Pre-launch Calibration Research Articles

Landsat 9 Transfer to Orbit of Pre-Launch Absolute Calibration of Operational Land Imager (OLI)

Landsat 9 Operational Land Imager (L9-OLI) was launched on 27 September 2021, after completing a successful radiometric pre-launch calibration and characterization phase. The radiometric math model that governs the ground system—the data processing and analysis system (DPAS)—uses various calibration parameters that had been derived based on the pre-launch tests and analysis. During the on-orbit commissioning phase, the OLI system acquired specific sets of data collects, which enabled the revalidation of the pre-launch absolute calibration scale and other associated instrument performance characteristics. The analysis results shown in this paper focus on the activities and results related to the transfer-to-orbit analysis for the SI-traceable pre-launch radiometric scale. Key topics discussed in this paper include: radiance and reflectance calibration parameters for OLI; solar diffuser collects; stimulation-lamp collects; dark response; signal-to-noise ratios; and noise characteristics; radiometric response stability and the on-orbit update to the radiance to reflectance conversion factors. It will be shown that the OLI response during the early on-orbit operation matched pre-launch results and therefore this re-validates the absolute radiometric scaling at the predicted pre-launch level within the expected level of uncertainties. The launch did not cause any significant changes to the OLI system from the perspective of the absolute radiometric calibration performance. Once the transfer to orbit of the absolute calibration was confirmed, it created a solid basis for further on-orbit refinements of the radiance calibration parameters. As such, follow-on calibration refinements are discussed in other articles within this special issue, and they address issues such as uniformity as well as cross-calibration activities.

Analysis on applicability of nonlinearity coefficients derived from prelaunch calibration tests to onboard calibration of Microwave Humidity Sounder （MWHS-Ⅲ） on FY-3E satellite

Analysis on applicability of nonlinearity coefficients derived from prelaunch calibration tests to onboard calibration of Microwave Humidity Sounder （MWHS-Ⅲ） on FY-3E satellite

Time Series Analysis-Based Long-Term Onboard Radiometric Calibration Coefficient Correction and Validation for the HY-1C Satellite Calibration Spectrometer

The HY-1C Satellite Calibration Spectrometer (SCS) is designed for high-accuracy and high-frequency cross-calibration for sensors mounted on the HY-1C satellite; thus, its onboard calibration consistency and stability are crucial for application. Most onboard calibration errors can be corrected via observation physical models and the prelaunch calibration process. However, the practical SCS calibration coefficient still retains some regularity, which indicates the existence of residual calibration errors. Therefore, in this study, a time series analysis-based method is proposed to eliminate this residual error. First, the SCS onboard calibration method and coefficients are described; second, a seasonal–trend decomposition based on the Loess (STL) method is used to model the SCS calibration coefficient; third, the calibration coefficient is validated, corrected and predicted using the constructed STL model; and finally, a long short-term memory (LSTM) neural network method is also used to model and forecast the calibration coefficient. The analysis results show that: 1. the STL method can effectively model, interpret and correct the SCS calibration coefficient error; and 2. the LSTM method can also fit and forecast the calibration coefficients, while its accuracy and interpretability are poor. The proposed methods provide a data analysis-based perspective to monitor remote sensors and help improve the calibration accuracy.

Band-Averaged Response Sensitivity Study of an Imaging Spectrometer for the CLARREO Pathfinder Mission

Prelaunch absolute, SI-traceable radiometric calibration of satellite-based sensors is key to ensuring the utility of imaging spectrometer-based data products. The development of detector-based calibration techniques leads to the feasibility of meeting the 0.3% uncertainty level needed to provide climate quality data sets. Detector-based calibration is a method in which a well-understood and stable transfer radiometer is calibrated in a standards laboratory to SI-traceable standards, and transported to a facility calibrating a sensor of interest. The transfer radiometer provides the calibration of the source used in the radiometric calibration. A detector-based calibration approach is part of the prelaunch calibration of the CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) sensor with the Goddard Laser for Absolute Measurement of Radiance (GLAMR) system. The SI-traceability of GLAMR is through the electric watt as part of the absolute radiometric calibration of the detectors at the National Institute of Standards and Technology using the Primary Optical Watt Radiometer. The current work uses GLAMR data collected with a visible and near-infrared imaging spectrometer calibration demonstration system to develop a source/sensor modeled calibration data set as part of a sensitivity study to evaluate uncertainties from the spectral sampling and processing methods that accompany the GLAMR calibration process. The spectral “supersets” include realistic instrumental features as well as effects from the GLAMR source. The methods needed to ensure that spurious sensor and GLAMR data are excluded are described. Results are given from the sensitivity study related to GLAMR spectral sampling and signal-to-noise ratio (SNR) effects, sensor integration time, and frame averaging of the imaging spectrometer data. The study shows that the 6 nm bandwidth sensor simulation requires a 1 nm spectral sampling of the GLAMR source with a radiance level that provides an in-band peak SNR > 200 to ensure that climate quality accuracies can be achieved. The results are also used to refine the test plan for the independent calibration for the CLARREO Pathfinder sensor calibration to optimize test time while meeting the required accuracy levels.

Intercomparison of Real and Simulated GEDI Observations across Sclerophyll Forests

Forest structure is an important variable in ecology, fire behaviour, and carbon management. New spaceborne lidar sensors, such as the Global Ecosystem Dynamics Investigation (GEDI), enable forest structure to be mapped at a global scale. Virtual GEDI-like observations can be derived from airborne laser scanning (ALS) data for given locations using the GEDI simulator, which was a tool initially developed for GEDI’s pre-launch calibration. This study compares the relative height (RH) and ground elevation metrics of real and simulated GEDI observations against ALS-derived benchmarks in southeast Australia. A total of 15,616 footprint locations were examined, covering a large range of forest types and topographic conditions. The impacts of canopy cover and height, terrain slope, and ALS point cloud density were assessed. The results indicate that the simulator produces more accurate canopy height (RH95) metrics (RMSE: 4.2 m, Bias: −1.3 m) than the actual GEDI sensor (RMSE: 9.6 m, Bias: −1.6 m). Similarly, the simulator outperforms GEDI in ground detection accuracy. In contrast to other studies, which favour the Gaussian algorithm for ground detection, we found that the Maximum algorithm performed better in most settings. Despite the determined differences between real and simulated GEDI observations, this study indicates the compatibility of both data sources, which may enable their combined use in multitemporal forest structure monitoring.

Vicarious Calibration of the Long Near Infrared Band: Cross-Sensor Differences in Sensitivity

Numerous assumptions and approximations are employed when translating satellite-derived radiance to surface remote sensing reflectance (<i>R_RS</i>) for ocean color applications. Among these is the vicarious calibration coefficient (<i>g</i>) of the &#x2018;long&#x2019; near infrared band (NIR_L) used for atmospheric correction. For this band, the pre-launch calibration has always been deemed sufficient [thus g(NIR_L) = 1.00] as long as other bands are vicariously calibrated. Recent research, however, suggests that MODIS/Aqua <i>R_RS</i> time series are quite sensitive to g(NIR_L) (and associated vicarious gains in other bands). In this work, we assessed the sensitivity of VIIRS/SNPP <i>R_RS</i> to NIR_L calibration, and compared our results to previous MODIS/Aqua and SeaWiFS/OrbView2 analysis. In doing so, we note <i>g</i>(NIR_L) sensitivities of mission-averaged <i>R_RS</i> timeseries are lower for VIIRS and SeaWiFS, relative to MODIS. At the scale of monthly climatologies, however, all sensors show prominent <i>g</i>(NIR_L) sensitivity, with that of SeaWiFS being the most substantial. These findings informed simulation analyses, whereby we identified signal-to-noise ratio (SNR) and radiant path geometry, as well as their interaction, as having notable impacts on <i>g</i>(NIR_L) sensitivity. As such, <i>g</i>(NIR_L) sensitivity is a necessary consideration for reflectance uncertainty budgets, especially for sensors with higher NIR SNR or particular prevailing radiant path geometries. Given the geometry components embedded within g(NIR_L) sensitivity, such studies should be coupled with cross-sensor intercalibrations (e.g., using simultaneous same view measurements) toward minimizing NIR_L errors between satellite instruments, but such efforts will not completely remediate remaining cross-sensor biases in <i>R_RS</i>.

Landsat 9 Thermal Infrared Sensor 2 On-Orbit Calibration and Initial Performance

The Thermal Infrared Sensor 2 (TIRS-2) on Landsat 9 launched September 27, 2021 and underwent a variety of tests during its commissioning phase to establish its postlaunch performance. We report on the calibration updates performed to maintain its calibration and generate high quality imagery. This is done by transferring the SI-traceable pre-launch calibration to on-orbit while accounting for changes in the TIRS-2 response as detected through on-board calibrator observations. Additional empirical corrections were implemented to mitigate image striping observed on-orbit. The detector arrays were monitored through its commissioning phase to ensure that stable detectors were chosen for operations. TIRS-2 has demonstrated &#x007E;0.025% instability over its orbit, &#x007E;80 mK noise equivalent delta temperature, and an absolute radiometric uncertainty &#x003C;1.4% in its nominal temperature range enabling a wide array of Earth science applications.

ATMS Radiance Data Products’ Calibration and Evaluation

The Advanced Technology Microwave Sounder (ATMS) is a passive microwave radiometer for the current generation of polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA). The first two ATMS instruments are manifested onboard the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites. Several critical changes have been made to ATMS operational calibration algorithm since March 2017. The calibration processing has been revised from a Rayleigh–Jeans approximated algorithm to a full radiance algorithm in order to reduce the error introduced by the approximation over cold radiances in the higher frequency channels. In addition, based on the lessons learned from S-NPP and NOAA-20 postlaunch calibration/validation tests, some major improvements have been made in the updated operational algorithm. These include reflector emission and antenna pattern corrections. Details of the radiance-based ATMS on-orbit calibration are documented in this report, and results of prelaunch calibration error budget analysis and postlaunch calibration accuracy evaluation are also presented for reference.

Chandrayaan-2 Large Area Soft X-ray Spectrometer (CLASS): Calibration, In-flight performance and first results

The Chandrayaan-2 Large Area Soft X-ray Spectrometer (CLASS) onboard the Chandraayaan-2 spacecraft around the Moon, has been remotely measuring the lunar X-ray fluorescence spectra since September, 2019. The primary objective of the experiment is to provide global maps of O, Mg, Al, Si at a resolution of 12.5 km/pix and of Ca, Ti and Fe at localized regions during enhanced solar activity, using the lunar X-ray fluorescence measurements in the 0.5 to 10 KeV range. CLASS is an array of swept charge devices (SCDs), a variant of X ray Charge Coupled Devices (CCDs) that provide good spectral resolution and large area. The quality of X-ray measurements strongly depends on accuracy of its calibration techniques. In this work, the results from the pre-launch calibration of the instrument that combines experimental measurements and simulations are described. The spectral redistribution function of the swept charge device is simulated using an augmented version of a previously developed charge transport model (Athiray et al., 2015). Response matrices built from these models are verified with in-flight data. We study the background in SCDs arising from particles in the lunar orbit over many months and identify the sources. We demonstrate the in-flight performance of the instrument that enables generation of direct elemental maps. Elemental abundances for a region in the farside highland and in the nearside western mare are derived demonstrating the method and the instrument capability of deriving the elemental abundances at different spatial scales and at different solar activity levels.

星载偏振扫描仪发射前定标及地面验证实验

星载偏振扫描仪发射前定标及地面验证实验

TEMPEST-D Radiometer: Instrument Description and Prelaunch Calibration

The Temporal Experiment for Storms and Tropical Systems Technology Demonstration (TEMPEST-D) instrument is a five-frequency millimeter-wave radiometer operating from 87 to 181 GHz. The cross-track scanning radiometer has been operating on a 6U CubeSat in low Earth orbit since September 5, 2018. The direct-detection architecture of the radiometer reduces its mass and power consumption by eliminating the need for a local oscillator and mixer, also reducing system complexity. The instrument includes a scanning reflector and ambient calibration target. The reflector rotates continuously to scan the antenna beams in the cross-track direction, first across the blackbody calibration target, then toward the Earth over the full range of incidence angles, and finally to cosmic microwave background radiation at 2.73 K. This enables precision end-to-end calibration of the millimeter-wave receivers during every 2-s scan period. The TEMPEST-D millimeter-wave radiometers are based on 35-nm indium phosphide (InP) high-electron-mobility transistor (HEMT) low-noise amplifiers. This article describes the instrument and its characterization prior to launch.

Calibrating Geosynchronous and Polar Orbiting Satellites: Sharing Best Practices

Earth remote sensing optical satellite systems are often divided into two categories—geosynchronous and sun-synchronous. Geosynchronous systems essentially rotate with the Earth and continuously observe the same region of the Earth. Sun-synchronous systems are generally in a polar orbit and view differing regions of the Earth at the same local time. Although similar in instrument design, there are enough differences in these two types of missions that often the calibration of the instruments can be substantially different. Thus, respective calibration teams develop independent methods and do not interact regularly or often. Yet, there are numerous areas of overlap and much to learn from one another. To address this issue, a panel of experts from both types of systems was convened to discover common areas of concern, areas where improvements can be made, and recommendations for the future. As a result of the panelist’s efforts, a set of eight recommendations were developed. Those that are related to improvements of current technologies include maintaining sun-synchronous orbits (not allowing orbital decay), standardization of spectral bandpasses, and expanded use of well-developed calibration techniques such as deep convective clouds, pseudo invariant calibration sites, and lunar methodologies. New techniques for expanded calibration capability include using geosynchronous instruments as transfer radiometers, continued development of ground-based prelaunch calibration technologies, expansion of RadCalNet, and development of space-based calibration radiometer systems.

Evaluating the Absolute Calibration Accuracy and Stability of AIRS Using the CMC SST

We compare the daily mean and standard deviation of the difference between the sea surface skin temperature (SST) derived from clear sky Atmospheric InfraRed Sounder (AIRS) data from seven atmospheric window channels between 2002 and 2020 and collocated Canadian Meteorological Centre (CMC) SST data from the tropical oceans. After correcting the mean difference for cloud contamination and diurnal effects, the remaining bias relative to the CMC SST, is reasonably consistent with estimates of the AIRS absolute accuracy based on the uncertainty of the pre-launch calibration. The time series of the bias produces trends well below the 10 mK/yr level required for climate change evaluations. The trends are in the 2 mK/yr range for the five window channels between 790 and 1231 cm−1, and +5 mK/yr for the shortwave channels. Between 2002 and 2020, the time series of the standard deviation of the difference between the AIRS SST and the CMC SST dropped fairly steadily to below 0.4 K in several AIRS window channels, a level previously only seen in gridded SST products relative to the Argo buoys.

Sentinel-3A/B SLSTR Pre-Launch Calibration of the Thermal InfraRed Channels

The first two models of the Sea and Land Surface Temperature Radiometers (SLSTR) for the European Copernicus Sentinel-3 missions were tested prior to launch at the Rutherford Appleton Laboratory space instrument calibration facility. The pre-launch tests provide an essential reference that ensures that the flight data of SLSTR are calibrated to the same standards needed for surface temperature measurements and to those used by shipborne radiometers for Fiducial Reference Measurement (FRM). The radiometric calibrations of the thermal infrared channels were validated against accurate and traceable reference BB sources under flight representative thermal vacuum environment. Measurements were performed in both earth views for source temperatures covering the main operating range, for different instrument configurations and for the full field-of-view of the instruments. The data were used to derive non-linearity curves to be used in the level-1 processing. All results showed that the measured brightness temperatures and radiometric noise agreed within the requirements for the mission. An inconsistency that particularly affected SLSTR-A was observed which has been attributed to an internal stray light error. A correction for the stray light has been proposed to reduce the error. The internal stray light error was reduced for SLSTR-B by replacing the coating on the main aperture stop. We present a description of the test methodology and the key results.

Radiometric Calibration and Uncertainty Analysis of KOMPSAT-3A Using the Reflectance-Based Method.

In recent years, Korea has sustained consistent access to remote sensed data by launching Korea Multi-Purpose Satellite-3A (KOMPSAT-3A, K3A)—an updated version of the high-resolution KOMPSAT series. This KOMPSAT-3A required calibration and validation (Cal/Val) before and after its launch to enable proper functional characterization and to maintain the veracity of data collected. The Korea Aerospace Research Institute (KARI) executed the initial prelaunch calibration in the laboratory and we performed the Cal/Val of KOMPSAT-3A during the Launch and Early Operation Phase (LEOP) in the field. Two suitable sites in Korea and Mongolia with stable weather, almost uniform terrain, and near Lambertian diffusion, provided the necessary tarp reflectance to calculate the absolute radiometric calibration coefficients. The surface reflectance was determined using 12 and four well-calibrated reference reflectance tarps employing the FieldSpec® 3(Analytical Spectral Devices Inc., Boulder, CO, USA) Spectroradiometer. Subsequently, the top of atmosphere (TOA) radiance was estimated using radiative transfer code (RTC) software based on the Atmospheric and Topographic Correction (ATCOR). In addition, cross calibration was simultaneously performed at the Libya-4 pseudo invariant calibration site (PICS) for KOMPSAT-3A TOA radiance, using the spectral band adjustment factor (SBAF) compensated Landsat 8 reflectance and the Second Simulation of Satellite Signal in the Solar Spectrum (6S) to compute cross calibration coefficients. The results of the KOMPSAT-3A absolute calibration coefficient show that the R2 values were over 0.99, implying a significant correlation for almost all bands between the TOA radiance and the KOMPSAT-3A spectral band response at both campaign sites. However, this study reveals a difference of less than 5% calibration gains for all bands compared to the prelaunch values, while the cross calibration gain is below 5% in visible bands and above 5% in the near infrared band. An effort to optimize the reliability of the absolute calibration coefficients resorted to the rigorous quantification of uncertainties amongst atmospheric conditions, the digital number (DN), the reflectance tarp, the bidirectional reflectance distribution function (BRDF), and ozone levels. Therefore, we presumed that the total uncertainty was 4.27%, which conforms to some published results.

Radiometric Cross-Calibration of GF-4/VNIR Sensor With Landsat8/OLI, Sentinel-2/MSI, and Terra/MODIS for Monitoring Its Degradation

Optical satellite sensor generally suffers from drifts and biases relative to their prelaunch calibration, caused by launch and the space environment. Radiometric cross-calibration is valuable for calibrating sensors without coincident surface measurements through transferring radiometric values between satellite sensors via a stable target. The data quality of visible and near-infrared (VNIR) sensor onboard Gaofen-4 (GF-4) satellite seriously depends on vicarious calibration, which is performed once every year, thus, a cross-calibration approach is proposed for monitoring its radiometric performance much more frequently. In this study, the GF-4/VNIR is cross-calibrated by Landsat8/OLI, Sentinel-2/MSI, and Terra/MODIS with the aid of the tandem scenes during 2017 and 2018 after correcting the discrepancy on viewing geometries and spectrum. The results show that there is test site dependency and sensor dependency, and cross-calibration coefficients in the four bands roughly have similar variation trend as a sinusoidal function during 2017 and 2018, varying from 0.00023 to 0.00079. Furthermore, uncertainty analysis of the cross-calibration is carried out to analyze the uncertainty contributions affecting the cross-calibration accuracy. Note that the calibration accuracy of referenced sensors, the uncertainty of the MODTRAN model, BRDF uncertainty are the three main factors affecting the cross-calibration accuracy, the total uncertainty is approximately 3.9%–6.64%.

A Novel Framework to Harmonise Satellite Data Series for Climate Applications

Fundamental and thematic climate data records derived from satellite observations provide unique information for climate monitoring and research. Since any satellite only operates over a relatively short period of time, creating a climate data record also requires the combination of space-borne measurements from a series of several (often similar) satellite sensors. Simply combining calibrated measurements from several sensors can, however, produce an inconsistent climate data record. This is particularly true of older, historic sensors whose behaviour in space was often different from their behaviour during pre-launch calibration and more scientific value can be derived from considering the series of historical and present satellites as a whole. Here, we consider harmonisation as a process that obtains new calibration coefficients for revised sensor calibration models by comparing calibrated measurements over appropriate satellite-to-satellite matchups, such as simultaneous nadir overpasses and which reconciles the calibration of different sensors given their estimated spectral response function differences. We present the concept of a framework that establishes calibration coefficients and their uncertainty and error covariance for an arbitrary number of sensors in a metrologically-rigorous manner. We describe harmonisation and its mathematical formulation as an inverse problem that is extremely challenging when some hundreds of millions of matchups are involved and the errors of fundamental sensor measurements are correlated. We solve the harmonisation problem as marginalised errors in variables regression. The algorithm involves computation of first and second-order partial derivatives using Algorithmic Differentiation. Finally, we present re-calibrated radiances from a series of nine Advanced Very High Resolution Radiometer sensors showing that the new time series has smaller matchup differences compared to the unharmonised case while being consistent with uncertainty statistics.

Performance Analysis of Microwave Humidity and Temperature Sounder Onboard the FY-3D Satellite From Prelaunch Multiangle Calibration Data in Thermal/Vacuum Test

A newly designed thermal/vacuum (T/V) prelaunch multiangle calibration test is proposed for Microwave Humidity and Temperature Sounder (MWHTS) onboard the Feng Yun 3D satellite. Compared with other existing prelaunch calibration tests designed at fix scan angle, this test is first proposed to analyze the measurements of MWHTS from multiscan angles. A set of comprehensive calibration method is established and used for calibration data processing. The high-quality data preprocessing methods are performed. Essential calibration coefficients such as cold bias, hot bias, and nonlinearity coefficients, and calibration results such as calibration residual error, sensitivity, and calibration accuracy of MWHTS are all obtained and analyzed in MWHTS’s six observing positions. The measured sensitivity value of channel 2 is 1.5 K while the measured sensitivities of the others range from 0.18 to 0.57 K. The calibration accuracy of channel 2 is 1.5 K while the calibration accuracies of the others range from 0.32 to 0.7 K. According to the discrepancy of multiangle calibration test results, the radiation leakage and the response lag for special channels are discovered for the first time in T/V test, and the reasons of these two special phenomena are fully analyzed. Moreover, the measurements of the T/V test with fast changing instrument temperatures are analyzed and the applicability of nonlinearity coefficients obtained in T/V test for in-orbit calibration is verified. In conclusion, MWHTS meets the basic design requirements of sensitivity and calibration accuracy, the changing of the MWHTS observing positions does not impact the calibration coefficients and results, and the nonlinearity coefficients obtained in T/V test are valid when instrument temperature experiences some fast changing.

The GEDI Simulator: A Large-Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions.

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar mission which will produce near global (51.6°S to 51.6°N) maps of forest structure and above‐ground biomass density during its 2‐year mission. GEDI uses a waveform simulator for calibration of algorithms and assessing mission accuracy. This paper implements a waveform simulator, using the method proposed in Blair and Hofton (1999; https://doi.org/10.1029/1999GL010484), and builds upon that work by adding instrument noise and by validating simulated waveforms across a range of forest types, airborne laser scanning (ALS) instruments, and survey configurations. The simulator was validated by comparing waveform metrics derived from simulated waveforms against those derived from observed large‐footprint, full‐waveform lidar data from NASA's airborne Land, Vegetation, and Ice Sensor (LVIS). The simulator was found to produce waveform metrics with a mean bias of less than 0.22 m and a root‐mean‐square error of less than 5.7 m, as long as the ALS data had sufficient pulse density. The minimum pulse density required depended upon the instrument. Measurement errors due to instrument noise predicted by the simulator were within 1.5 m of those from observed waveforms and 70–85% of variance in measurement error was explained. Changing the ALS survey configuration had no significant impact on simulated metrics, suggesting that the ALS pulse density is a sufficient metric of simulator accuracy across the range of conditions and instruments tested. These results give confidence in the use of the simulator for the pre‐launch calibration and performance assessment of the GEDI mission.

Pre-launch calibration results of the TROPOMI payload on-board the Sentinel-5 Precursor satellite

Abstract. The Sentinel-5 Precursor satellite was successfully launched on 13 October 2017, carrying the Tropospheric Monitoring Instrument (TROPOMI) as its single payload. TROPOMI is the next-generation atmospheric sounding instrument, continuing the successes of GOME, SCIAMACHY, OMI, and OMPS, with higher spatial resolution, improved sensitivity, and extended wavelength range. The instrument contains four spectrometers, divided over two modules sharing a common telescope, measuring the ultraviolet, visible, near-infrared, and shortwave infrared reflectance of the Earth. The imaging system enables daily global coverage using a push-broom configuration, with a spatial resolution as low as 7×3.5 km2 in nadir from a Sun-synchronous orbit at 824 km and an Equator crossing time of 13:30 local solar time. This article reports the pre-launch calibration status of the TROPOMI payload as derived from the on-ground calibration effort. Stringent requirements are imposed on the quality of on-ground calibration in order to match the high sensitivity of the instrument. A new methodology has been employed during the analysis of the obtained calibration measurements to ensure the consistency and validity of the calibration. This was achieved by using the production-grade Level 0 to 1b data processor in a closed-loop validation set-up. Using this approach the consistency between the calibration and the L1b product, as well as confidence in the obtained calibration result, could be established. This article introduces this novel calibration approach and describes all relevant calibrated instrument properties as they were derived before launch of the mission. For most of the relevant properties compliance with the calibration requirements could be established, including the knowledge of the instrument spectral and spatial response functions. Partial compliance was established for the straylight correction; especially the out-of-spectral-band correction for the near-infrared channel needs future validation. The absolute radiometric calibration of the radiance and irradiance responsivity is compliant with the high-level mission requirements, but not with the stricter calibration requirements as the available on-ground validation shows. The relative radiometric calibration of the Sun port was non-compliant. The non-compliant subjects will be addressed during the in-flight commissioning phase in the first 6 months following launch.