In the framework of the Satellite Application Facility on Climate Monitoring (CM-SAF) an algorithm was developed to retrieve Cloud Physical Properties…In the framework of the Satellite Application Facility on Climate Monitoring (CM-SAF) an algorithm was developed to retrieve Cloud Physical Properties (CPP) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation (METEOSAT−8) and the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) satellites. This paper presents the CPP algorithm and determines if SEVIRI can be used together with AVHRR to build a consistent and accurate data set of cloud optical thickness (COT) and cloud liquid water path (CLWP) over Europe for climate research purposes. After quantifying the differences in 0.6 and 1.6 μm operational calibrated reflectances of SEVIRI and AVHRR, a recalibration procedure is proposed to normalize and absolutely calibrate these reflectances. The effects of recalibration, spatial resolution, and viewing geometry differences on the SEVIRI and AVHRR cloud property retrievals are evaluated. The intercomparison of 0.6 and 1.6 μm operationally calibrated reflectances indicates ∼6 and ∼26% higher reflectances for SEVIRI than for AVHRR. These discrepancies result in retrieval differences between AVHRR and SEVIRI of ∼8% for COT and ∼60% for CLWP. Owing to recalibration these differences reduce to ∼5%, while the magnitude of the median COT and CLWP values of AVHRR decrease ∼2 and ∼60% and the SEVIRI values increase ∼10 and ∼55%, respectively. The differences in spatial resolution and viewing geometry slightly influence the retrieval precision. Thus the CPP algorithm can be used to build a consistent and high-quality data set of SEVIRI and AVHRR retrieved cloud properties for climate research purposes, provided the instrument reflectances are recalibrated, preferably guided by the satellite operators.more
This paper describes a new method for cloud-correcting observations of black-sky surface albedo derived using the Advanced Very High Resolution Radiom…This paper describes a new method for cloud-correcting observations of black-sky surface albedo derived using the Advanced Very High Resolution Radiometer (AVHRR). Cloud cover constitutes a major challenge for surface albedo estimation using AVHRR data for all possible conditions of cloud fraction and cloud type with any land cover type and solar zenith angle. This study shows how the new cloud probability (CP) data to be provided as part of edition A3 of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record from the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT can be used instead of traditional binary cloud masking to derive cloud-free monthly mean surface albedo estimates. Cloudy broadband albedo distributions were simulated first for theoretical cloud distributions and then using global cloud probability (CP) data for 1 month. A weighted mean approach based on the CP values was shown to produce very-high-accuracy black-sky surface albedo estimates for simulated data. The 90 % quantile for the error was 1.1 % (in absolute albedo percentage) and that for the relative error was 2.2 %. AVHRR-based and in situ albedo distributions were in line with each other and the monthly mean values were also consistent. Comparison with binary cloud masking indicated that the developed method improves cloud contamination removal.more
The second Advanced Technology Microwave Sounder (ATMS) was onboard the National Oceanic and Atmospheric Administration (NOAA)-20 satellite when launc…The second Advanced Technology Microwave Sounder (ATMS) was onboard the National Oceanic and Atmospheric Administration (NOAA)-20 satellite when launched on 18 November 2017. Using nearly six months of the earliest NOAA-20 observations, the biases of the ATMS instrument were compared between NOAA-20 and the Suomi National Polar-Orbiting Partnership (S-NPP) satellite. The biases of ATMS channels 8 to 13 were estimated from the differences between antenna temperature observations and model simulations generated from Meteorological Operational (MetOp)-A and MetOp-B satellites’ Global Positioning System (GPS) radio occultation (RO) temperature and water vapor profiles. It was found that the ATMS onboard the NOAA-20 satellite has generally larger cold biases in the brightness temperature measurements at channels 8 to 13 and small standard deviations. The observations from ATMS on both S-NPP and NOAA-20 are shown to demonstrate an ability to capture a less than 1-h temporal evolution of Hurricane Florence (2018) due to the fact that the S-NPP orbits closely follow those of NOAA-20.more
We analyze trends in total column water vapor (TCWV) retrieved from independent satellite observations and retrieval schemes. GOME-SCIAMACHY (Global O…We analyze trends in total column water vapor (TCWV) retrieved from independent satellite observations and retrieval schemes. GOME-SCIAMACHY (Global Ozone Monitoring Experiment-SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) measurements are carried out in the visible part of the solar spectrum and present a partly cloud-corrected climatology that is available over land and ocean. The HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) product, provided by EUMETSAT's Satellite Application Facility on Climate Monitoring is based on passive microwave observations from the Special Sensor Microwave/Imager. It also includes the TCWV from cloudy pixels but is only available over oceans. The common observation time period is between 1996 and 2005. Due to the relatively short length of the period, the strong interannual variability with strong contributions from El Niño and La Niña events and the strong anomaly at the start of the common period, caused by the 1997/1998 El Niño, the observed trends should not be interpreted as long-term climate trends. After subtraction of average seasonality from monthly gridded data, a linear model and a level shift model have been fitted to the HOAPS and GOME-SCIAMACHY data, respectively. Autocorrelation and cross correlation of fit residuals are accounted for in assessing uncertainties in trends. The trends observed in both time series agree within uncertainty margins. This agreement holds true for spatial patterns, magnitudes, and global averages. The consistency increases confidence in the reliability of the trends because the methods, spectral range, and observation technique as well as the satellites and their orbits are completely independent of each other. The similarity of the trends in both data sets is an indication of sufficient stability in the observations for the time period of ≈ 10 years.more
The aim of this work is to analyse the quality of long-term trends of surface incoming shortwave solar radiation (SIS) derived from two satellite data…The aim of this work is to analyse the quality of long-term trends of surface incoming shortwave solar radiation (SIS) derived from two satellite datasets from the EUMETSAT Satellite Application on Climate Monitoring (CM SAF): the SIS Data Set from the Advanced Very High-Resolution Radiometer (AVHRR) data, Edition 2 (CLARA-A2), and the SIS Data Set-Heliosat, Edition 2 (SARAH-2). In order to achieve this goal, reference ground-based SIS measurements recorded at 12 stations over the Iberian Peninsula for the period 1985–2015 are used in this study. Firstly, the two satellite datasets have been compared against ground-based SIS measurements at 12 surface sites, showing a good agreement (i.e., R = 0.83 in SARAH-2 and R = 0.80 in CLARA-A2 on an annual basis). However, the two satellite datasets substantially underestimate the SIS trends found for the ground-based measurements. Thus, while the ground-based SIS data reported trends between −0.5 and + 6.5 Wm−2decade−1 (with statistical significance at 95% level at most stations), the satellite datasets gave trends lower for all locations (without statistical significance); between −0.4 and + 3.8 Wm−2decade−1 for CLARA-A2, and between +0.2 and + 2.8 Wm−2decade−1 for SARAH-2. It is worth to mention that the seasonal analysis of the SIS trends for both ground-based and satellite data displays a reasonably good agreement in spring (i.e., high positive trends), in accordance with the notable decline in the cloudiness for this season in the study region. By contrast, satellite products exhibit smaller SIS anomalies than ground-based data in summer, particularly from the beginning 2000s, which could be related to well-known decrease in the aerosol load over the study region.more
Chiou, E. W.; Bhartia, P. K.; McPeters, R. D.; Loyola, D. G.; Coldewey-Egbers, M.; Fioletov, V. E.; Van Roozendael, M.; Spurr, R.; Lerot, C.; Frith, S. M.
Abstract. This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, na…Abstract. This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile total ozone, (ii) GTO (GOME-type total ozone), and (iii) ground-based total ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0–30° S, 0–30° N, 50–30° S, and 30–60° N. It has been found that, on average, the differences in monthly zonal mean total ozone vary between −0.3 and 0.8 % and are well within 1%. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean total ozone vary between 0.6–0.7% and 2.8–3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4–0.6% and 2.2–3.5%. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4–2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between −0.04 and 0.1% yr−1 (−0.1 and 0.3 DU yr−1). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multi-year total ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30–60° N from −5% in 1996 to −2% in 2010. In contrast, at 50–30° S and 30° S–30° N there has been a levelling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1%, but a slight increase has been found in the differences during the period 1996–2010.more