Post-launch calibration and validation over the lifetime of missions is needed to ensure that any long-term variation in an observation, e.g. an area getting hotter, can be unambiguously assigned to a change in the Earth system, rather than a change in calibration. Such activities enable measurements from different satellites to be inter-compared and used seamlessly to create long-term multi-instrument/multi-platform data records, which serve as the basis for large-scale international science investigations into topics with high societal or environmental importance. In order to help address this need we have established a set of automated validation sites where the necessary measurements for validating mid and thermal infrared data from spaceborne and airborne sensors are made every few minutes on a continuous basis. We have also conducted multi-agency airborne campaigns with thermal infrared sensors to develop precursor datasets for future NASA and ESA missions to acquire mid and thermal infrared data as well as characterize variability within the automated validation sties.

We have established automated validation sites at several locations including Lake Tahoe CA/NV, Salton Sea CA and La Crau, France. The Lake Tahoe site was established in 1999, the Salton Sea site was established in 2008 and the La Crau site was established in 2023. Each site has one or more custom-built highly accurate (50mK) radiometers measuring the surface skin temperature. All the measurements are made every few minutes and downloaded hourly via a cellular modem.

Data from the sites have been used to validate numerous satellite instruments including the Advanced Very High Resolution Radiometer (AVHRR) series, the Along Track Scanning Radiometer (ATSR) series, the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), the Landsat series, the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, the Visible Infrared Imaging Radiometer Suite (VIIRS) and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). In all cases the standard products have been validated including the standard radiance at sensor, radiance at surface, surface temperature and surface emissivity products.

Over the last several years NASA and ESA have conducted multiple joint airborne campaigns to obtain data at high spatial and spectral resolutions to simulate future satellite sensors as well as characterize potential validation sites, such as the La Crau validation site. These data are currently being used to simulate the ASI/NASA Surface Biology and Geology (SBG) thermal infrared (TIR) mission, the ESA Land Surface Temperature Monitoring (LSTM) mission and the ISRO/CNES Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment (TRISHNA) mission.

We will present results from the validation of the mid and thermal infrared data using the automated validation sites as well as results from the recent airborne campaigns.

How to cite: Hook, S., Eng, B., Rivera, G., Freepartner, R., Hatch, B., Johnson, W., Schüttemeyer, D., Langsdale, M., and Wooster, M.: Validation and simulation of existing and future satellite mid and thermal infrared sensors using a combination of automated validation sites and airborne datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6849, https://doi.org/10.5194/egusphere-egu24-6849, 2024.

Viewing and illumination geometry are known to have significant impacts on remotely sensed retrieval of land surface temperature (LST), particularly for heterogeneous regions with mixed components. Disregarding directional effects can have significant impacts on both the stability and accuracy of satellite datasets, for example when harmonising datasets from different sensors with different viewing geometries. However, it is difficult to accurately quantify these impacts, in part due to the challenges of retrieving high-quality data for the different components in a scene at a variety of different viewing and illumination geometries over a time period where the real surface temperature and sun-sensor geometries are invariant. With LST an Essential Climate Variable and the development of high resolution future thermal infrared missions (e.g. LSTM, SBG, TRISHNA), it is essential that further work is done to redress this.

With this in mind, a joint NASA-ESA airborne campaign focused on directionality was conducted in Italy in the summer of 2023, led by the National Centre for Earth Observation at King’s College London. This campaign involved concurrent acquisition across longwave infrared (LWIR) wavelengths at both nadir and off-nadir viewing angles through the deployment of two aircraft flying simultaneously, each equipped with state-of-the-art LWIR hyperspectral instrumentation. Data was collected to enable simulation of angular effects at the satellite scale over both agricultural and urban surfaces, with the aim of understanding and potentially developing adjustments for wide view angle satellite-based LST retrievals and remotely sensed evapotranspiration estimates. In-situ observations were collected additionally to enable accuracy assessment of the airborne datasets.

This presentation first details the airborne campaign, including the unique and novel data collection strategies and design modifications to enable evaluation of directional effects for thermal satellites. Preliminary results from the campaign are then presented as well as plans for further analysis related to future satellite thermal missions. 

How to cite: Langsdale, M., Wooster, M., Schuettemeyer, D., Hook, S., Middleton, C., Grosvenor, M., Eng, B., Colombo, R., Miglietta, F., Genesio, L., Sobrino, J., Rivera, G., Beeden, D., and Jay, W.: Multi-angular airborne observations for simulating thermal directionality at the satellite scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11905, https://doi.org/10.5194/egusphere-egu24-11905, 2024.

Atmospheric Correction Inter-comparison eXercise (ACIX) was initiated in 2016 in the frame of the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV) and it is co-organised by ESA and NASA. The aim of ACIX is to compare the state-of-the-art atmospheric correction (AC) processors. ACIX is a voluntary and open-access initiative to which every AC processor’s developer is invited to participate. In the current third edition, ACIX-III Land, the focus is on imaging spectrometer data, also called hyperspectral data. Data from two spectrometers in orbit (PRISMA and EnMAP) will be used in a suite of test sites. These sites were selected based on the availability of ground-based measurements and flight campaign data with coincident acquisitions, i.e., RadCalNet and CHIME-AVIRIS-NG campaigns.

 The ACIX-III Land exercise will intercompare the performances of several AC software suits capable of retrieving Surface Reflectance (SR), Water Vapour (WV) and Aerosols Optical Depth (AOD). The original datasets along with the participant results will be catalogued, intercompared, and analysed within the Copernicus Expansion Mission - Product Algorithm Laboratory (CEM-PAL). The CEM-PAL is a virtual environment aiming to facilitate efficient prototyping of algorithms used to generate and test Expansion Missions Level-2 products, including algorithm modification, hosted processing, qualification functionalities and scientific validation environment. Once the ACIX-III results are published, the dataset will be repurposed to initially support the CHIME L2 developments with plans to extent the support to other missions (e.g., SBG, LSTM).

This contribution will present the ACIX-III Land, and CEM-PAL initiatives, highlighting the main implementation points, latest status, and future developments to support related Cal/Val activities.

How to cite: Alonso, K., Cremer, N., Boccia, V., Brodrick, P. G., Chlus, A., Doxani, G., Gascon, F., Niemeijer, S., Thompson, D. R., Townsend, P., and Ulahannan, N.: Integration of ACIX-III Land Atmospheric Correction Inter-comparison eXercise within the Copernicus Expansion Mission Product Algorithm Laboratory to Support Surface Reflectance Cal/Val, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20397, https://doi.org/10.5194/egusphere-egu24-20397, 2024.

GBOV (Copernicus Ground-Based Observation for Validation), is an element of CLMS (Copernicus Land Monitoring Service). Its initial purpose was to support yearly validation effort of core CLMS product (TOC-R, Albedo, LAI, FAPAR, FCOVER, SSM and LST), five of whom are listed among GCOS Essential Climate Variables (ECV). GBOV has however reached a much larger community with about 1200 users, including ESA optical MPC. There is a large variety of ground data publicly available through numerous networks including ICOS, BSRN, NEON, TERN, SurfRad … For GBOV service, the choice was made to focus on data from permanent deployment, i.e. long-term datasets, rather than field campaign data. Indeed, this reduces the number of available ground variables, but long-term deployments ensure the maximum of ground to satellite data matchups as well as measurement protocols consistency.

GBOV provides ground measurement (the so-called “Reference Measurements”) to the community, but its fundamental interest is that up-scaling procedures are applied to these ground measurements in order to provide ARVD (Analysis Ready Validation Data) to the community, the so-called “Land Products”. GBOV service is freely accessible on https://land.copernicus.eu/global/gbov and provides data over 112 sites. Available ground data variables include: Top of Canopy Reflectance (ToC-R), surface albedo, Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Available Radiation (FAPAR), Fraction of Covered ground (FCover), Surface Soil Moisture (SSM) and Land Surface Temperature (LST).

The networks providing GBOV initial input data are unfortunately not evenly distributed. In an attempt to reduce the thematic and geographical gap, GBOV is developing its own network as part of collaboration with the existing networks. In GOBV phase 1, six ground stations have been upgraded with additional instrumentation. In GBOV phase 2, a ground station has been deployed in August 2023 on Fuji Hokuroku research station in Japan for vegetation variables monitoring. This is part of a collaboration with NIES (National Institute of Environmental Studies). In 2024, a vegetation station will be installed over Fontainebleau research station (France) as part of a GBOV/ICOS collaboration. Fuji Hokuroku and Litchfield (TERN network Australia) will receive a GBOV LST station in 2024.

Over the past year, several updates have been implemented in GBOV database to better respond to CLMS and general users requirements. This includes improved uncertainty estimates for vegetation products, improved procedure for Soil Moisture and LST products. More effort is being made for the end-to-end uncertainty budget computation.

This presentation will emphasis product status and recent product evolutions.

How to cite: Lerebourg, C., Grousset, R., Vidal, T., Bai, G., Clerici, M., Gobron, N., Dash, J., Bar, S., James, F., Brown, L., Lopez-baeza, E., Perez-hoyos, A., Ghent, D., Anand, J., Muller, J.-P., and Song, R.: GBOV (Copernicus Ground-Based Observation for Validation) service: latest product updates and evolutions for EO data Cal/Val, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10447, https://doi.org/10.5194/egusphere-egu24-10447, 2024.

For Landsat 8 and Landsat 9 (L8 and L9), the radiometric stability of the Operational Land Imager (OLI) is monitored using two solar diffusers, three sets of stimulation lamps, and regular lunar collects. Consistent response to the multiple calibrators provides high confidence in the radiometric characterization of the imagers over time and calibration parameters needed to maintain the stability of image products. After 11 years on orbit, all spectral bands in Landsat 8 OLI are stable within 1.5%, while Landsat 9 OLI degradation over its 2.5 years of life remains within 0.3% across all bands.

The MultiSpectral Instruments (MSIs) onboard Sentinel 2A and 2B (S2A and S2B) satellites were designed with 8 similar spectral bands (out of 13) as the OLIs, which created opportunities to combine data from both types of instruments and obtain higher temporal frequency of Earth observations. To ensure proper interoperability among the different instruments, they need to be radiometrically cross-calibrated and consistently georeferenced. We use coincident acquisitions over Pseudo Invariant Calibration Sites (PICS) to monitor the radiometric calibration consistency and stability of the instruments over time. For geometry, Landsat and Sentinel 2 images acquired within a month of each other over the same ground targets were used to assess the co-registration accuracy between the sensor products.

Our results show a general agreement in radiometry of all four instruments over their lifetimes to within 1%. Following the launch of MSI instruments, the initial geometric co-registration assessment between the MSI instruments and the Landsat 8 OLI instrument showed more than 12 m Circular Error (CE90), larger than a Sentinel 2, 10m, pixel. To further improve co-registration and, thus, interoperability of the four instruments, Landsat Collection-2 products use a geometric reference that was harmonized using the Global Reference Image (GRI). The GRI is a dataset consisting of geometrically refined Sentinel 2 images with an absolute accuracy better than 6 m globally. After adopting a common geometric reference in the generation of Landsat and Sentinel 2 products, our assessment of geometric co-registration of the Landsat and Sentinel terrain-corrected products shows a CE90 error of less than 6 m.

Multiple efforts have also been made to validate the accuracy of surface reflectance products from both Landsat and Sentinel 2. In-situ measurements have been made during overpasses of L8, L9, S2A, and S2B using various methods. These measurements also show consistency between all the sensors and can also be used for other missions.

How to cite: Micijevic, E., Anderson, C., Barsi, J., Rengarajan, R., Haque, MD. O., and Mann, J.: Intercomparison of Landsat OLI and Sentinel 2 MSI performance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13262, https://doi.org/10.5194/egusphere-egu24-13262, 2024.

Tropical forests are of great ecological and climatological importance. Although they only cover about 6% of Earth’s surface, they are home to approx. 50% of the world’s animal and plant species. Their trees store 50% more carbon than trees outside the tropics. At the same time, they are one of the most endangered ecosystems on Earth: about 6 million of hectares per year are felled for timber or cleared for farming. Compared to the other components of the carbon cycle (i.e. the ocean as a sink and the burning of fossil fuels as a source), the uncertainties in the local land carbon stocks and the carbon fluxes are particularly large. This is especially true for tropical forests: more than 98% of the carbon flux generated by changes in land-use may be due to tropical deforestation, which converts carbon stored as biomass into emissions.

In this context, the AfriSAR 2015/16 campaign, supported by ESA, was carried out over four forest sites in Gabon by ONERA (July 2015) during the dry season and by DLR (February 2016) during the wet season. From the data collected the innovative techniques applied to estimate forest height and biomass could be improved significantly and are summarized in a special issue ‘Forest Structure Estimation in Remote Sensing’ of IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

The motivation of the AfriSAR campaign was to acquire demonstration data for the soon to be launched ESA BIOMASS mission, that was selected as the 7th Earth Explorer mission in May 2013 in order to meet the pressing need for information on tropical carbon sinks and sources by providing estimates of forest height and biomass. AfriSAR focused on African tropical and savannah forest types (with biomass in the 100-300 t/ha range) and complements previous ESA campaigns over Indonesian and Amazonian forest types in 2004 (INDREX-II) and 2009 (TropiSAR).

The present contribution concerns the GABONX campaign, the ESA supported successor to AfriSAR, which took place in May to July 2023. GABONX aims to detect and quantify changes that have occurred since the DLR acquisitions in February 2016. To this end, DLR’s F-SAR sensor acquired interferometric stacks of fully polarimetric L- and P-Band data over the same forest sites in the same flight geometry as in 2016. The results presented give an overview of campaign activities with particular emphasis on the calibration of the SAR instrument as well as the validation of forest parameters derived from polarimetric interferometry. The SAR sensor calibration is based on an innovative approach that leverages state-of-the-art EM simulation to accurately characterize the 5m trihedral reference target deployed for the campaign in Gabon. The validation of derived forest parameters uses lidar measurements obtained in the time frame of the GABONX campaign by NASA’s LVIS sensor. As an outlook, further collaborative calibration and validation activities will hopefully include the cross-calibration of DLR’s F-SAR and NASA’s UAVSAR, which is set to acquire L- and P-Band data over the GABONX sites in 2024.

How to cite: Jaeger, M., Hajnsek, I., Pardini, M., Guliaev, R., Papathanassiou, K., Limbach, M., Keller, M., Reigber, A., Fatoyinbo, T., Simard, M., Hofton, M., Blair, B., Dubayah, R., Mambimba Ndjoungui, A., Mengue, L., Vianney Mpiga Assele, U., and Casal, T.: Calibration and Validation Activities in the Context of the 2023 GABONX Airborne SAR Campaign for Tropical Forest Height and Change Analysis over Gabon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10864, https://doi.org/10.5194/egusphere-egu24-10864, 2024.

Since more than 10 years, CryoSat-2 (CS2) has observed and monitored the Arctic Ocean, providing unprecedented spatial and temporal coverage. Satellite altimetry enables to measure sea ice thickness, one essential variable to understand the sea ice dynamics. Numerous sea-ice products developed by the community showed the skills of CS2 to retrieve sea-ice thickness. Nevertheless, several questions remain to better quantify the quality of the measurements. One of them is to better assess the snow depth, a key parameter to obtain the sea ice thickness. In 2018, ICESat-2 mission was launched carrying a LIDAR altimeter. We took advantage of the difference of penetration in the snow layer of laser and Ku-Band altimetry to compute a snow depth product covering the ICESat-2 period. This product is then validated and compared to in situ datasets, reanalysis, models and other snow depth products from satellite missions such as SARAL. Results are quite good concerning the comparison to in situ datasets giving us confidence in the product reliability. In July 2020, the orbit of CryoSat-2 was raised, as part of the CRYO2ICE project, to coincide in space and time to tracks from NASA high resolution altimeter ICESat-2 over the Arctic ocean. This is a unique opportunity to benefit from along-track colocalised data. We present here a methodology to compare ICESat-2 and CryoSat-2 along coincident tracks and compare the resulting snow depth product to gridded products. The lack of in situ measurements is one of the main limitations to analyze the along-track product contribution. Finally we focus on the advantages of combining laser and Ku-band altimetry to lower the uncertainties. The snow depth uncertainties of our product are about 6 cm on average. This ESA-supported study should help prepare the Copernicus CRISTAL mission, which will include a Ka/Ku dual-frequency altimeter for the first time.

How to cite: Carret, A., Fleury, S., Di Bella, A., Landy, J., Lawrence, I., Laforge, A., Kurtz, N., and Garnier, F.: A multi frequency altimetry snow depth product over the Arctic sea ice, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15804, https://doi.org/10.5194/egusphere-egu24-15804, 2024.

Snow and ice albedo plays a fundamental role in climate change amplification. Its importance is by modulating absorbed sunlight; the largest average melt energy source. Further, the presence or lack of light absorbing impurities including living matter and meltwater effects can strongly influence snow and ice heating rates. Through multiple consecutive satellite missions, cryosphere albedo has been mapped globally and continuously for more than four decades now.
This work examines a 42 year record of cryosphere albedo by joining the satellite climate records of snow and ice albedo from AVHRR 1982 to present, NASA MODIS 1999 to present, and EU Copernicus Sentinel-3 2017 to present. The long-term stability of the climate records is examined using independent field data from Greenland and Antarctica. Additionally, the work presents long term trends in snow and ice albedo in relation to the competing effects of surface melting, snowfall and rainfall.

How to cite: Box, J., Bahbah, R., Ahlstrøm, A., Wehrlé, A., Kokhanovsky, A., Picard, G., and Arnaud, L.: Four decades of cryosphere albedo from spaceborne observations - assessment with field data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19307, https://doi.org/10.5194/egusphere-egu24-19307, 2024.

The National Aeronautical and Space Administration (NASA) Salinity and Stratification at the Sea Ice Edge (SASSIE) field campaign took place in the Arctic Ocean between August and October of 2022. The scientific aim is to understand the relationship between both haline and thermal stratification and sea-ice advance, and to test the hypothesis that a significant fresh layer at the surface can accelerate the formation of sea ice by limiting convective processes. With the advent of satellite-derived sea surface salinity (SSS) observations from SMOS, Aquarius/SAC-D, and SMAP in the last decade, such observations could provide insights into sea ice formation rates and extent. With the sensitivity of L-Band radiometry for SSS being low at the temperatures prevalent in the Arctic Ocean (-2°C – 5°C) and additional problems with sea ice contamination in the satellite footprint, careful calibration and validation is needed to determine the quality of satellite-derived SSS in this region, particularly near the ice-edge.

Here, we present three components that have resulted from this NASA Field Campaign.

1.) An overview of data gathered is presented, including an unprecedented density of near-surface salinity measurements from diverse platforms. These were measured during a one-month shipboard hydrographic and atmospheric survey in the Beaufort Sea and include continuous observations at radiometric depth (1-2cm) from the salinity snake instrument, more than 3000 high-resolution uCTD profiles, and air-sea flux measurements. Concurrent with the shipborne observations, an airborne campaign to observe ocean salinity, temperature, and other parameters from a low-flying aircraft was performed. Finally, we discuss the deployment and results of autonomous assets, buoys, and floats that were able to observe both the melt season and the sea ice advance. We combine these in situ observations with satellite SSS data to examine the effects of stratification on ocean dynamics in the Beaufort Sea near the sea ice edge and discuss the quality of SSS data in this region.

2.) NASA Physical Oceanography Programs has affirmed its commitment to Open Science and reproducibility of results. For the SASSIE field campaign, we have created a unique web portal that showcases the datasets gathered during the campaign, giving video overviews as well as written summaries of the available data and motivations for their collection. We have also created repositories that contain processing code used in the creation of these datasets, as well as example processing scripts in the form of Jupyter notebooks, which allow end users to execute a live download of datasets from NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) as well as processing and plotting these data in Python.

3.) We show the active integration of these tools into the salinity pilot mission exploitation platform (Salinity Pi-MEP), operated by the European Space Agency (ESR) in collaboration with NASA. We demonstrate how such an integration leverages access to other datasets, and facilitates calibration-validation efforts for Level-2 and Level-3 satellite data from multiple satellites. 

How to cite: Schanze, J., Gaube, P., Anderson, J., Bingham, F., Drushka, K., Guimbard, S., Lee, T., Reul, N., Sabia, R., and Westbrook, E. and the NASA Salinity and Stratification at the Sea Ice Edge Field Campaign Team: Sea Surface Salinity in the Arctic Ocean - Results from the NASA SASSIE Field Campaign, Calibration-Validation of Satellite Observations, and Data Outreach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14759, https://doi.org/10.5194/egusphere-egu24-14759, 2024.

The Pilot-Mission Exploitation Platform (Pi-MEP) for salinity (https://www.salinity-pimep.org/) is an initiative originally meant to support and widen the uptake of ESA Soil Moisture and Ocean Salinity (SMOS) mission data over the ocean. Since its beginning in 2017, the project aims at setting up a computational web-based platform focusing on satellite sea surface salinity data validation, supporting also process studies over the ocean. It has been designed in close collaboration with a dedicated science advisory group in order to achieve three main objectives: 1) gathering all the data required to exploit satellite sea surface salinity data, 2) systematically producing a wide range of metrics for comparing and monitoring sea surface salinity products’ quality, and 3) providing user-friendly tools to explore, visualize and exploit both the collected products and the results of the automated analyses. 

Over the years, the Pi-MEP has become a reference hub for the validation of satellite sea surface salinity missions products (SMOS, Aquarius, SMAP), being collocated with an extensive in situ database (e.g. Argo float, thermosalinographs, moorings, surface drifters, saildrones and equipped marine mammals) and additional thematic datasets (precipitation, evaporation, currents, sea level anomalies, sea surface temperature, etc. ). Co-localized databases between satellite products and in situ datasets are systematically generated together with validation analysis reports for 30 predefined regions. The data and reports are made fully accessible through the web interface of the platform. The datasets, validation metrics and tools of the platform are described in detail in Guimbard et al., 2021. Several dedicated scientific case studies involving satellite SSS data are also systematically investigated by the platform, such as major river plumes monitoring, mesoscale signatures in boundary currents, or spatio-temporal evolution in challenging regions (high latitudes, semi-enclosed seas, and the high-precipitation region of the eastern tropical Pacific).

Since 2019, a partnership to sustain the Salinity Pi-MEP project has been agreed between ESA and NASA, encompassing R&D and validation over the entire set of satellite salinity sensors. The two Agencies are now working together to widen the platform features on several technical aspects, such as triple-collocation software implementation, additional match-up collocation criteria and sustained exploitation of data from dedicated in-situ field campaigns (e.g., SPURS, EUREC4A).

In this talk, we will showcase the main results of the latest phase of the project, with the recent distinctive focus on the representation errors characterization of the various satellite salinity missions. 

Guimbard, S.; Reul, N.; Sabia, R.; Herlédan, S.; Khoury Hanna, Z.E.; Piollé, J.-F.; Paul, F.; Lee, T.; Schanze, J.J.; Bingham, F.M.; Le Vine, D.; Vinogradova-Shiffer, N.; Mecklenburg, S.; Scipal, K. & Laur, H. (2021) The Salinity Pilot-Mission Exploitation Platform (Pi-MEP): A Hub for Validation and Exploitation of Satellite Sea Surface Salinity Data Remote Sensing 13(22):4600 https://doi.org/10.3390/rs13224600

How to cite: Guimbard, S., Reul, N., sabia, R., Díez-García, R., Herlédan, S., El Khoury Hanna, Z., Lee, T., Schanze, J., Bingham, F., and Scipal, K.: Advancing Sea Surface Salinity R&D: The Pi-MEP Initiative for Satellite Salinity Data Validation and Exploitation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12907, https://doi.org/10.5194/egusphere-egu24-12907, 2024.

Across the broad potential user base for Earth Observation (EO) data, confidence in the quality of the available products is vital, particularly for users requiring quantitative measured outputs they can rely on. Particularly as the commercial EO sector rapidly expands, however, it is an increasing challenge for the user community to discern between the wide variety of product offerings in a reliable manner, especially in terms of product quality.

In response to this ESA and NASA, through their Joint Program Planning Group (JPPG) Subgroup, have developed a common EO product Quality Assurance (QA) Framework to provide comprehensive assessments of product quality. The evaluation is primarily aimed at verifying that the data has achieved its claimed performance levels, and, reviews the extent to which the products have been prepared following community best practice in a manner that is “fit for purpose”. A Cal/Val maturity matrix provides a high-level colour-coded a simple summary of the quality assessment results for users. The matrix contains a column for each section of analysis (e.g., metrology), and cells for each subsection of analysis (e.g., sensor calibration). Subsection grades are indicated by the colour of the respective grid cell, which are defined in the key.

Both ESA and NASA have on-going activities supporting the procurement of commercial EO data that make use of the joint QA Framework – to ensure decisions on data acquisition are made with confidence. On the ESA side, the Earthnet Data Assessment Project (EDAP) project performs data assessments on EO missions in optical, atmospheric and SAR domains. Similarly, the NASA Earth Science Division (ESD) Commercial Smallsat Data Acquisition (CSDA) Program, completed a pilot study in 2020, and has since entered sustainment use phase for some of the commercial data sets.

In this presentation the joint ESA/NASA QA Framework is described, with some examples of its application to commercial EO products.

How to cite: Hunt, S., Albinet, C., Nickeson, J., Osmanoglu, B., Hall, A., Lin, G., De Laurentiis, L., Goryl, P., Policelli, F., Ostrenga, D., and Fox, N.: ESA/NASA Quality Assurance Framework for Earth Observation Products, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12428, https://doi.org/10.5194/egusphere-egu24-12428, 2024.

The European Earth Observation programme Copernicus is implementing the next-generation system for atmospheric composition monitoring: after the success of the Sentinel-5 Precursor TROPOMI, a constellation of Sentinel-4 geostationary and Sentinel-5 Low-Earth orbiting missions will be launched in 2025 and beyond for air quality, ozone and climate variables monitoring, while the CO2M missions will observe greenhouse gases emissions and related proxies.  Post-launch validation of the data products is essential to determine their quality and enable users to judge their fitness-for-purpose.  Therefore, in 2021-2022 the European Union funded the H2020 Copernicus Cal/Val Solution (CCVS) project with the aim to review the status of existing validation infrastructures and methods for all Sentinel missions and to define a holistic solution to overcome limitations (https://ccvs.eu).  In this contribution we report on the maturity assessment and gap analysis performed in this project.  This assessment synthesizes lessons learned from earlier work in FP7 and H2020 projects, and from the operational/routine validation services run in the ESA/Copernicus Atmosphere Mission Performance Cluster (ATM-MPC), the EUMETSAT Atmospheric Composition Satellite Application Facility (AC SAF), the Copernicus Atmosphere Monitoring Service (CAMS) and the Copernicus Climate Change Service (C3S).  The CCVS assessment includes feedback from space agencies, Copernicus stakeholders and the CEOS Working Group on Calibration and Validation (WGCV).  

The validation means, such as the precursor data sets and comparison methods, have evolved significantly in the past decade: (1) New ground-based instruments have been developed and networks have expanded  in geographical coverage and in capabilities, (2) traceability to metrological standards and uncertainty characterization of the (Fiducial) Reference Measurements (FRM) has improved considerably, (3) rapid provision of FRM through data distribution services is becoming commonplace, (4)  the advantages of advanced comparison methods have been demonstrated, and (5) all of this has facilitated the development of operational, near-real-time validation systems such as the Validation Data Analysis Facility (VDAF-AVS) of the ATM-MPC for the Sentinel-5P mission. 

On the other hand, a list of remaining challenges still restrain the scope and quality of the validation of several atmospheric data products: (1) Station-to-station differences in ground-based validation results suggest (poorly understood) intra-network and inter-network inhomogeneity, (2) the coverage offered by ground-based networks (of the full range of the measurand values and of the influence quantities affecting the retrieval) can have important gaps, (3) timeliness of ground-based data provision remains poor for several products, (4) comparability (representativeness) between ground-based and satellite measurements requires further methodological advances and supporting measurement campaigns, (5) the accuracy and breadth of scope of the latest generation of satellite sounders puts correspondingly tight and difficult-to-meet requirements on the FRM data quality, (6) cross-validation of the different satellites requires a coordinated approach, and (7) some networks and activities experience increased/recurrent funding difficulties. 

We conclude this overview of the CCVS gap analysis for atmospheric composition data with illustrations of concrete actions undertaken recently to address some of the validation challenges highlighted by the project.

The CCVS project has received funding from the European Union’s Horizon 2020 programme under grant agreement No 101004242 (Project title: “Copernicus Cal/Val Solution). 

How to cite: Verhoelst, T., Lambert, J.-C., De Mazière, M., Langerock, B., Compernolle, S., Boersma, F., Hubert, D., Keppens, A., Pierangelo, C., Pinardi, G., Kumar Sha, M., Tack, F., Theys, N., Tilstra, G., Van Roozendael, M., Vigouroux, C., Dehn, A., Goryl, P., Marbach, T., and Clerc, S.: Post-launch Validation of the Copernicus Atmospheric Composition Satellites: Outcomes of the CCVS Gap Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17973, https://doi.org/10.5194/egusphere-egu24-17973, 2024.

Starting with the Lidar In-Space Technology Experiment (LITE) in 1994, spaceborne lidars have provided highly detailed global views of the vertical structure of clouds and aerosols. And since that time, surface-based lidar, well as aircraft lidar, have been used for validation through correlative measurements. While the validation of space-based lidar systems by surface-based lidar observations is not straightforward, protocols for doing so are well-established and have shown good agreement in many instances.     

The Micro Pulse Lidar Network (MPLNET) is a federated, global network of Micro Pulse Lidar systems deployed worldwide to measure aerosol and cloud vertical structure, and mixed layer heights. The data have been collected continuously, day and night, for more than 20 years from sites around the world with multiple sites containing 5+ or 10+ years of data. MPLNET is also a contributing network to the World Meteorological Organization (WMO) Global Atmospheric Watch (GAW) Aerosol Lidar Observation Network (GALION). The use of common instrumentation and processing algorithms within MPLNET allow for direct comparisons between sites. Thus, long-term MPLNET measurements can be used to verify the fidelity of geophysical parameters measured throughout the lifetime of individual satellite missions (e.g. CALIPSO, CATS, EarthCARE, CALIGOLA, and AOS) and provide a metric for intercomparisons between different space-based lidar missions when gaps between satellite missions occur.

In this presentation, we use multiple years of comparisons between MPLNET and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) flown aboard CALIPSO. For these comparisons, we use newly developed Level 3 MPLNET products consisting of monthly, diurnal statistics for cloud and aerosol retrievals covering a representative range of conditions and locations. Furthermore, we compare top-of-the-atmosphere cirrus cloud radiative forcing derived from these two complementary platforms. Finally, using results from an upcoming validation rehearsal, we demonstrate how these procedures will be utilized during the EarthCARE mission, scheduled to launch in May 2024.    

How to cite: Lewis, J., Campbell, J., Dolinar, E., Lolli, S., Stewart, S., Belcher, L., and Welton, E.: Utilizing surface-based observations from the Micro Pulse Lidar Network (MPLNET) for validation of space-based satellite missions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15137, https://doi.org/10.5194/egusphere-egu24-15137, 2024.

Since 2019 the NASA Pandora and ESA Pandonia projects have been collaborating to coordinate and facilitate the expansion of a global network of ground-based spectrometers to support space-based measurements of trace gases relevant to air quality (NO2, O3, HCHO, SO2, …). This network of standardized, calibrated Pandora instruments, the Pandonia Global Network (PGN, https://www.pandonia-global-network.org), is focused on providing data needed to help validate satellite measurements and to contribute to scientific studies of air quality.  As of January 2024, the PGN is comprised of 158 official sites in 34 countries. This presentation will describe recent efforts to expand and improve the network to support the increased capability and complexity of space-based measurements. Collaborative efforts by partner agencies, especially the US Environmental Protection Agency (EPA) and the Korean National Institute of Environmental Research (NIER), and new programs such as the Increasing Participation in Minority Serving Institutions (IPMSI) and Satellite Needs Working Group (SNWG) have accelerated the growth of the PGN, providing greater global coverage and allowing improved data products.  With these improvements and continued input from other suborbital assets, the PGN is well positioned to facilitate the interpretation and validation of high spatial resolution and diurnal measurements provided by the newest orbiting and geostationary satellite instruments. 

How to cite: Hanisco, T., Abuhassan, N., Casadio, S., Cede, A., Chang, L., Dehn, A., Lefer, B., Lind, E., Pandey, A., Place, B., Redondas, A., Szykman, J., Tiefengraber, M., Valin, L., van Roozendael, M., and von Bismarck, J.: Validation and support of space-based measurements with the Pandonia Global Network of ground-based spectrometers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20394, https://doi.org/10.5194/egusphere-egu24-20394, 2024.

Atmospheric formaldehyde (HCHO) is a short-lived but ubiquitous product of hydrocarbon oxidation. It is a tracer of hydrocarbon emissions and reactivity. HCHO has been observed from satellite-based instruments for over two decades. Retrievals typically involve (1) fitting slant columns to the observed UV/IR radiances and (2) deriving vertical columns from the slant columns using air mass factors. Air mass factors are calculated using radiative modeling and a-priori vertical HCHO distributions from a chemical transport model. The Pandora instruments form a ground-based remote sensing network that is valuable for validating satellite retievals. Pandora provides total and tropospheric columns of HCHO via direct sun (DS) and Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations in the UV, respectively. Here, we discuss conversion of slant columns to vertical columns for DS and MAX-DOAS Pandora measurements, neither of which involves radiative modeling and a-priori assumptions. We intercompare daily and seasonal variations in Pandora HCHO columns from these two distinct measurement techniques for ‘hotspot’ and ‘background’ sites to demonstrate their robustness and complementary strengths, as well as to estimate their uncertainties. We further examine the inter-site and seasonal variability in satellite (e.g., OMI, OMPS) retrievals relative to Pandora HCHO columns.     

How to cite: Pandey, A., Place, B., Liao, J., Abuhassan, N., Cede, A., Hanisco, T., and Lind, E.: Using Pandora direct sun and MAX-DOAS formaldehyde columns for evaluating satellite retrievals, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20665, https://doi.org/10.5194/egusphere-egu24-20665, 2024.

A multi-channel brightness temperature (TB) Fundamental Climate Data Record (FCDR) for the period 1991-present has been developed in this study using measurements from two Special Sensor Microwave Imagers (SSM/I) onboard the F11 and F13 satellites and one Special Sensor Microwave Imager/Sounder (SSMIS) onboard the F17 satellite of the US Defense Meteorological Satellite Program (DMSP). Hardware differences among these instruments were corrected using a combination of techniques including Principal Component Analysis (PCA), using the third instrument as an intermediate, and weighted averaging, which accounts for interchannel covariability and observation matching issues. After intercalibration, all imagers were standardized using SSMIS as the observation reference. The average biases of the recalibrated TBs for almost all channels between any two instruments are globally less than 0.2 K, with standard deviations (STDs) of less than 1.2 K. This resulted in a 30-year continuous and stable FCDR. Based on this FCDR, a long time series of column water vapour (CWV) over the global oceans was retrieved. Validation of this retrieved moisture product against reanalysis, in-situ radiosonde, and Global Navigation Satellite System (GNSS) measurements showed reasonable accuracy, suggesting that the presented FCDR has high potential for climate applications. In the future, this research method will be applied to more satellites to create an expanding dataset of satellite observations that could enhance the accuracy of climate model assessments and improve the reliability of climate predictions.

How to cite: Liu, S. and Wang, Y.: Highly consistent brightness temperature fundamental climate data record from SSM/I and SSMIS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4525, https://doi.org/10.5194/egusphere-egu24-4525, 2024.

Fundamental climate data records (FCDRs) play a vital role in monitoring climate change. In this article, we develop a spaceborne passive microwave-based FCDR byrecalibrating the Advanced Microwave Scanning Radiometerfor Earth Observing System (AMSR-E) on the Aqua satellite,the microwave radiometer imager (MWRI) onboard the FengYun-3B (FY3B) satellite, and the Advanced Microwave ScanningRadiometer-2 (AMSR2) onboard the JAXA’s Global ChangeObservation Mission first-Water (GCOM-W1) satellite. Beforerecalibration, it is found that AMSR-E and AMSR2 observations are stable over time, but MWRI drifted colder beforeMay 2015 and had nonnegligible errors in geolocation formost channels. In addition, intersensor differences of brightnesstemperatures (TBs) are as large as 5–10 K. To improve dataconsistency and continuity, several intersensor calibration methods are applied by using AMSR2 as a reference while usingMWRI to bridge the data gap between AMSR2 and AMSRE. The double difference method is used to provide intersensordifference time series for correcting calibration biases, such asscene temperature-dependent bias, solar-heating-induced bias,and systematic constant bias. Hardware differences betweensensors are corrected using principal component analysis. Afterrecalibration, the mean biases of both MWRI and AMSR-Eare less than 0.3 K compared to the AMSR2 reference andtheir standard deviations are less than 1 K for all channels.Under oceanic rain-free conditions, the TB biases are less than0.2 K for all channels and no significant relative bias driftswere found between sensors for overlapping observations. Thesestatistics suggest that the consistency between these instrumentswas significantly improved and the derived FCDR could be usefulto obtain long-term water cycle-related variables for climateresearch. 

How to cite: Wu, B. and Wang, Y.:  A Fundamental Climate Data Record Derived fromAMSR-E, MWRI, and AMSR2 , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15316, https://doi.org/10.5194/egusphere-egu24-15316, 2024.