Search Results (21)

The Flexible Combined Imager (FCI), developed as the next-generation imager for the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteosat Third Generation (MTG) satellite series, represents a significant advancement over its predecessor, SEVIRI, on the Meteosat Second Generation (MSG) satellites. FCI offers more spectral bands, higher spatial resolution, and faster imaging capabilities, supporting a wide range of applications in weather forecasting, climate monitoring, and environmental analysis. On 13 January 2024, the FCI onboard MTG-I1 (renamed Meteosat-12 in December 2024) experienced a critical anomaly involving the failure of its onboard Calibration and Obturation Mechanism (COM). As a result, the use of the COM was discontinued to preserve operational safety, leaving the instrument dependent on alternative calibration methods. This loss of onboard calibration presents immediate challenges, particularly for the infrared channels, including image artifacts (e.g., striping), reduced radiometric accuracy, and diminished stability. To address these issues, EUMETSAT implemented an external calibration approach leveraging algorithms from the Global Space-based Inter-Calibration System (GSICS). The inter-calibration algorithm transfers stable and accurate calibration from the Infrared Atmospheric Sounding Interferometer (IASI) hyperspectral instrument aboard Metop-B and Metop-C satellites to FCI’s infrared channels daily, ensuring continued data quality. Comparisons with Cross-track Infrared Sounder (CrIS) data from NOAA-20 and NOAA-21 satellites using a similar algorithm is then used to validate the radiometric performance of the calibration. This confirms that the external calibration method effectively compensates for the absence of onboard blackbody calibration for the infrared channels. For the visible and near-infrared channels, slower degradation rates and pre-anomaly calibration ensure continued accuracy, with vicarious calibration expected to become the primary source. This adaptive calibration strategy introduces a novel paradigm for in-flight calibration of geostationary instruments and offers valuable insights for satellite missions lacking onboard calibration devices. This paper details the COM anomaly, the external calibration process, and the broader implications for future geostationary satellite missions. Full article

Microwave sounding observations obtained from the National Oceanic and Atmospheric Administration (NOAA) and the European Meteorological Operational Satellite Program (METOP) satellites have been used for retrieving the cloud ice water path (IWP). However, the IWP algorithms developed in the past cannot be applied to the Fengyun-3F (FY-3F) microwave radiometers due to the differences in frequency of the primary channels and the fields of view. In this study, the IWP algorithm was tailored for the FY-3F satellite, and the retrieved IWP was compared with the fifth generation of reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5) and the Meteorological Operational Satellite-C (METOP-C) products. The results indicate that the IWP distribution retrieved from FY-3F observations demonstrates strong consistency with the cloud ice distributions in ERA5 data and METOP-C products in low-latitude regions. However, discrepancies are observed among the three datasets in mid- to high-latitude regions. ERA5 data underestimate the frequency of high IWP values and overestimate the frequency of low IWP values. The IWP retrieval results from satellite datasets demonstrate a high level of consistency. Furthermore, an analysis of the IWP time series reveals that the retrieval algorithm used in this study better captures variability and seasonal characteristics of IWP compared to ERA5 data. Additionally, a comparison of FY-3F retrieval results with METOP-C products shows a high correlation and generally consistent distribution characteristics across latitude bands. These findings confirm the high accuracy of IWP retrieval from FY-3F data, which holds significant value for advancing IWP research in China. Full article

In this study, the global land surface albedo namely GAC43 was retrieved for the years 1979 to 2020 using Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data onboard National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational (MetOp) satellites. We provide a comprehensive retrieval process of the GAC43 albedo, followed by a comprehensive assessment against in situ measurements and three widely used satellite-based albedo products, the third edition of the CM SAF cLoud, Albedo and surface RAdiation (CLARA-A3), the Copernicus Climate Change Service (C3S) albedo product, and MODIS BRDF/albedo product (MCD43). Our quantitative evaluations indicate that GAC43 demonstrates the best stability, with a linear trend of ±0.002 per decade at nearly all pseudo invariant calibration sites (PICS) from 1982 to 2020. In contrast, CLARA-A3 exhibits significant noise before the 2000s due to the limited availability of observations, while C3S shows substantial biases during the same period due to imperfect sensors intercalibrations. Extensive validation at globally distributed homogeneous sites shows that GAC43 has comparable accuracy to C3S, with an overall RMSE of approximately 0.03, but a smaller positive bias of 0.012. Comparatively, MCD43C3 shows the lowest RMSE (~0.023) and minimal bias, while CLARA-A3 displays the highest RMSE (~0.042) and bias (0.02). Furthermore, GAC43, CLARA-A3, and C3S exhibit overestimation in forests, with positive biases exceeding 0.023 and RMSEs of at least 0.028. In contrast, MCD43C3 shows negligible bias and a smaller RMSE of 0.015. For grasslands and shrublands, GAC43 and MCD43C3 demonstrate comparable estimation uncertainties of approximately 0.023, with close positive biases near 0.09, whereas C3S and CLARA-A3 exhibit higher RMSEs and biases exceeding 0.032 and 0.022, respectively. All four albedo products show significant RMSEs around 0.035 over croplands but achieve the highest estimation accuracy better than 0.020 over deserts. It is worth noting that significant biases are typically attributed to insufficient spatial representativeness of the measurement sites. Globally, GAC43 and C3S exhibit similar spatial distribution patterns across most land surface conditions, including an overestimation compared to MCD43C3 and an underestimation compared to CLARA-A3 in forested areas. In addition, GAC43, C3S, and CLARA-A3 estimate higher albedo values than MCD43C3 in low-vegetation regions, such as croplands, grasslands, savannas, and woody savannas. Besides the fact that the new GAC43 product shows the best stability covering the last 40 years, one has to consider the higher proportion of backup inversions before 2000. Overall, GAC43 offers a promising long-term and consistent albedo with good accuracy for future studies such as global climate change, energy balance, and land management policy. Full article

In the past decades, satellite hyperspectral remote sensing instruments have been providing key measurements for environmental monitoring, such as the analysis of water and air quality, soil usage, weather forecasting, or climate change. The success of this technology, however, relies on an accurate knowledge of the instrument’s spectral response functions (SRFs). Usually, the SRFs are assessed on-ground and then monitored on-flight using tedious analysis of the acquired radiances coupled with instrumental models; nonetheless, the complete retrieval of the SRFs is generally out of reach. In this context, EUMETSAT has developed a novel SRF retrieval methodology, with the intention of applying it routinely to the current Metop IASI instruments and soon to Metop-SG IASI-NG, and MTG-S IRS. By making use of spatiotemporal colocations of different detectors within a single instrument or between different platforms, relative SRFs may be retrieved on-flight without any a priori knowledge. The presented methodology is suited for instruments acquiring radiances with contiguous sampling over large spectral bands as the SRFs are retrieved by analyzing the neighboring channels’ correlations. This article focuses on Fourier transform spectrometers (FTS) in the far infrared as they possess these characteristics per design, but it is believed that the method could be extended to other technology and spectral bands. The SRFs are further processed to evaluate the relative self-apodization functions (SAFs), as they represent the discrepancies between the detectors at the interferograms level, the primary measurements of FTS. The following article presents both simulations and applications of the SRF retrieval for the three IASI instruments aboard the Metop platforms of the EPS program. We analyze both IASI sensors aboard Metop-B and C as well as the evolution of Metop-A IASI over 13 years of operation. Full article

This study presents our first discovery about two abnormal problems in the blackbody calibration target associated with the antenna unit A2 in the Metop-C AMSU-A instrument. The problems include the anomalous patterns in both blackbody kinetic temperature $\left(T_w\right)$ and radiative temperature (measured in warm count or $C_w$), and the time lag between orbital cycles of $T_w$ and $C_w$. This study further determines solar intrusion as the root cause of the anomalous pattern problem. According to our analysis, solar illumination is constantly observed during each orbit near the satellite terminator, causing anomalous changes in $C_w$ and $T_w$, characterized by sudden and abnormal increases typically for more than 16 min. The resultant maximum antenna temperature errors due to abnormal increases in $C_w$ are approximately in the range from 0.15 K to 0.25 K, while the maximum errors due to the abnormal increase in $T_w$ are in the range from 0.04 K to 0.07 K, varying with orbit, season, and channel. The time shift feature is characterized with a changeable time lag with the season in the $T_w$ orbital cycle in comparison with the $C_w$ cycle. The longest time lag up to about 18 min occurs in summer through early fall, while the time lag can be decreased down to about 9 min in winter through early spring. Hence, this study underscores the imperative need for future research to rectify radiance errors and reconstruct a more accurate long-term Metop-C AMSU-A radiance data set for channels 1 and 2, crucial for climate studies. Full article

This study aims to explore the joint usage of multisource scatterometer measurements in polar sea water and ice discrimination. All radar backscatter measurements from current operating satellite scatterometers are considered, including the C-band ASCAT scatterometer on board the MetOp series satellites, the Ku-band scatterometer on board the HY-2B satellite (HSCAT), and the Ku-band scatterometer on board the CFOSAT satellite (CSCAT). By performing seven experiments that use the same support vector machine (SVM) classifier method but with different input data, we find that the SVM model with all available HSCAT, CSCAT, and ASCAT scatterometer data as inputs gives the best performance. In addition to the SVM outputs, we employ the image erosion/dilation techniques and area growth method to reduce misclassifications of sea water and ice. The sea ice extent obtained in this study shows a good agreement with the National Snow and Ice Data Center (NSIDC) sea ice concentration data from the years 2019 to 2021. More specifically, the sea ice areas are closer to the sea ice areas calculated using 15% as the threshold for NSIDC sea ice concentration data in both Arctic and Antarctic. The sea ice edges acquired by the multisource scatterometer show a close correlation with sea ice edges from the Sentinel-1 Synthetic Aperture Radar (SAR) images. In addition, we found that the coverage of multisource scatterometer data in a half-day is usually above 97%, and more importantly, the sea ice areas obtained on the basis of half-day and daily multisource scatterometer data are very close to each other. The presented work can serve as guidance on the usage of all available scatterometer measurements in sea ice monitoring. Full article

To understand the activity of gravity waves (GWs) over the Tibetan Plateau (TP) is of great significance for improving global climate models. Considering that the lower stratosphere is the main level of GWs activity, this paper first established a 14-year 2° × 2° longitude–latitude monthly mean GWs model in the lower stratosphere (18~20 km) of the TP by combining post-processed dry temperature profiles provided by the multi-Global Navigation Satellite System (GNSS) radio occultation (RO) missions: The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and the Meteorological Operational (METOP) series polar-orbiting meteorological satellites (METOP-A, METOP-B, and METOP-C) from August 2006 to September 2020. Based on this model, this paper analyzed the characteristics of GWs activity around TP and the effects of topography, background wind, and zonal wind on GWs activity and summarized the general process of topographic wave excitation and upward propagation around TP. The spatial distribution of the lower stratospheric GW Ep is highly correlated with the spatial distribution of background wind and the topography of TP during GWs excitation. The GW Ep is obviously filtered by the zero-speed wind. The change in GW Ep is strongly correlated with the change in topography. These phenomena indicate that the GWs of TP are mainly topographic waves. Moreover, the lower stratospheric GW Ep of TP shows that periodic changes are mainly affected by the periodic background wind, and the GW Ep value is larger in February and smaller in August. The large GW Ep in the lower stratosphere of TP is not only related to the GWs strongly generated by the interaction between the strong background wind and the large elevation or large topographic changes but also related to the strong zonal westerly winds that promote the propagation of GWs upward. Multivariable linear regression models were used to reconstruct the lower stratospheric GW Ep over TP based on the background wind and the zonal wind and a goodness of fit of 81.1% was achieved. It indicates that the GW Ep is dominated by the topographic wave over TP in the lower stratosphere and the background wind has a greater influence on the GWs than the zonal wind. Full article

Craniosynostosis (CS) is a major birth defect in which one or more skull sutures fuse prematurely. We previously performed a genome-wide association study (GWAS) for sagittal non-syndromic CS (sNCS), identifying associations downstream from BMP2 on 20p12.3 and intronic to BBS9 on 7p14.3; analyses of imputed variants in DLG1 on 3q29 were also genome-wide significant. We followed this work with a GWAS for metopic non-syndromic NCS (mNCS), discovering a significant association intronic to BMP7 on 20q13.31. In the current study, we sequenced the associated regions on 3q29, 7p14.3, and 20p12.3, including two candidate genes (BMP2 and BMPER) near some of these regions in 83 sNCS child-parent trios, and sequenced regions on 7p14.3 and 20q13.2-q13.32 in 80 mNCS child-parent trios. These child-parent trios were selected from the original GWAS cohorts if the probands carried at least one copy of the top associated GWAS variant (rs1884302 C allele for sNCS; rs6127972 T allele for mNCS). Many of the variants sequenced in these targeted regions are strongly predicted to be within binding sites for transcription factors involved in craniofacial development or bone morphogenesis. Variants enriched in more than one trio and predicted to be damaging to gene function are prioritized for functional studies. Full article

Multiple radio occultation (RO) missions are currently providing observations that are assimilated by the world’s leading numerical weather prediction centers. These RO missions use the same signals originating from the Global Navigation Satellite Systems (GNSS), but they have different satellite designs and sizes with different antennas and receivers. This results in different noise levels for different missions. Although the amplitude data are characterized by the Signal-to-Noise Ratio (SNR), the noise, to which they are normalized, is not the real Noise Floor (NF) of the RO observations. We study the statistical distributions of the SNR and NF for RO missions including COSMIC, COSMIC2, METOP-A, METOP-B, METOP-C, and Spire. We demonstrate that different missions have different NF values and different NF and SNR distributions, sometimes multimodal. We propose to use the most probable NF value as an SNR normalization constant in order to compare the SNR values from different RO missions. Full article

The spatial–temporal distribution of the global gravity wave (GW) potential energy (Ep) at the lower stratosphere of 20–35 km is studied using the dry temperature profiles from multi- Global Navigation Satellite System (GNSS) radio occultation (RO) missions, including CHAMP, COSMIC, GRACE, and METOP-A/B/C, during the 14 years from 2007 to 2020, based on which the linear trends of the GW Ep and the responses of GW Ep to solar activity, quasi biennial oscillation (QBO), and El Niño-Southern Oscillation (ENSO) are analyzed using the multivariate linear regression (MLR) method. It is found that the signs and the magnitudes of the trends of GW Ep during each month vary at different altitude ranges and over different latitudes. At 25–35 km of the middle and high latitudes, GW Ep values generally show significant negative trends in almost all months, and the values of the negative trends become smaller in the regions closer to the poles. The distribution of the deseasonalized trends in the monthly zonal-mean GW Ep demonstrates that the GW activities are generally declining from 2007 to 2020 over the globe. The responses of GW Ep to solar activity are found to be mostly positive at 20–35 km over the globe, and the comparison between the distribution pattern of the deseasonalized trends in the GW activities and that of the responses of GWs to solar activity indicates that the sharp decline in solar activity from 2015 to 2017 might contribute to the overall attenuation of gravity wave activity during the 14 years. Significant negative responses of GW Ep to QBO are found at 30–35 km over 30° S–25° N, and the negative responses extend to the mid and high latitudes in the southern hemisphere at 20–30 km. The responses of GW Ep to QBO change to be significantly positive at 20–30 km over 15° S–15° N, which demonstrates that the zonal wind field should be the main factor affecting the GW activities at 20–30 km over the tropics. The responses of GW Ep at 20–35 km to ENSO are found to be positive over 15° S–15° N, while at 30–35 km over 15° N–30° N and at 20–35 km near 50° N, significant negative responses of GW Ep to ENSO exist. Full article

The first full-mission global AVHRR FRAC sea surface temperature (SST) dataset with a nominal 1.1 km resolution at nadir was produced from three Metop First Generation (FG) satellites: Metop-A (2006-on), -B (2012-on) and -C (2018-on), using the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) SST enterprise system. Historical reprocessing (‘Reanalysis-1’, RAN1) starts at the beginning of each mission and continues into near-real time (NRT). ACSPO generates two SST products, one with global regression (GR; highly sensitive to skin SST), and another one with piecewise regression (PWR; proxy for depth SST) algorithms. Small residual effects of orbital and sensor instabilities on SST retrievals are mitigated by retraining the regression coefficients daily, using matchups with drifting and tropical moored buoys within moving time windows. In RAN, the training windows are centered at the processed day. In NRT, the same size windows are employed but delayed in time, ending four to ten days prior to the processed day. Delayed-mode RAN reprocessing follows the NRT with a two-month lag, resulting in a higher quality and a more consistent SST record. In addition to its completeness, the newly created Metop-FG RAN1 SST dataset shows very close agreement with in situ data (including the fully independent Argo floats), well within the NOAA specifications for accuracy (global mean bias; ±0.2 K) and precision (global standard deviation; 0.6 K) in a ~20% clear-sky domain (percent of clear-sky SST pixels to the total of ice-free ocean). All performance statistics are stable in time, and consistent across the three platforms. The Metop-FG RAN1 data set is archived at the NASA JPL PO.DAAC and NOAA NCEI. This paper documents the newly created dataset and evaluates its performance. Full article

Scatterometers provide very stable ocean vector wind data records. This is because they measure the ratio of backscattered to incident microwave signal over the ocean surface as opposed to an absolute quantity (e.g., emitted microwave signal). They provide an optimal source of observations for building a long ocean vector wind Climate Data Record (CDR). With this objective in mind, observations from different satellite platforms need to be assessed for high absolute accuracy versus a common ground truth and for fine cross-calibration during overlapping periods. Here we describe the methodology for developing a CDR of ocean surface winds from the C-band ASCAT scatterometers onboard MetOp-A, -B, and -C. This methodology is based on the following principles: a common Geophysical Model Function (GMF) and wind algorithm developed at Remote Sensing Systems (RSS) and the use of in situ and satellite winds to cross-calibrate the three scatterometers within the accuracy required for CDRs, about 0.1 m/s at the global monthly scale. Using multiple scatterometers and radiometers for comparison allows for the opportunity to isolate sensors that are drifting or experiencing step-changes as small as 0.05 m/s. We detected and corrected a couple of such changes in the ASCAT-A wind record. The ASCAT winds are now very stable over time and well cross-calibrated with each other. The full C-band wind CDR now covers 2007-present and can be easily extended in the next decade with the launch of the MetOp Second Generation scatterometers. Full article

The present analysis utilized the 6-hourly data of wind speed (zonal and meridional) for the period between 2011 and 2019, as retrieved from the Copernicus Marine Environmental Service (CMEMS), covering the Thracian Sea (the northern part of the Aegean Sea). Data were estimated from the global wind fields derived from the Advanced Scatterometer (ASCAT) L2b scatterometer on-board Meteorological Operational (METOP) satellites, and then processed towards the equivalent neutral-stability 10 m winds with a spatial resolution of 0.25° × 0.25°. The analysis involved: (a) descriptive statistics on wind speed and direction data; (b) frequency distributions of daily-mean wind speeds per wind direction sector; (c) total wind energy content assessment per wind speed increment and per sector; (d) total annual wind energy production (in MWh/yr); and (e) wind power density, probability density function, and Weibull wind speed distribution, together with the relevant dimensionless shape and scale parameters. Our results show that the Lemnos Plateau has the highest total wind energy content (4455 kWh/m²/yr). At the same time, the area to the SW of the Dardanelles exhibits the highest wind energy capacity factor (~37.44%), producing 7546 MWh/yr. This indicates that this zone could harvest wind energy through wind turbines, having an efficiency in energy production of 37%. Lower capacity factors of 24–28% were computed at the nearshore Thracian Sea zone, producing between 3000 and 5600 MWh/yr. Full article

Land surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. This article presents the algorithm concepts for the remote sensing of this variable based on the heritage of several developments which were performed at Méteo France over the last decade and described in several papers by Carrer et al. The scientific algorithm comprises four steps: an atmospheric correction, a sensor harmonisation (optional), a BRDF (Bidirectional Reflectance Distribution Function) inversion, and the albedo calculation. At the time being, the method has been applied to 11 sensors in the framework of two European initiatives (Satellite Application Facility on Land Surface Analysis—LSA SAF, and Copernicus Climate Change Service—C3S): NOAA-7-9-11-14-16-17/AVHRR2-3, SPOT/VGT1-2, Metop/AVHRR-3, PROBA-V, and MSG/SEVIRI. This work leads to a consistent archive of almost 40 years of satellite-derived albedo data (available in 2020). From a single sensor, up to three different albedo products with different characteristics have been developed to address the requirements of both, near real-time (NRT) (weather prediction with a demand of timeliness of 1 h) and climate communities. The evaluation of the algorithm applied to different platforms was recently made by Lellouch et al. and Sánchez Zapero et al. in 2020 which can be considered as companion papers. After a summary of the method for the retrieval of these surface albedos, this article describes the specificities of each retrieval, lists the differences, and discusses the limitations. The plan of continuity with the next European satellite missions and perspectives of improvements are introduced. For example, Metop/AVHRR-3 albedo will soon become the medium resolution sensor product with the longest NRT data record, since MODIS is approaching the end of its life-cycle. Additionally, Metop-SG/METimage will ensure its continuity thanks to consistent production of data sets guaranteed till 2050 by the member states of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). In the end, the common strategy which we proposed through the different programmes may offer an unprecedented opportunity to study the temporal trends affecting surface properties and to analyse human-induced climate change. Finally, the access to the source code (called PYALUS) is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable. Full article

Following the mission science plan of EPS/Metop-SG C-band scatterometer for 2023–2044, we consider the potential application of the sea ice/water discrimination method based on the minimum statistical distance of the measured normalized radar cross sections (NRCS) to the geophysical model functions (GMF) of the sea ice and water, respectively. The application of the method is considered for the classical spacecraft scatterometer geometry with three fixed fan-beam antennas and the hypothetical prospective scatterometer geometry with the five fixed fan-beam antennas. Joint vertical (VV) and horizontal (HH) transmit and receive polarization are considered for the spaceborne scatterometer geometries. We show explicitly that the hypothetical five fixed fan-beam antenna geometry combined with the dual VV and HH polarization for all antennas provides better estimates of the sea wind speed and direction as well as sea ice/water discrimination during single spacecraft pass. The sea ice/water discrimination algorithms developed for each scatterometer geometry and dual VV/HH polarization are presented. The obtained results can be used to optimize the design of new spaceborne scatterometers and will be beneficial to the forthcoming satellite missions. Full article