Quantifying the Impact of Aerosols on Geostationary Satellite Infrared Radiance Simulations: A Study with Himawari-8 AHI

Author(s):
Sun, H.; Wang, D.; Han, W.; Yang, Y.
Publication title: Remote Sensing
2024
 | Volume: 16 | Issue: 12
2024
DOI: 10.3390/rs16122226
Abstract:
Aerosols exert a significant influence on the brightness temperature observed in the thermal infrared (IR) channels, yet the specific contributions of… Aerosols exert a significant influence on the brightness temperature observed in the thermal infrared (IR) channels, yet the specific contributions of various aerosol types remain underexplored. This study integrated the Copernicus Atmosphere Monitoring Service (CAMS) atmospheric composition reanalysis data into the Radiative Transfer for TOVS (RTTOV) model to quantify the aerosol effects on brightness temperature (BT) simulations for the Advanced Himawari Imager (AHI) aboard the Himawari-8 geostationary satellite. Two distinct experiments were conducted: the aerosol-aware experiment (AER), which accounted for aerosol radiative effects, and the control experiment (CTL), in which aerosol radiative effects were omitted. The CTL experiment results reveal uniform negative bias (observation minus background (O-B)) across all six IR channels of the AHI, with a maximum deviation of approximately −1 K. Conversely, the AER experiment showed a pronounced reduction in innovation, which was especially notable in the 10.4 μm channel, where the bias decreased by 0.7 K. The study evaluated the radiative effects of eleven aerosol species, all of which demonstrated cooling effects in the AHI’s six IR channels, with dust aerosols contributing the most significantly (approximately 86%). In scenarios dominated by dust, incorporating the radiative effect of dust aerosols could correct the brightness temperature bias by up to 2 K, underscoring the substantial enhancement in the BT simulation for the 10.4 μm channel during dust events. Jacobians were calculated to further examine the RTTOV simulations’ sensitivity to aerosol presence. A clear temporal and spatial correlation between the dust concentration and BT simulation bias corroborated the critical role of the infrared channel data assimilation on geostationary satellites in capturing small-scale, rapidly developing pollution processes. © 2024 by the authors. more
Atmosphere Method NWP-SAF Software for CDR development

Radiative Effect of Two Contrail Cirrus Outbreaks Over Western Europe Estimated Using Geostationary Satellite Observations and Radiative Transfer Calculations

Author(s):
Wang, X.; Wolf, K.; Boucher, O.; Bellouin, N.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 7
2024
DOI: 10.1029/2024GL108452
Abstract:
Estimation of the perturbation to the Earth's energy budget by contrail outbreaks is required for estimating the climate impact of aviation and verify… Estimation of the perturbation to the Earth's energy budget by contrail outbreaks is required for estimating the climate impact of aviation and verifying the climate benefits of proposed contrail avoidance strategies such as aircraft rerouting. Here we identified two successive large-scale contrail outbreaks developing in clear-sky conditions in geostationary and polar-orbiting satellite infrared images of Western Europe lasting from 22–23 June 2020. Their hourly cloud radiative effect, obtained using geostationary satellite cloud retrievals and radiative transfer calculations, is negative or weakly positive during daytime and positive during nighttime. The cumulative energy forcing of the two outbreaks is 7 PJ and −8.5 PJ, with uncertainties of 3 PJ, stemming each from approximately 15–20 flights over periods of 19 and 7 hr, respectively. This study suggests that an automated quantification of contrail outbreak radiative effect is possible, at least for contrails forming in clear sky conditions. © 2024. The Authors. more
Application Atmosphere Climate Data Records EUM-Secr

Radiometric Calibration of the Advanced Wind Scatterometer Radar ASCAT Carried Onboard the METOP-A Satellite

Author(s):
Wilson, J J W; Anderson, C; Baker, M A; Bonekamp, H; Saldaña, J Figa; Dyer, R G; Lerch, J A; Kayal, G; Gelsthorpe, R V; Brown, M A; Schied, E; Schutz-Munz, S; Rostan, F; Pritchard, E W; Wright, N G; King, D; Onel, Ü
Publication title: IEEE Transactions on Geoscience and Remote Sensing
2010
 | Volume: 48 | Issue: 8
2010
DOI: 10.1109/TGRS.2010.2045763
Abstract:
The Advanced Wind Scatterometer (ASCAT) is a six-beam spaceborne radar instrument designed to measure wind fields over the oceans. An ASCAT instrument… The Advanced Wind Scatterometer (ASCAT) is a six-beam spaceborne radar instrument designed to measure wind fields over the oceans. An ASCAT instrument is carried by each of the three METOP satellites. The ASCAT calibration strategy is described and detailed results are presented concerning the radiometric calibration achieved. more
Climate Data Records EUM-Secr Validation

Random forest regression for improved mapping of solar irradiance at high latitudes

Author(s):
Babar, B.; Luppino, L.T.; Boström, T.; Anfinsen, S.N.
Publication title: Solar Energy
2020
 | Volume: 198
2020
DOI: 10.1016/j.solener.2020.01.034
Abstract:
Datasets from meteorological reanalyses and retrievals from satellites are the available sources of large-scale information about solar radiation. How… Datasets from meteorological reanalyses and retrievals from satellites are the available sources of large-scale information about solar radiation. However, both the reanalyses and the satellite-based estimates can be severely biased, especially in high latitude regions. In this study, surface solar irradiance estimates from the ECMWF Reanalysis 5 (ERA5) and the Cloud, Albedo, Radiation dataset Edition 2 (CLARA-A2) were used as input to a random forest regression (RFR) model to construct a novel dataset with higher accuracy and precision than the input datasets. For daily averages of global horizontal irradiance (GHI) at Norwegian sites, CLARA-A2 and ERA5 respectively produced a root mean squared deviation (RMSD) of 17.9 Wm−2 and 27.1 Wm−2, a mean absolute deviation (MAD) of 11.9 Wm−2 and 17.5 Wm−2, and a bias of −1.5 Wm−2 and 4.3 Wm−2. In contrast, the proposed regression model provided an RMSD of 16.2 Wm−2, an MAD of 10.8 Wm−2, and a bias of 0.0 Wm−2. This shows that the RFR model is both accurate and precise, and significantly reduces both dispersion and bias in the new dataset with respect to the constituent sources. A sky-stratification analysis was performed and it was found that the proposed model provides better estimates under all sky conditions with particular improvements in intermediate-cloudy conditions. The proposed regression model was also tested on five Swedish locations and it was found to improve surface solar irradiance estimates to a similar degree as for the Norwegian locations, thus proving its consistency under similar climatic conditions. © 2020 International Solar Energy Society more
Application Atmosphere CM-SAF Climate Data Records

Rapid fCO2 rise in the northern Barents Sea and Nansen Basin

Author(s):
Ericson, Y.; Fransson, A.; Chierici, M.; Jones, E.M.; Skjelvan, I.; Omar, A.; Olsen, A.; Becker, M.
Publication title: Progress in Oceanography
2023
 | Volume: 217
2023
DOI: 10.1016/j.pocean.2023.103079
Abstract:
Maps of surface water fugacity of CO2 (fCO2) over eastern Fram Strait, south-western Nansen Basin, and the north-western Barents Sea (73–84°N, 5–46°E)… Maps of surface water fugacity of CO2 (fCO2) over eastern Fram Strait, south-western Nansen Basin, and the north-western Barents Sea (73–84°N, 5–46°E) from September 1997 to December 2020 were made and used to investigate seasonal and temporal trends. The mapping utilized a neural network technique, the self-organizing map (SOM), that was trained with different combinations of satellite/observational/model data of sea surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), chlorophyll a (Chl a), sea ice concentration, and atmospheric mole fraction of CO2 (xCO2). The trained SOM was labelled with available surface ocean fCO2 data, and the labelled SOM was subsequently used to map the fCO2. The produced maps reveal that fCO2 in northern Barents Sea, at the border of the Nansen Basin, has increased significantly over the last decades by between 4.2 and 5.5 ± 0.6–1.1 µatm yr−1 over the winter to summer seasons. These rates are twice the rate of atmospheric CO2 increase, which was about 2 µatm yr−1. The spatial pattern coincides with the strongest decreases in sea ice concentration as well as with a salinification of the surface water. The former allows for a prolongation of the air-sea CO2 flux with resultant oceanic CO2 uptake in previously ice-covered waters, and the latter is caused by a shift from Arctic Water dominance to more saline waters containing more dissolved inorganic carbon, most likely of Atlantic Water origin although brine-release influenced deep water may also contribute. © 2023 The Authors more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Recent Advances in Satellite Data Rescue

Author(s):
Poli, Paul; Dee, Dick P.; Saunders, Roger; John, Viju O.; Rayer, Peter; Schulz, Jörg; Holmlund, Kenneth; Coppens, Dorothee; Klaes, Dieter; Johnson, James E.; Esfandiari, Asghar E.; Gerasimov, Irina V.; Zamkoff, Emily B.; Al-Jazrawi, Atheer F.; Santek, David; Albani, Mirko; Brunel, Pascal; Fennig, Karsten; Schröder, Marc; Kobayashi, Shinya; Oertel, Dieter; Döhler, Wolfgang; Spänkuch, Dietrich; Bojinski, Stephan
Publication title: Bulletin of the American Meteorological Society
2017
 | Volume: 98 | Issue: 7
2017
DOI: 10.1175/BAMS-D-15-00194.1
Abstract:
Abstract To better understand the impacts of climate change, environmental monitoring capabilities must be enhanced by deploying additional and more a… Abstract To better understand the impacts of climate change, environmental monitoring capabilities must be enhanced by deploying additional and more accurate satellite- and ground-based (including in situ) sensors. In addition, reanalysis of observations collected decades ago but long forgotten can unlock precious information about the recent past. Historical, in situ observations mainly cover densely inhabited areas and frequently traveled routes. In contrast, large selections of early meteorological satellite data, waiting to be exploited today, provide information about remote areas unavailable from any other source. When initially collected, these satellite data posed great challenges to transmission and archiving facilities. As a result, data access was limited to the main teams of scientific investigators associated with the instruments. As archive media have aged, so have the mission scientists and other pioneers of satellite meteorology, who sometimes retired in possession of unique and unpublished information. This paper presents examples of recently recovered satellite data records, including satellite imagery, early infrared hyperspectral soundings, and early microwave humidity soundings. Their value for climate applications today can be realized using methods and techniques that were not yet available when the data were first collected, including efficient and accurate observation simulators and data assimilation into reanalyses. Modern technical infrastructure allows serving entire mission datasets online, enabling easy access and exploration by a broad range of users, including new and old generations of climate scientists. more
EUM-Secr International cooperation Method

Recent and projected changes in climate patterns in the Middle East and North Africa (MENA) region

Author(s):
Francis, D.; Fonseca, R.
Publication title: Scientific Reports
2024
 | Volume: 14 | Issue: 1
2024
DOI: 10.1038/s41598-024-60976-w
Abstract:
Observational and reanalysis datasets reveal a northward shift of the convective regions over northern Africa in summer and an eastward shift in winte… Observational and reanalysis datasets reveal a northward shift of the convective regions over northern Africa in summer and an eastward shift in winter in the last four decades, with the changes in the location and intensity of the thermal lows and subtropical highs also modulating the dust loading and cloud cover over the Middle East and North Africa region. A multi-model ensemble from ten models of the Coupled Model Intercomparison Project—sixth phase gives skillful simulations when compared to in-situ measurements and generally captures the trends in the ERA-5 data over the historical period. For the most extreme climate change scenario and towards the end of the twenty-first century, the subtropical highs are projected to migrate poleward by 1.5°, consistent with the projected expansion of the Hadley Cells, with a weakening of the tropical easterly jet in the summer by up to a third and a strengthening of the subtropical jet in winter typically by 10% except over the eastern Mediterranean where the storm track is projected to shift polewards. The length of the seasons is projected to remain about the same, suggesting the warming is likely to be felt uniformly throughout the year. © The Author(s) 2024. more
Application Atmosphere CM-SAF Climate Data Records Validation

Recent trends in the agrometeorological climate variables over Scandinavia

Author(s):
Devasthale, Abhay; Carlund, Thomas; Karlsson, Karl-Göran
Publication title: Agricultural and Forest Meteorology
2022
 | Volume: 316
2022
DOI: 10.1016/j.agrformet.2022.108849
Abstract:
The impacts of global climate change in response to increasing greenhouse gasses are spatio-temporally heterogeneous and are observed in a number of e… The impacts of global climate change in response to increasing greenhouse gasses are spatio-temporally heterogeneous and are observed in a number of essential climate variables (ECVs). Among the ECVs that are highly relevant for the agriculture and forestry applications are clouds, precipitation and the incoming surface solar radiation (SIS). The past trends in these three agrometeorological ECVs and, more importantly, the co-variability among them can impact future agriculture and forestry policies and practices, their resilience and conservation. Therefore, using 37-year long climate data records spanning from 1982 to 2018 from the satellite- and surface based observing systems, we investigate the co-variability of trends in cloudiness, precipitation and SIS over Scandinavia during the summer months (April through September). The results reveal a complex nature of such co-variability among the trends in these three climate variables over Scandinavia. We report that the total cloudiness has decreased over much of Scandinavia. The decrease is most pronounced and statistically significant over southern Scandinavia in April, over the western coast in July and over much of northern Scandinavia in August. These decreasing trends are mainly due to reductions in the low and middle level clouds. The trends in all-sky incoming surface radiation are opposite in nature and broadly follow the spatio-temporal patterns of the trends in total cloudiness. The precipitation trends are heterogeneous, both spatially and temporally. The analysis of co-variability of trends reveals three distinct area-regimes that are relevant for assessing the changes in the land use and land cover. © 2022 Swedish Meteorological and Hydrological Institute more
Application Atmosphere CM-SAF Climate Data Records

Recalibration of over 35 Years of Infrared and Water Vapor Channel Radiances of the JMA Geostationary Satellites

Author(s):
Tabata, Tasuku; John, Viju O.; Roebeling, Rob A.; Hewison, Tim; Schulz, Jörg
Publication title: Remote Sensing
2019
 | Volume: 11 | Issue: 10
2019
DOI: 10.3390/rs11101189
Abstract:
Infrared sounding measurements of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-resolution In… Infrared sounding measurements of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-resolution Infrared Radiation Sounder/2 (HIRS/2) instruments are used to recalibrate infrared (IR; \textasciitilde11 µm) channels and water vapor (WV; \textasciitilde6 µm) channels of the Visible and Infrared Spin Scan Radiometer (VISSR), Japanese Advanced Meteorological Imager (JAMI), and IMAGER instruments onboard the historical geostationary satellites of the Japan Meteorological Agency (JMA). The recalibration was performed using a common recalibration method developed by European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), which can be applied to the historical geostationary satellites to produce Fundamental Climate Data Records (FCDR). Pseudo geostationary imager radiances were computed from the infrared sounding measurements and regressed against the radiances from the geostationary satellites. Recalibration factors were computed from these pseudo imager radiance pairs. This paper presents and evaluates the result of recalibration of longtime-series of IR (1978–2016) and WV (1995–2016) measurements from JMA’s historical geostationary satellites. For the IR data of the earlier satellites (Geostationary Metrological Satellite (GMS) to GMS-4) significant seasonal variations in radiometric biases were observed. This suggests that the sensors on GMS to GMS-4 were strongly affected by seasonal variations in solar illumination. The amplitudes of these seasonal variations range from 3 K for the earlier satellites to \textless0.4 K for the recent satellites (GMS-5, Geostationary Operational Environmental Satellite-9 (GOES-9), Multi-functional Transport Satellite-1R (MTSAT-1R) and MTSAT-2). For the WV data of GOES-9, MTSAT-1R and MTSAT-2, no seasonal variations in radiometric biases were observed. However, for GMS-5, the amplitude of seasonal variation in bias was about 0.5 K. Overall, the magnitude of the biases for GMS-5, MTSAT-1R and MTSAT-2 were smaller than 0.3 K. Finally, our analysis confirms the existence of errors due to atmospheric absorption contamination in the operational Spectral Response Function (SRF) of the WV channel of GMS-5. The method used in this study is based on the principles developed within Global Space-based Inter-calibration System (GSICS). Moreover, presented results contribute to the Inter-calibration of imager observations from time-series of geostationary satellites (IOGEO) project under the umbrella of the World Meteorological Organization (WMO) initiative Sustained and Coordinated Processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM). more
Application Climate Data Records EUM-Secr Validation

Reducing the Uncertainty in the Satellite Altimetry Estimates of Global Mean Sea Level Trends Using Highly Stable Water Vapor Climate Data Records

Author(s):
Barnoud, A; Picard, B; Meyssignac, B; Marti, F; Ablain, M; Roca, R
Publication title: JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
2023
 | Volume: 128 | Issue: 3
2023
DOI: 10.1029/2022JC019378
Abstract:
The global mean sea level (GMSL) has risen by 3.3 & PLUSMN; 0.2 mm.yr(-1) (68% confidence level) over 1993-2021. The wet troposphere correction (WTC) … The global mean sea level (GMSL) has risen by 3.3 & PLUSMN; 0.2 mm.yr(-1) (68% confidence level) over 1993-2021. The wet troposphere correction (WTC) used to compute the altimetry-based mean sea level data is known to be a large source of error in the GMSL long-term stability. The WTC is derived from the microwave radiometers (MWR) on board the altimetry missions. In order to improve the long-term estimates of the GMSL, we propose an alternative WTC computation based on highly stable climate data records (CDRs) of water vapor derived from independent MWR measurements on board meteorological satellites. A polynomial model is applied to convert water vapor to WTC. The CDR-derived WTC enables reducing the low frequency uncertainty of the WTC applied to the altimetry data, hence reducing the uncertainty of the GMSL trend estimate. Furthermore, over 2016-2021, the comparison of MWR-based with CDR-based WTC shows a likely drift of the Jason-3 MWR WTC on the order of -0.5 mm.yr(-1) that would lead to an overestimation of the GMSL trend from 2016. more
Application Atmosphere CM-SAF Climate Data Records
Subscribe to