Life Cycle of Shallow Marine Cumulus Clouds From Geostationary Satellite Observations

Author(s):
Seelig, Torsten; Deneke, Hartwig; Quaas, Johannes; Tesche, Matthias
Publication title: JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
2021
 | Volume: 126 | Issue: 22
2021
DOI: 10.1029/2021JD035577
Abstract:
An analysis of the life cycle of shallow marine cumulus clouds is presented based on geostationary observations by the Spinning Enhanced Visible and I… An analysis of the life cycle of shallow marine cumulus clouds is presented based on geostationary observations by the Spinning Enhanced Visible and InfraRed Imager aboard Meteosat Second Generation (MSG-SEVIRI). Trajectories of about 250,000 individual shallow marine cumulus clouds have been derived by applying Particle Image Velocimetry to the Satellite Application Facility on Climate Monitoring CLoud property dAtAset using SEVIRI for a region in the trade wind zone centered around the Canary Islands in August 2015. The temporal evolution of the physical properties of these clouds allows to characterize cloud development and to infer the distribution of cloud life time and cloud extent. In the derived data set, the life time distribution follows a double power law with most clouds existing on a time scale of tens of minutes. The cloud physical properties, available during daytime, are analyzed along the cloud tracks. Relative time series of cloud extent, cloud water path, cloud droplet effective radius at cloud top, cloud optical thickness, and cloud droplet number concentration for clouds in two temporal ranges reveal conditions that can be attributed to long-lasting clouds. Clouds of a certain horizontal extent and cloud top height as well as cloud droplet radius show longer life times if they are optically more dense, i.e., have a higher droplet number concentration. Furthermore, the investigation of the content of liquid cloud water regarding cloud life time and cloud extent shows that small short-living clouds significantly contribute to cloud radiative effects. more
Application Atmosphere CM-SAF Climate Data Records

Limited Benefits of Increased Spatial Resolution for Sea Ice in HighResMIP Simulations

Author(s):
Selivanova, J.; Iovino, D.; Vichi, M.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 14
2024
DOI: 10.1029/2023GL107969
Abstract:
State-of-the-art coupled climate models struggle to accurately simulate historical variability and trends of Antarctic sea ice, impacting their reliab… State-of-the-art coupled climate models struggle to accurately simulate historical variability and trends of Antarctic sea ice, impacting their reliability for future projections. Increasing horizontal resolution is expected to improve the representation of coupled atmosphere-ice-ocean processes at high latitudes. Here, we examine the historical changes in the Antarctic sea ice area and volume in High Resolution Model Intercomparison Project simulations against satellite data sets and ocean reanalyzes to assess the benefits of increased spatial resolution. Our results do not show considerable benefits when horizontal resolutions up to 0.25° in the ocean and 25 km in the atmosphere. Limited improvements are reported in the simulated historical sea ice trends, which are nevertheless model-dependent, and associated with the use of model components with more complex sea-ice parameterizations. Given the high computational cost of climate-scale simulations at high spatial resolution, we advocate prioritizing enhancements in sea-ice physics and the interactions among model components in coupled climate simulations. © 2024. The Author(s). more
Application Climate Data Records Cryosphere OSI-SAF Validation

Linking scales of sea ice surface topography: evaluation of ICESat-2 measurements with coincident helicopter laser scanning during MOSAiC

Author(s):
Ricker, R; Fons, S; Jutila, A; Hutter, N; Duncan, K; Farrell, SL; Kurtz, NT; Hansen, RMF
Publication title: CRYOSPHERE
2023
 | Volume: 17 | Issue: 3
2023
DOI: 10.5194/tc-17-1411-2023
Abstract:
Information about sea ice surface topography and related deformation is crucial for studies of sea ice mass balance, sea ice modeling, and ship naviga… Information about sea ice surface topography and related deformation is crucial for studies of sea ice mass balance, sea ice modeling, and ship navigation through the ice pack. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), part of the National Aeronautics and Space Administration (NASA) Earth Observing System, has been on orbit for over 4 years, sensing the sea ice surface topography with six laser beams capable of capturing individual features such as pressure ridges. To assess the capabilities and uncertainties of ICESat-2 products, coincident high-resolution measurements of sea ice surface topography are required. During the yearlong Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the Arctic Ocean, we successfully carried out a coincident underflight of ICESat-2 with a helicopter-based airborne laser scanner (ALS), achieving an overlap of more than 100 km. Despite the comparably short data set, the high-resolution centimeter-scale measurements of the ALS can be used to evaluate the performance of ICESat-2 products. Our goal is to investigate how the sea ice surface roughness and topography are represented in different ICESat-2 products as well as how sensitive ICESat-2 products are to leads and small cracks in the ice cover. Here, we compare the ALS measurements with ICESat-2's primary sea ice height product, ATL07, and the high-fidelity surface elevation product developed by the University of Maryland (UMD). By applying a ridge-detection algorithm, we find that 16 % (4 %) of the number of obstacles in the ALS data set are found using the strong (weak) center beam in ATL07. Significantly higher detection rates of 42 % (30 %) are achieved when using the UMD product. While only one lead is indicated in ATL07 for the underflight, the ALS reveals many small, narrow, and only partly open cracks that appear to be overlooked by ATL07. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Long-Term Variations and Its Driving Factors of the TOA Albedo over the Loess Plateau

Author(s):
Wang, Qianru; Zhang, Shuhua
2024
2024
DOI: 10.1175/JCLI-D-23-0380.1
Abstract:
Solar radiation balances significantly affect Earth’s surface energy balance and climate change. Studying top-of-the-atmosphere (TOA) albedo changes i… Solar radiation balances significantly affect Earth’s surface energy balance and climate change. Studying top-of-the-atmosphere (TOA) albedo changes is of great significance for understanding Earth’s energy budget and atmospheric circulation. The Loess Plateau (LP), located in the middle reaches of the Yellow River in China, is one of the most severely eroded areas in the world. In this paper, long-term remote sensing data were used to analyze the changes in the TOA albedo in the LP from 1982 to 2016. The results showed that the TOA albedo, its atmospheric contribution (AC), and surface contribution (SC) exhibited decreasing trends: −0.0012, −0.0010, and −0.0003 a−1. The spatial pattern of the TOA albedo was similar to AC, which indicates that AC dominates the change in the TOA albedo. We detected driving factors for AC and SC and found that the cloud fraction (CF) was the main driving factor of the AC, whereas the soil moisture (SM) dominated the SC. The driving factors of two typical regions with a significantly decreasing trend in the TOA albedo were also detected. The Mu Us Desert, where vegetation improved significantly, showed a decreasing trend in the TOA albedo, and we found that NDVI was the main driving factor for the change in the SC of the TOA albedo. However, the Eastern Qilian Mountains, where snow cover decreased in recent years, also showed a significant decreasing trend in the TOA albedo; the SC here was mainly driven by the changes in snow cover days (SCD). These results indicate that changes in the surface environment alter the radiation balance. Significance Statement The Loess Plateau in China is one of the most severe cases of soil erosion in the world, and ecological restoration projects have been carried out to recover the fragile ecological environment. Our study was designed to explore changes in the top-of-the-atmosphere (TOA) albedo of the Loess Plateau between 1982 and 2016 using a long time series of multisource satellite products, and driving factors in the atmosphere and at the surface were analyzed. We concluded that the TOA albedo of the Loess Plateau decreased over 35 years, and its atmospheric contribution dominated the change in the TOA albedo. However, the significant ecological improvement in the Loess Plateau, especially in the central vegetation recovery region, such as the Mu Us Desert, was also strongly related to the regional changes in the surface contribution of the TOA albedo. The climate changes had a considerable impact on the eastern branch of the Qilian Mountains in the Qinghai region, where the decline in snow cover days affected the local Alpine meadow ecosystems; therefore, snow cover days also played a decisive role in the local variation of the surface contribution of the TOA albedo. more
Application Atmosphere CM-SAF Climate Data Records Terrestrial

Local analytical optimal nudging for assimilating AMSR2 sea ice concentration in a high-resolution pan-Arctic coupled ocean (HYCOM 2.2.98) and sea ice (CICE 5.1.2) model

Author(s):
Wang, K.; Ali, A.; Wang, C.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 10
2023
DOI: 10.5194/tc-17-4487-2023
Abstract:
Local analytical optimal nudging (LAON) is introduced and thoroughly evaluated for assimilating the Advanced Microwave Scanning Radiometer 2 (AMSR2) s… Local analytical optimal nudging (LAON) is introduced and thoroughly evaluated for assimilating the Advanced Microwave Scanning Radiometer 2 (AMSR2) sea ice concentration (SIC) in the Norwegian High-resolution pan-Arctic ocean and sea ice Prediction System (NorHAPS). NorHAPS is a developing high-resolution (3-5 km) pan-Arctic coupled ocean and sea ice modeling and prediction system based on the HYbrid Coordinate Ocean Model (HYCOM version 2.2.98) and the Los Alamos multi-category sea ice model (CICE version 5.1.2), with the LAON for data assimilation. In this study, our focus is on the LAON assimilation of AMSR2 SIC, which is designed to update the model SIC in every time step such that the analysis will eventually reach the optimal estimate. The SIC innovation (observation minus model) is designed to be proportionally distributed to the multiple sea ice categories. A hindcast experiment is performed with and without the LAON assimilation for the period 1 January 2021 to 30 April 2022, in which the extra computational cost for the LAON assimilation is about 5 % of the free run without assimilation. The results show that the LAON assimilation greatly improves the simulated sea ice concentration, extent, area, thickness, and volume, as well as the sea surface temperature (SST). It also produces significantly more accurate sea ice edge and marginal zone (MIZ) than the observed AMSR2 SIC that is assimilated when evaluated against the Norwegian Ice Service (NIS) ice chart. The results are also compared with the Copernicus Marine Environment Monitoring Service (CMEMS) operational SIC analyses from NEMO, TOPAZ4, and neXtSIM, which use ensemble Kalman filters and direct insertion for data assimilation. It is shown that the LAON assimilation produces significantly lower integrated ice edge error (IIEE) and integrated MIZ error (IME) than the CMEMS SIC analyses when evaluated against the NIS ice chart. LAON also produces a continuous and smooth evolution of sub-daily SIC, which avoids abrupt jumps often seen in other assimilated products. This efficient and accurate method is promising for data assimilation in global and high-resolution models. © 2023 Keguang Wang et al. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Long-Term Scatterometer Wind Climate Data Records

Author(s):
Verhoef, Anton; Vogelzang, Jur; Verspeek, Jeroen; Stoffelen, Ad
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
 | Volume: 10 | Issue: 5
2017
DOI: 10.1109/JSTARS.2016.2615873
Abstract:
The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) prod… The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) produces near-real-time scatterometer ocean vector winds since almost 20 years already. Data from the European remote sensing satellites (ERS-1 and ERS-2 scatterometer), QuikSCAT (SeaWinds), Metop (ASCAT), Oceansat 2 (OSCAT), and RapidScat on the International Space Station have been, or are being, produced. The OSI SAF scatterometer products, produced at the Royal Netherlands Meteorological Institute, provide superior comparison to both buoy and numerical weather prediction (NWP) datasets. Moreover, the wind processing software is publicly available through the EUMETSAT NWP SAF. An increasing amount of users employs scatterometer wind data for climate studies. However, the wind retrieval algorithms have been continuously improved over the years and the currently existing archives of near-real-time data are not always suitable to fulfill the need for homogeneous datasets spanning a longer period of time. Currently, only few validated vector wind climate datasets are available. Therefore, the OSI SAF is reprocessing several offline datasets. This paper is focusing on two climate data records from SeaWinds and ASCAT winds, which together span the period from 1999 to 2014. The data are compared to the NWP model and buoy winds. The stability of the wind characteristics is assessed and an attempt is made to attribute temporal changes to climatological and NWP model changes over time. more
Atmosphere Climate Data Records OSI-SAF Validation

LSA SAF Meteosat FRP products – Part 2: Evaluation and demonstration for use in the Copernicus Atmosphere Monitoring Service (CAMS)

Author(s):
Roberts, G.; Wooster, M. J.; Xu, W.; Freeborn, P. H.; Morcrette, J.-J.; Jones, L.; Benedetti, A.; Jiangping, H.; Fisher, D.; Kaiser, J. W.
Publication title: Atmospheric Chemistry and Physics
2015
 | Volume: 15 | Issue: 22
2015
DOI: 10.5194/acp-15-13241-2015
Abstract:
Characterising the dynamics of landscape-scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation … Characterising the dynamics of landscape-scale wildfires at very high temporal resolutions is best achieved using observations from Earth Observation (EO) sensors mounted onboard geostationary satellites. As a result, a number of operational active fire products have been developed from the data of such sensors. An example of which are the Fire Radiative Power (FRP) products, the FRP-PIXEL and FRP-GRID products, generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from imagery collected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) series of geostationary EO satellites. The processing chain developed to deliver these FRP products detects SEVIRI pixels containing actively burning fires and characterises their FRP output across four geographic regions covering Europe, part of South America and Northern and Southern Africa. The FRP-PIXEL product contains the highest spatial and temporal resolution FRP data set, whilst the FRP-GRID product contains a spatio-temporal summary that includes bias adjustments for cloud cover and the non-detection of low FRP fire pixels. Here we evaluate these two products against active fire data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and compare the results to those for three alternative active fire products derived from SEVIRI imagery. The FRP-PIXEL product is shown to detect a substantially greater number of active fire pixels than do alternative SEVIRI-based products, and comparison to MODIS on a per-fire basis indicates a strong agreement and low bias in terms of FRP values. However, low FRP fire pixels remain undetected by SEVIRI, with errors of active fire pixel detection commission and omission compared to MODIS ranging between 9–13 % and 65–77 % respectively in Africa. Higher errors of omission result in greater underestimation of regional FRP totals relative to those derived from simultaneously collected MODIS data, ranging from 35 % over the Northern Africa region to 89 % over the European region. High errors of active fire omission and FRP underestimation are found over Europe and South America and result from SEVIRI's larger pixel area over these regions. An advantage of using FRP for characterising wildfire emissions is the ability to do so very frequently and in near-real time (NRT). To illustrate the potential of this approach, wildfire fuel consumption rates derived from the SEVIRI FRP-PIXEL product are used to characterise smoke emissions of the 2007 "mega-fire" event focused on Peloponnese (Greece) and used within the European Centre for Medium-Range Weather Forecasting (ECMWF) Integrated Forecasting System (IFS) as a demonstration of what can be achieved when using geostationary active fire data within the Copernicus Atmosphere Monitoring Service (CAMS). Qualitative comparison of the modelled smoke plumes with MODIS optical imagery illustrates that the model captures the temporal and spatial dynamics of the plume very well, and that high temporal resolution emissions estimates such as those available from a geostationary orbit are important for capturing the sub-daily variability in smoke plume parameters such as aerosol optical depth (AOD), which are increasingly less well resolved using daily or coarser temporal resolution emissions data sets. Quantitative comparison of modelled AOD with coincident MODIS and AERONET (Aerosol Robotic Network) AOD indicates that the former is overestimated by ~ 20–30 %, but captures the observed AOD dynamics with a high degree of fidelity. The case study highlights the potential of using geostationary FRP data to drive fire emissions estimates for use within atmospheric transport models such as those implemented in the Monitoring Atmospheric Composition and Climate (MACC) series of projects for the CAMS. more
Climate Data Records LSA-SAF Land Validation

Making better sense of the mosaic of environmental measurement networks: a system-of-systems approach and quantitative assessment

Author(s):
Thorne, Peter W.; Madonna, Fabio; Schulz, Joerg; Oakley, Tim; Ingleby, Bruce; Rosoldi, Marco; Tramutola, Emanuele; Arola, Antti; Buschmann, Matthias; Mikalsen, Anna C.; Davy, Richard; Voces, Corinne; Kreher, Karin; De Maziere, Martine; Pappalardo, Gelsomina
Publication title: Geoscientific Instrumentation, Methods and Data Systems
2017
 | Volume: 6 | Issue: 2
2017
DOI: 10.5194/gi-6-453-2017
Abstract:
Abstract. There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and ope… Abstract. There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies, etc. The Horizon 2020 project GAIA–CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is correct. Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available and maintains rich metadata. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based on such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate on networks measuring primarily a subset of the atmospheric Essential Climate Variables of interest to GAIA–CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream example applications of the GAIA–CLIM project. However, the approach laid out should be more widely applicable across a broad range of application areas. If broadly adopted, the system-of-systems approach will have potential benefits in guiding users to the most appropriate set of observations for their needs and in highlighting to network owners and operators areas for potential improvement. more
EUM-Secr International cooperation Validation

Mapping long-term and high-resolution global gridded photosynthetically active radiation using the ISCCP H-series cloud product and reanalysis data

Author(s):
Tang, Wenjun; Qin, Jun; Yang, Kun; Jiang, Yaozhi; Pan, Weihao
Publication title: EARTH SYSTEM SCIENCE DATA
2022
 | Volume: 14 | Issue: 4
2022
DOI: 10.5194/essd-14-2007-2022
Abstract:
Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fiel… Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fields. In this study, we produced a 35-year (1984-2018) high-resolution (3 h, 10 km) global gridded PAR dataset using an effective physical-based model. The main inputs of the model were the latest International Satellite Cloud Climatology Project (ISCCP) H-series cloud products, MERRA-2 aerosol data, ERA5 surface routine variables, and MODIS and CLARRA-2 albedo products. Our gridded PAR product was evaluated against surface observations measured at 7 experimental stations of the SURFace RADiation budget network (SURFRAD), 42 experimental stations of the National Ecological Observatory Network (NEON), and 38 experimental stations of the Chinese Ecosystem Research Network (CERN). Instantaneous PAR was validated against SURFRAD and NEON data; mean bias errors (MBE) and root mean square errors (RMSE) were, on average 5.8 and 44.9 W m(-2), respectively, and the correlation coefficient (R) was 0.94 at the 10 km scale. When upscaled to 30 km, the errors were markedly reduced. Daily PAR was validated against SURFRAD, NEON, and CERN data, and the RMSEs were 13.2, 13.1, and 19.6 W m(-2,) respectively, at the 10 km scale. The RMSEs were slightly reduced when upscaled to 30 km. Compared with the well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES), our PAR product was found to be a more accurate dataset with higher resolution. This new dataset is now available at https://doi.org/10.11888/RemoteSen.tpdc.271909 (Tang, 2021). more
Application CM-SAF Climate Data Records Land
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