplifiers and sensors, minimizing baseline errors to below 1 µV. Key components include shunt resistors for scaling current outputs in photovoltaic configurations, typically 100–500 Ω to convert to proportional voltages, and temperature compensation circuits utilizing PT100 resistance temperature detectors embedded in the sensor body to adjust gain and offset for thermal variations across -40°C to +70°C. These PT100 sensors provide resistance-based feedback to op-amp circuits, reducing temperature-induced errors in sensitivity by up to 0.1% per °C. Error mitigation incorporates instrumentation amplifiers with high common-mode rejection ratios (>100 dB) to suppress from power lines or RF sources, ensuring over cable runs up to 300 m. Bandwidth is matched to the pyranometer's (1–30 s) via adjustable filter poles, preventing overshoot while preserving dynamic response to changes.

Digital Data Acquisition

Digital data acquisition in pyranometers involves the conversion of conditioned analog signals from the into digital format, enabling precise recording and analysis of measurements. Typically, analog-to-digital converters (ADCs) with resolutions ranging from 12 to 24 bits are employed to digitize the voltage output, ensuring high fidelity in capturing variations down to milliwatts per square meter. For instance, the SR20-D2 pyranometer utilizes a 24-bit ADC to achieve this precision. Sampling rates generally operate between 1 and 60 Hz, with 1 Hz being standard for routine monitoring and higher rates up to 60 Hz applied in or high-resolution studies to resolve rapid fluctuations in solar radiation. Recording of digitized data is handled by dedicated dataloggers, often featuring storage for robust, long-term retention of measurements. Integration periods conform to (WMO) standards, aggregating data over 1 to 60 minutes to produce averages that minimize noise while capturing diurnal patterns; 1-minute intervals are recommended for detailed analysis, while hourly sums support broader meteorological reporting. Timestamping ensures data traceability, frequently synchronized via integrated GPS receivers in modern loggers to provide accurate UTC timing and location metadata, preventing drift in long deployments. Initial analysis occurs through embedded or companion software that applies corrections to raw digital data, enhancing accuracy beyond the analog stage. Cosine errors, arising from non-ideal angular responses, and temperature dependencies are mitigated using polynomial algorithms; for example, a fourth-order polynomial corrects temperature effects in SMP series pyranometers, limiting deviations to under 1% across -40°C to +70°C. Quality checks include thresholds on the clearness index (Kt), defined as the ratio of measured global horizontal irradiance to extraterrestrial irradiance, to flag anomalies such as cloud cover inconsistencies or instrument faults, with Kt values typically ranging from 0.05 to 0.8 under varying sky conditions. Contemporary pyranometers incorporate IoT capabilities, such as Modbus RTU output over RS-485 interfaces, facilitating seamless integration with supervisory control and data acquisition (SCADA) systems or networked sensors. Cloud-based platforms enable remote upload and access, allowing real-time monitoring and automated backups from field deployments. Quantization effects from the ADC contribute negligibly (<0.1%) to the overall measurement uncertainty. Per WMO guidelines, the total uncertainty for daily sums is approximately ±2%, alongside calibration traceability to the World Radiometric Reference (WRR).

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