Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT

Author(s):
Belmonte Rivas, Maria; Stoffelen, Ad
Publication title: Ocean Science
2019
 | Volume: 15 | Issue: 3
2019
DOI: 10.5194/os-15-831-2019
Abstract:
Abstract. This paper analyzes the differences between ERA-Interim and ERA5 surface winds fields relative to Advanced Scatterometer (ASCAT) ocean vecto… Abstract. This paper analyzes the differences between ERA-Interim and ERA5 surface winds fields relative to Advanced Scatterometer (ASCAT) ocean vector wind observations, after adjustment for the effects of atmospheric stability and density, using stress-equivalent winds (U10S) and air–sea relative motion using ocean current velocities. In terms of instantaneous root mean square (rms) wind speed agreement, ERA5 winds show a 20 % improvement relative to ERA-Interim and a performance similar to that of currently operational ECMWF forecasts. ERA5 also performs better than ERA-Interim in terms of mean and transient wind errors, wind divergence and wind stress curl biases. Yet, both ERA products show systematic errors in the partition of the wind kinetic energy into zonal and meridional, mean and transient components. ERA winds are characterized by excessive mean zonal winds (westerlies) with too-weak mean poleward flows in the midlatitudes and too-weak mean meridional winds (trades) in the tropics. ERA stress curl is too cyclonic in midlatitudes and high latitudes, with implications for Ekman upwelling estimates, and lacks detail in the representation of sea surface temperature (SST) gradient effects (along the equatorial cold tongues and Western Boundary Current (WBC) jets) and mesoscale convective airflows (along the Intertropical Convergence Zone and the warm flanks for the WBC jets). It is conjectured that large-scale mean wind biases in ERA are related to their lack of high-frequency (transient wind) variability, which should be promoting residual meridional circulations in the Ferrel and Hadley cells. more
Application Atmosphere Climate Data Records OSI-SAF

CLAAS: the CM SAF cloud property data set using SEVIRI

Author(s):
Stengel, M.; Kniffka, A.; Meirink, J. F.; Lockhoff, M.; Tan, J.; Hollmann, R.
Publication title: Atmospheric Chemistry and Physics
2014
 | Volume: 14 | Issue: 8
2014
DOI: 10.5194/acp-14-4297-2014
Abstract:
Abstract. An 8-year record of satellite-based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived withi… Abstract. An 8-year record of satellite-based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived within the EUMETSAT Satellite Application Facility on Climate Monitoring. The data set is based on SEVIRI measurements of the Meteosat Second Generation satellites, of which the visible and near-infrared channels were intercalibrated with MODIS. Applying two state-of-the-art retrieval schemes ensures high accuracy in cloud detection, cloud vertical placement and microphysical cloud properties. These properties were further processed to provide daily to monthly averaged quantities, mean diurnal cycles and monthly histograms. In particular, the per-month histogram information enhances the insight in spatio-temporal variability of clouds and their properties. Due to the underlying intercalibrated measurement record, the stability of the derived cloud properties is ensured, which is exemplarily demonstrated for three selected cloud variables for the entire SEVIRI disc and a European subregion. All data products and processing levels are introduced and validation results indicated. The sampling uncertainty of the averaged products in CLAAS is minimized due to the high temporal resolution of SEVIRI. This is emphasized by studying the impact of reduced temporal sampling rates taken at typical overpass times of polar-orbiting instruments. In particular, cloud optical thickness and cloud water path are very sensitive to the sampling rate, which in our study amounted to systematic deviations of over 10% if only sampled once a day. The CLAAS data set facilitates many cloud related applications at small spatial scales of a few kilometres and short temporal scales of a~few hours. Beyond this, the spatiotemporal characteristics of clouds on diurnal to seasonal, but also on multi-annual scales, can be studied. more
Atmosphere CM-SAF Climate Data Records Validation

CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data

Author(s):
Karlsson, Karl-Göran; Anttila, Kati; Trentmann, Jörg; Stengel, Martin; Fokke Meirink, Jan; Devasthale, Abhay; Hanschmann, Timo; Kothe, Steffen; Jääskeläinen, Emmihenna; Sedlar, Joseph; Benas, Nikos; van Zadelhoff, Gerd-Jan; Schlundt, Cornelia; Stein, Diana; Finkensieper, Stefan; Håkansson, Nina; Hollmann, Rainer
Publication title: Atmospheric Chemistry and Physics
2017
 | Volume: 17 | Issue: 9
2017
DOI: 10.5194/acp-17-5809-2017
Abstract:
Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR dat… Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR data – second edition denoted as CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail, as are some major validation results. Some of the main improvements to the data record come from a major effort in cleaning and homogenizing the basic AVHRR level-1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Arctic summer surface albedo and cloud conditions are provided. more
Atmosphere CM-SAF Climate Data Records Land Validation

CLAAS-3: The third edition of the CM SAF cloud data record based on SEVIRI observations

Author(s):
Benas, N.; Solodovnik, I.; Stengel, M.; Huser, I.; Karlsson, K.-G.; Hakansson, N.; Johansson, E.; Eliasson, S.; Schroder, M.; Hollmann, R.; Meirink, J.F.
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 11
2023
DOI: 10.5194/essd-15-5153-2023
Abstract:
CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI (Spinning Enhanced Visible and InfraRed Imager), was released in December 2022. … CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI (Spinning Enhanced Visible and InfraRed Imager), was released in December 2022. It is based on observations from SEVIRI, on board geostationary satellites Meteosat-8, 9, 10 and 11, which are operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). CLAAS-3 was produced and released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF), which aims to provide high-quality satellite-based data records suitable for climate monitoring applications. Compared to previous CLAAS releases, CLAAS-3 is expanded in terms of both temporal extent and cloud properties included, and it is based on partly updated retrieval algorithms. The available data span the period from 2004 to present, covering Europe; Africa; the Atlantic Ocean; and parts of South America, the Middle East and the Indian Ocean. They include cloud fractional coverage, cloud-top height, phase (liquid or ice) and optical and microphysical properties (water path, optical thickness, effective radius and droplet number concentration), from instantaneous data (every 15min) to monthly averages. In this study we present an extensive evaluation of CLAAS-3 cloud properties, based on independent reference data sets. These include satellite-based retrievals from active and passive sensors, ground-based observations and in situ measurements from flight campaigns. Overall results show very good agreement, with small biases attributable to different sensor characteristics, retrieval/sampling approaches and viewing/illumination conditions. These findings demonstrate the fitness of CLAAS-3 to support the intended applications, which include evaluation of climate models, cloud characterisation and process studies focusing especially on the diurnal cycle and cloud filtering for other applications. The CLAAS-3 data record is publicly available via the CM SAF website at 10.5676/EUM_SAF_CM/CLAAS/V003 (Meirink et al., 2022). © 2023 Copernicus GmbH. All rights reserved. more
Atmosphere CM-SAF Climate Data Records Validation

Climate data integration into wheat performance evaluation reveals large inter-varietal responses

Author(s):
Raymond, Joanna; Penfield, Steven; Lovett, Andrew; Mackay, Ian; Philpott, Haidee; Simpson, Conor John Christopher; Dorling, Stephen
Publication title: Environmental Research: Food Systems
2024
 | Volume: 2 | Issue: 1
2024
DOI: 10.1088/2976-601X/ad90e4
Abstract:
There is an urgent need to adapt crop breeding strategies to boost resilience in the face of a growing food demand and a changing climate. Achieving t… There is an urgent need to adapt crop breeding strategies to boost resilience in the face of a growing food demand and a changing climate. Achieving this requires an understanding of how weather and climate variability impacts crop growth and development. Using the United Kingdom (UK) as an example, we evaluate changes in the UK agroclimate and analyse how these have influenced domestic wheat production. Here we quantify spatial and temporal variability and changes in weather and climate across growing seasons over the last four decades (1981–2020). Drawing on variety trial data, we then use statistical modelling to explore the interaction between genotype and agroclimate variation. We show that changes in the UK agroclimate present both risks, and opportunities for wheat growers, depending on location. From 1981–2020, in Wales, the West Midlands, large parts of the North West, and Northern Ireland, there was an overall increase in frost risk in early spring of 0.15 additional frost days per year, whilst in the east early frost risk decreased by up to 0.29 d per year. Meanwhile, over the period 1987–2020, surface incoming shortwave radiation during grainfill increased in the east by up to 13% but decreased in Western areas by up to 15%. We show significant inter-varietal differences in yield responses to growing degree days, heavy rainfall, and the occurrence of late frost. This highlights the importance of evaluating variety-climate interactions in variety trial analyses, and in climate-optimised selection of crops and varieties by growers. This work provides guidance for future research on how climate change is affecting the UK agroclimate and resulting impacts on winter cereal production. more
Application Atmosphere CM-SAF Climate Data Records Terrestrial

CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023

Author(s):
Karlsson, Karl-Göran; Stengel, Martin; Meirink, Jan Fokke; Riihelä, Aku; Trentmann, Jörg; Akkermans, Tom; Stein, Diana; Devasthale, Abhay; Eliasson, Salomon; Johansson, Erik; Håkansson, Nina; Solodovnik, Irina; Benas, Nikos; Clerbaux, Nicolas; Selbach, Nathalie; Schröder, Marc; Hollmann, Rainer
Publication title: Earth System Science Data
2023
 | Volume: 15 | Issue: 11
2023
DOI: 10.5194/essd-15-4901-2023
Abstract:
This paper presents the third edition of The Satellite Application Facility on Climate Monitoring's (CM SAF) cloud, albedo, and surface radiation data… This paper presents the third edition of The Satellite Application Facility on Climate Monitoring's (CM SAF) cloud, albedo, and surface radiation dataset from advanced very-high-resolution radiometer (AVHRR) data, CLARA-A3. The content of earlier CLARA editions, namely cloud, surface albedo, and surface radiation products, has been extended with two additional surface albedo products (blue- and white-sky albedo), three additional surface radiation products (net shortwave and longwave radiation, and surface radiation budget), and two top of atmosphere radiation budget products (reflected solar flux and outgoing longwave radiation). The record length is extended to 42 years (1979–2020) by also incorporating results from the first version of the advanced very high resolution radiometer imager (AVHRR/1). A continuous extension of the climate data record (CDR) has also been implemented by processing an interim climate data record (ICDR) based on the same set of algorithms but with slightly changed ancillary input data. All products are briefly described together with validation results and intercomparisons with currently existing similar CDRs. The extension of the product portfolio and the temporal coverage of the data record, together with product improvements, is expected to enlarge the potential of using CLARA-A3 for climate change studies and, in particular, studies of potential feedback effects between clouds, surface albedo, and radiation. The CLARA-A3 data record is hosted by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) CM SAF and is freely available at https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V003 (Karlsson et al., 2023b). more
Atmosphere CM-SAF Climate Data Records EUM-Secr Land Method OSI-SAF Validation

Climate Data Records from Meteosat First Generation Part I: Simulation of Accurate Top-of-Atmosphere Spectral Radiance over Pseudo-Invariant Calibration Sites for the Retrieval of the In-Flight Visible Spectral Response

Author(s):
Govaerts, Yves; Rüthrich, Frank; John, Viju; Quast, Ralf
Publication title: Remote Sensing
2018
 | Volume: 10 | Issue: 12
2018
DOI: 10.3390/rs10121959
Abstract:
Meteosat First-Generation satellites have acquired more than 30 years of observations that could potentially be used for the generation of a Climate D… Meteosat First-Generation satellites have acquired more than 30 years of observations that could potentially be used for the generation of a Climate Data Record. The availability of harmonized and accurate a Fundamental Climate Data Record is a prerequisite to such generation. Meteosat Visible and Infrared Imager radiometers suffer from inaccurate pre-launch spectral function characterization and spectral ageing constitutes a serious limitation to achieve such prerequisite. A new method was developed for the retrieval of the pre-launch instrument spectral function and its ageing. This recovery method relies on accurately simulated top-of-atmosphere spectral radiances matching observed digital count values. This paper describes how these spectral radiances are simulated over pseudo-invariant targets such as open ocean, deep convective clouds and bright desert surface. The radiative properties of these targets are described with a limited number of parameters of known uncertainty. Typically, a single top-of-atmosphere radiance spectrum can be simulated with an estimated uncertainty of about 5%. The independent evaluation of the simulated radiance accuracy is also addressed in this paper. It includes two aspects: the comparison with narrow-band well-calibrated radiometers and a spectral consistency analysis using SEVIRI/HRVIS band on board Meteosat Second Generation which was accurately characterized pre-launch. On average, the accuracy of these simulated spectral radiances is estimated to be about ±2%. more
Application Climate Data Records EUM-Secr Method

Climate of Syria Based on Cordex Simulations: Present and Future

Author(s):
Naaouf, N.; Torma, C.Z.
Publication title: Earth Systems and Environment
2023
 | Volume: 7 | Issue: 3
2023
DOI: 10.1007/s41748-023-00351-3
Abstract:
Regional climate models are widely used to assess current and future impacts of climate change. In this study, we evaluate the performance of regional… Regional climate models are widely used to assess current and future impacts of climate change. In this study, we evaluate the performance of regional climate models from the Coordinated Regional Climate Downscaling Experiment programme integrated over the following three CORDEX domains: AFR, MNA and WAS. Four meteorological variables (temperature, precipitation, solar radiation and cloud cover) were evaluated over Syria at a grid spacing of 0.44°. The performance of five models in simulating the present climate characteristics (1989–2008) is evaluated with respect to the observations: CRU, ERA5 reanalysis and SARA and CLARA satellite data. We find that the mini-ensemble captures well the general spatial patterns and annual cycles of the selected variables. Anotheraim of this study was to assess the expected change of the mentioned four climate variables over Syria under the moderate emission scenario (RCP4.5) and the high emission scenario (RCP8.5) in the near future (2031–2050) and in the far future (2080–2099) with respect to the present climate (1989–2008). The simulations show a decreasing trend in cloud cover (between 6% and 10%) and precipitation (up to 9%) by mid and late century, regardless of the forcing scenarios. The simulations show a pronounced warming over Syria, which is expected to reach 6 °C by the end of the twenty-first century following the high greenhouse gas concentration scenario (RCP8.5). Furthermore, such an increase, combined with a decrease in precipitation, will shift Syria’s climate towards a more arid one. © 2023, The Author(s). more
Atmosphere CM-SAF Climate Data Records Validation

Climate Data Records from Meteosat First Generation Part II: Retrieval of the In-Flight Visible Spectral Response

Author(s):
Quast, Ralf; Giering, Ralf; Govaerts, Yves; Rüthrich, Frank; Roebeling, Rob
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 5
2019
DOI: 10.3390/rs11050480
Abstract:
How can the in-flight spectral response functions of a series of decades-old broad band radiometers in Space be retrieved post-flight? This question i… How can the in-flight spectral response functions of a series of decades-old broad band radiometers in Space be retrieved post-flight? This question is the key to developing Climate Data Records from the Meteosat Visible and Infrared Imager on board the Meteosat First Generation (MFG) of geostationary satellites, which acquired Earth radiance images in the Visible (VIS) broad band from 1977 to 2017. This article presents a new metrologically sound method for retrieving the VIS spectral response from matchups of pseudo-invariant calibration site (PICS) pixels with datasets of simulated top-of-atmosphere spectral radiance used as reference. Calibration sites include bright desert, open ocean and deep convective cloud targets. The absolute instrument spectral response function is decomposed into generalised Bernstein basis polynomials and a degradation function that is based on plain physical considerations and able to represent typical chromatic ageing characteristics. Retrieval uncertainties are specified in terms of an error covariance matrix, which is projected from model parameter space into the spectral response function domain and range. The retrieval method considers target type-specific biases due to errors in, e.g., the selection of PICS target pixels and the spectral radiance simulation explicitly. It has been tested with artificial and well-comprehended observational data from the Spinning Enhanced Visible and Infrared Imager on-board Meteosat Second Generation and has retrieved meaningful results for all MFG satellites apart from Meteosat-1, which was not available for analysis. more
Application Climate Data Records EUM-Secr Method

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

Author(s):
Rüthrich, Frank; John, Viju O.; Roebeling, Rob A.; Quast, Ralf; Govaerts, Yves; Woolliams, Emma R.; Schulz, Jörg
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 10
2019
DOI: 10.3390/rs11101165
Abstract:
This paper presents a new Fundamental Climate Data Record (FCDR) for the visible (VIS) channel of the Meteosat Visible and Infrared Imager (MVIRI), wi… 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. more
Application Climate Data Records EUM-Secr Validation
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