Meteosat Visible And Infrared Imager Research Articles

Assimilation of INSAT-3D imager water vapour clear sky brightness temperature in the NCMRWF’s assimilation and forecast system

This paper describes the direct assimilation of water vapour (WV) clear sky brightness temperatures (CSBTs) from the INSAT-3D imager in the National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Model (NCUM) assimilation and forecast system. INSAT-3D imager WV CSBTs show a systematic bias of 2–3 K compared to the data simulated from the model first guess fields in the pre-assimilation study. The bias in the INSAT-3D imager WV CSBTs is removed using a statistical bias correction prior to assimilation. The impact of INSAT-3D imager WV channel CSBTs is investigated through different approaches: (i) single observation experiments and (ii) global assimilation experiments using the hybrid-four-dimensional variational technique. Single observation experiments of channels of the same frequency from different instruments like the INSAT-3D imager and sounder, and the Meteosat visible and infrared imager (MVIRI) onboard Meteosat-7, show the INSAT-3D imager and MVIRI WV channels have a similar impact on the analysis increment. Global assimilation clearly shows the positive impact of the INSAT-3D imager WV CSBTs on the humidity and upper tropospheric wind fields, whereas the impact on the temperature field, particularly over the tropics, is neutral. Validation of model forecasted parameters with the in situ radio sonde observations also showed the positive impact of assimilation on the humidity and wind fields. INSAT-3D imager WV CSBTs have been assimilated operationally in NCUM since August 2018.

Climate Data Records from Meteosat First Generation Part III: Recalibration and Uncertainty Tracing of the Visible Channel on Meteosat-2–7 Using Reconstructed, Spectrally Changing Response Functions

This paper presents a new Fundamental Climate Data Record (FCDR) for the visible (VIS) channel of the Meteosat Visible and Infrared Imager (MVIRI), with pixel-level metrologically traceable uncertainties and error covariance estimates. MVIRI has flown onboard Meteosat First Generation (MFG) satellites between 1982 and 2017. It has served the weather forecasting community with measurements of “visible”, “infra-red” and “water vapour” radiance in near real-time. The precision of the pre-launch sensor spectral response function (SRF) characterisation, particularly of the visible band of this sensor type, improved considerably with time, resulting in higher quality radiances towards the end of the MFG program. Despite these improvements, the correction of the degradation of this sensor has remained a challenging task and previous studies have found the SRF degradation to be faster in the blue than in the near-infrared part of the spectrum. With these limitations, the dataset cannot be immediately applied in climate science. In order to provide a data record that is suited for climate studies, the Horizon 2020 project “FIDelity and Uncertainty in Climate-data records from Earth Observation” (FIDUCEO) conducted (1) a thorough metrological uncertainty analysis for each instrument, and (2) a recalibration using enhanced input data such as reconstructed SRFs. In this paper, we present the metrological analysis, the recalibration results and the resulting consolidated FCDR. In the course of this study we were able to trace-back the remaining uncertainties in the calibrated MVIRI reflectances to underlying effects that have distinct physical root-causes and spatial/temporal correlation patterns. SEVIRI and SCIAMACHY reflectances have been used for a validation of the harmonised dataset. The resulting new FCDR is publicly available for climate studies and for the production of climate data records (CDRs) spanning about 35 years.

Inverse transport modeling of volcanic sulfur dioxide emissions using large-scale simulations

Abstract. An inverse transport modeling approach based on the concepts of sequential importance resampling and parallel computing is presented to reconstruct altitude-resolved time series of volcanic emissions, which often cannot be obtained directly with current measurement techniques. A new inverse modeling and simulation system, which implements the inversion approach with the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) is developed to provide reliable transport simulations of volcanic sulfur dioxide (SO2). In the inverse modeling system MPTRAC is used to perform two types of simulations, i.e., unit simulations for the reconstruction of volcanic emissions and final forward simulations. Both types of transport simulations are based on wind fields of the ERA-Interim meteorological reanalysis of the European Centre for Medium Range Weather Forecasts. The reconstruction of altitude-dependent SO2 emission time series is also based on Atmospheric InfraRed Sounder (AIRS) satellite observations. A case study for the eruption of the Nabro volcano, Eritrea, in June 2011, with complex emission patterns, is considered for method validation. Meteosat Visible and InfraRed Imager (MVIRI) near-real-time imagery data are used to validate the temporal development of the reconstructed emissions. Furthermore, the altitude distributions of the emission time series are compared with top and bottom altitude measurements of aerosol layers obtained by the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite instruments. The final forward simulations provide detailed spatial and temporal information on the SO2 distributions of the Nabro eruption. By using the critical success index (CSI), the simulation results are evaluated with the AIRS observations. Compared to the results with an assumption of a constant flux of SO2 emissions, our inversion approach leads to an improvement of the mean CSI value from 8.1 to 21.4 % and the maximum CSI value from 32.3 to 52.4 %. The simulation results are also compared with those reported in other studies and good agreement is observed. Our new inverse modeling and simulation system is expected to become a useful tool to also study other volcanic eruption events.

Climatology of free-tropospheric humidity: extension into the SEVIRI era, evaluation and exemplary analysis

Abstract. A new free-tropospheric humidity (FTH) data record is presented. It is based on observations from the Meteosat Visible and Infrared Imager (MVIRI) onboard Meteosat-2–Meteosat-5, as well as Meteosat-7, and the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat-8 and Meteosat-9 at the water absorption band near 6.3 μm. The data set is available under clear-sky and low-level cloud conditions. With the extension to SEVIRI observations, the data record covers the period 1983–2009 with a spatial resolution of 0.625° × 0.625° and a temporal resolution of 3 h. The FTH is the mean relative humidity (RH) in a broad layer in the free troposphere. The relation between the observed brightness temperature (BT) and the FTH is well established. Previous retrievals are refined by taking into account the relative humidity Jacobians in the training process of the statistical retrieval. The temporal coverage is extended into the SEVIRI period, the homogenization of the BT record is improved, and the full archive is reprocessed using updated regression coefficients. The FTH estimated from the Meteosat observations is compared to the FTH computed from the RH profiles of the Analyzed RadioSoundings Archive (ARSA). An average relative bias of −3.2% and a relative root-mean-square difference (RMSD) of 16.8% are observed. This relative RMSD agrees with the outcome of an analysis of the total uncertainty of the FTH product. The decadal stability of the FTH data record is 0.5 ± 0.45% per decade. As exemplary applications, the interannual standard deviation, the differences on decadal scales, and the linear trend in the FTH data record and in the frequency of occurrence of FTH < 10% (FTHp10) are analyzed per season. Interannual standard deviation maxima and maxima in absolute decadal differences are featured in gradient areas between dry and wet regions, as well as in areas where FTH reaches minima and FTHp10 reaches maxima. An analysis of the FTH linear trends and of the associated uncertainty estimates is achieved to identify possible problems with the data record. Positive trends in FTHp10 are featured in gradient areas between wet and dry regions, in regions where the FTH is minimum, in regions where FTHp10 is maximum, and in regions where differences between FTHp10 averaged over the 2000s and 1990s are negative. However, these positive trends in FTHp10 are associated with maximum standard deviation and are thus hardly significant. This analysis and intercomparisons with other humidity data records are part of the Global Energy and Water Cycle Experiment (GEWEX) Water Vapor Assessment (G-VAP).

HelioFTH: combining cloud index principles and aggregated rating for cloud masking using infrared observations from geostationary satellites

Abstract. In this paper a cloud mask and cloud fractional coverage (CFC) retrieval scheme called HelioFTH is presented. The algorithm is self-calibrating and relies on infrared (IR) window-channel observations only. It needs no input from numerical weather prediction (NWP) or radiative transfer models, nor from other satellite platforms. The scheme is applicable to the full temporal and spatial resolution of the Meteosat Visible and InfraRed Imager (MVIRI) and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensors. The main focus is laid on the separation of middle- and high-level cloud coverage (HCC) from low-level clouds based on an internal cloud-top pressure (CTP) product. CFC retrieval employs a IR-only cloud mask based on an aggregated rating scheme. CTP retrieval is based on a Heliosat-like cloud index for the MVIRI IR channel. CFC from HelioFTH, the International Satellite Cloud Climatology Project (ISCCP) DX and the Satellite Application Facility on Climate Monitoring (CM SAF) were validated with CFC from the Baseline Surface Radiation Network (BSRN) and the Alpine Surface Radiation Budget (ASRB) network. HelioFTH CFC differs by not more than 5–10% from CM SAF CFC but it is higher than ISCCP-DX CFC. In particular the conditional probability to detect cloud-free pixels with HelioFTH is raised by about 35% compared to ISCCP-DX. The HelioFTH CFC is able to reproduce the day-to-day variability observed at the surface. Also, the HelioFTH HCC was inter-compared to CM SAF and ISCCP-DX over different regions and stations. The probability of false detection of cloud-free HCC pixels is in the same order as ISCCP-DX compared to the CM SAF HCC product over the full-disk area. HelioFTH could be used for generating an independent climate data record of cloud physical properties once its consistency and homogeneity is validated for the full Meteosat time series.

Convective Activity over Africa and the Tropical Atlantic Inferred from 20 Years of Geostationary Meteosat Infrared Observations

Abstract A 20-yr (1986–2005) time series of Meteosat Visible and Infrared Imager (MVIRI) geostationary infrared observations was used to study deep convection over Africa and the tropical Atlantic. The 20-yr time period is covered by six consecutive satellites (Meteosat-2–7). To correct for possible systematic differences between instruments on the different satellite platforms, a time series of Meteosat infrared observations over cloud-free ocean surfaces was compared to reanalysis-based radiative transfer results. Based on the comparison of simulations with observations, a homogenization was performed for the MVIRI infrared channel. The homogenized 20-yr dataset was then subjected to a tracking analysis for deep convection over Africa and the tropical Atlantic for the boreal summer months of July–September. The mean state of convection as well as anomalies for high– and low–Sahel rainfall years were studied. Comparisons with the Global Precipitation Climatology Center’s (GPCC) rainfall estimates were performed for the Sahel region and interannual variability was evaluated comparing convection for the five driest and five wettest Sahel years. Results support earlier findings that precipitation in the Sahel region is strongly linked to the latitudinal position of the African Easterly Jet with deep convection being triggered more strongly if the jet is displaced northward. A relationship between the jet position and long-lived convective systems over the tropical Atlantic was found as well.

A 10-year climatology of warm-season cloud patterns over Europe and the Mediterranean from Meteosat IR observations

Thermal infrared (IR, 10.5–12.5 μm) images from the Meteosat Visible and InfraRed Imager (MVIRI) of cold cloud episodes (cloud top brightness temperature < 241 K) are used as a proxy of precipitating clouds to derive a warm-season (May–August) climatology of their coherency, duration, span, and propagation speed over Europe and the Mediterranean. The analysis focuses over the 30°–54° N, 15°W–40°E domain in May–August 1996–2005. Harmonic analysis using discrete Fourier transforms is applied together with a statistical analysis and an investigation of the diurnal cycle. The objective of the study is to make available a set of results on the propagation dynamics of the cloud systems with the aim of assisting numerical modellers in improving summer convection parameterization. The zonal propagation of cold cloud systems is accompanied by a weak meridional component confined to narrow latitude belts. The persistence of cold clouds over the area evidences the role of orography, the Pyrenees, the Alps, the Balkans and Anatolia. A diurnal oscillation is found with a maximum marking the initiation of convection in the lee of the mountains and shifting from about 1400 UTC at 40°E to 1800 UTC at 0°. A moderate eastward propagation of the frequency maximum from all mountain chains across the domain exists and the diurnal maxima are completely suppressed west of 5°W. The mean power spectrum of the cold cloud frequency distribution evidences a period of one day all over Europe disappearing over the ocean (west of 10°W). Other maxima are found in correspondence of 3 to 7 day synoptic activity. A median zonal phase speed of 16.1 m s − 1 is found for all events ≥ 1000 km and ≥ 20 h and a full set of results divided by year and recurrence categories is also presented. The maxima of the diurnal signal are in phase with the presence of elevated terrain and with land masses.

Aerosol characterization and optical thickness retrievalsusing GOME and METEOSAT satellite data

¶Retrievals of atmospheric aerosol optical thickness are highly dependent on the choice of the class describing the aerosol properties leading to significant errors while using classes available in the literature. High spectral resolution measurements from GOME (Global Ozone Monitoring Experiment) between the ultraviolet and the near infrared can be used for an accurate characterization of the aerosol optical properties. The radiometer MVIRI (METEOSAT Visible and Infrared Imager) on board the geostationary satellite METEOSAT, while being equipped only with broadband VIS channel, ensures an adequate half-hourly monitoring of the atmospheric conditions over a large portion of the Earth. The present algorithm is based on a combination of data from both sensors for the retrieval of the aerosol optical thickness at the reference wavelength of 0.55 µm (AOT). A case of a desert dust outbreak from the African continent over the Atlantic Ocean is examined. AOT values obtained using a priori fixed classes taken from the literature are compared with those retrieved with this algorithm using the GOME-derived classes. Systematic differences of the order of a few tenths on average are found which remain significant also after considering the measurement errors. This represents a novelty introduced by the synergetic use of both sensors.

Potential of MSG for surface temperature and emissivity estimation: Considerations for real-time applications

Meteosat Second Generation (MSG) will provide data with an unprecedented combination of spatial, temporal, and spectral resolutions from geostationary orbit for Africa, and most of Europe and the Atlantic ocean. This article focuses on the potential of MSG's Spinning Enhanced Visible and Infrared Imager (SEVIRI) for Land Surface Temperature (LST) and emissivity estimation. SEVIRI's advantages over the Meteosat Visible and Infrared Imager (MVIRI) and the National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) are outlined. On the basis of SEVIRI's spectral and temporal resolutions the Thermal Infrared Spectral Indices (TISI) day/night method is selected for estimating emissivity. The concept of using the Sun as an active source in the 3-4 w m window is summarized and SEVIRI-specific coefficients required by the TISI day/night method are supplied. The sensitivity of the method to atmospheric conditions and to surface emissivity is analysed using simulated radiances for standard atmospheres and channel emissivities derived from spectral laboratory measurements of different surface types. In order to obtain a fast and accurate procedure for the estimation of channel emissivities and LST, the combination of the TISI day/night method with a neural network (NN) for calculating atmospheric variables is proposed.