Reducing Weather Influences on an 89 GHz Sea Ice Concentration Algorithm in the Arctic Using Retrievals From an Optimal Estimation Method

Author(s):
Lu, Junshen; Scarlat, Raul; Heygster, Georg; Spreen, Gunnar
Publication title: JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
2022
 | Volume: 127 | Issue: 9
2022
DOI: 10.1029/2019JC015912
Abstract:
Sea ice concentration (SIC) derived from 89 GHz data has up to four times finer spatial resolution compared to that from the widely used 19 and 37 GHz… Sea ice concentration (SIC) derived from 89 GHz data has up to four times finer spatial resolution compared to that from the widely used 19 and 37 GHz data. But it has lower accuracy due to the enhanced weather influences from water vapor, cloud liquid water (CLW), wind, and surface temperature. Here we improve a high-resolution SIC algorithm, called the ASI algorithm, based on the difference between vertical and horizontal polarization 89 GHz data, by correcting the observed data for these weather influences through a radiative transfer model and geophysical data retrieved by an optimal estimation method. The improved algorithm denoted ASI3, is developed for the Arctic based on the weather-corrected brightness temperatures and newly identified open water (80 K) and sea ice (14 K) tie-points. The most important component of this correction is the inclusion of CLW, the largest weather influence contributor. ASI3 results are evaluated over pure surface sites of 0% and 100% SICs under various weather conditions, showing a much lower average standard deviation (1.1%) than ASI (16.2%). ASI3 reduces weather patterns over pack ice resulting in more homogeneous retrievals but biased toward lower values. Comparison to Landsat imagery under clear-sky conditions shows that ASI3 results in better agreement with the Landsat SIC than ASI. The number of cases where real sea ice is falsely identified as open water is reduced by ASI3 due to its relaxed open-water mask and wider water/ice dynamic range. more
Climate Data Records Cryosphere OSI-SAF Validation

Reference-Quality Emission and Backscatter Modeling for the Ocean

Author(s):
English, Stephen; Prigent, Catherine; Johnson, Ben; Yueh, Simon; Dinnat, Emmanuel; Boutin, Jacqueline; Newman, Stuart; Anguelova, Magdalena; Meissner, Thomas; Kazumori, Masahiro; Weng, Fuzhong; Supply, Alexandre; Kilic, Lise; Bettenhausen, Michael; Stoffelen, Ad; Accadia, Christophe
Publication title: Bulletin of the American Meteorological Society
2020
 | Volume: 101 | Issue: 10
2020
DOI: 10.1175/BAMS-D-20-0085.1
Climate Data Records Method NWP-SAF Ocean

Regime shift in Arctic Ocean sea ice thickness

Author(s):
Sumata, Hiroshi; de Steur, Laura; Divine, Dmitry V.; Granskog, Mats A.; Gerland, Sebastian
Publication title: Nature
2023
 | Volume: 615 | Issue: 7952
2023
DOI: 10.1038/s41586-022-05686-x
Abstract:
Manifestations of climate change are often shown as gradual changes in physical or biogeochemical properties1. Components of the climate system, howev… Manifestations of climate change are often shown as gradual changes in physical or biogeochemical properties1. Components of the climate system, however, can show stepwise shifts from one regime to another, as a nonlinear response of the system to a changing forcing2. Here we show that the Arctic sea ice regime shifted in 2007 from thicker and deformed to thinner and more uniform ice cover. Continuous sea ice monitoring in the Fram Strait over the last three decades revealed the shift. After the shift, the fraction of thick and deformed ice dropped by half and has not recovered to date. The timing of the shift was preceded by a two-step reduction in residence time of sea ice in the Arctic Basin, initiated first in 2005 and followed by 2007. We demonstrate that a simple model describing the stochastic process of dynamic sea ice thickening explains the observed ice thickness changes as a result of the reduced residence time. Our study highlights the long-lasting impact of climate change on the Arctic sea ice through reduced residence time and its connection to the coupled ocean–sea ice processes in the adjacent marginal seas and shelves of the Arctic Ocean. more
Climate Data Records Cryosphere OSI-SAF Ocean

Regional Variation in Extratropical North Atlantic Air-Sea Interaction 1960–2020

Author(s):
Latif, M.; Martin, T.; Bielke, I.
Publication title: Geophysical Research Letters
2024
 | Volume: 51 | Issue: 11
2024
DOI: 10.1029/2024GL108174
Abstract:
Air-sea interaction in late boreal winter is studied over the extratropical North Atlantic (NA) during 1960–2020 by examining the relationship between… Air-sea interaction in late boreal winter is studied over the extratropical North Atlantic (NA) during 1960–2020 by examining the relationship between sea-surface temperature (SST) and total turbulent heat flux (THF). The two quantities are positively correlated on interannual timescales over the central-midlatitude and subpolar NA, suggesting the atmosphere on average drives SST and THF variability is independent of SST. On decadal timescales and over the central-midlatitude NA the correlation is negative, suggesting ocean processes on average drive SST and THF variability is sensitive to SST. The correlation is positive over the subpolar NA. There, interannual and decadal THF variability is governed by the North Atlantic Oscillation (NAO). During the major late 20th and early 21st century SST increase in the subpolar NA diminishing oceanic heat loss associated with a weakening NAO was observed. This study suggests that the atmosphere is more sensitive to SST over the central-midlatitude than subpolar NA. © 2024. The Author(s). more
Application Atmosphere CM-SAF Climate Data Records

Refining the Resolution of DUACS Along-Track Level-3 Sea Level Altimetry Products

Author(s):
Pujol, Marie-Isabelle; Dupuy, Stéphanie; Vergara, Oscar; Sánchez Román, Antonio; Faugère, Yannice; Prandi, Pierre; Dabat, Mei-Ling; Dagneaux, Quentin; Lievin, Marine; Cadier, Emeline; Dibarboure, Gérald; Picot, Nicolas
Publication title: Remote Sensing
2023
 | Volume: 15 | Issue: 3
2023
DOI: 10.3390/rs15030793
Abstract:
This paper describes the demonstration of a regional high-resolution level-3 (L3) altimeter data unification and altimeter combination system (DUACS) … This paper describes the demonstration of a regional high-resolution level-3 (L3) altimeter data unification and altimeter combination system (DUACS) developed with support from the French space agency (CNES). Deduced from full-rate (20 Hz to 40 Hz) level-2 (L2) altimeter measurements, this product provides sea level anomalies (SLA) and other essential physical variables at a spatial resolution of one sample every ~1 km over the North Atlantic Ocean. This allows us to resolve wavelengths from ~35 km to ~55 km depending on the altimeter considered. This was made possible by recent advances in radar altimeter processing for both synthetic aperture radar (SAR) and low-resolution-mode (LRM) measurements, as well as improvements made to different stages of the DUACS processing chain. Firstly, the new adaptive and low-resolution with range migration correction (LR-RMC) processing techniques were considered for Jason and Sentinel-3 (S3A), respectively. They significantly reduce errors at short wavelengths, and the adaptive processing also reduces possible land contamination near the coast. Next, up-to-date geophysical and environmental corrections were selected for this production. This includes specific corrections intended to reduce the measurement noise on LRM measurements and thus enhance the observability at short wavelengths. Compared with the 1 Hz product, the observable wavelengths reached with the demonstration high-resolution product are reduced by up to one third, or up to half in the northeast Atlantic region. The residual noises were optimally filtered from full-rate measurements, taking into consideration the different observing capabilities of the altimeters processed. A specific data recovery strategy was applied, significantly optimizing the data availability, both in the coastal and open ocean areas. This demonstration L3 product is thus better resolved than the conventional 1 Hz product, especially near the coast, where it is defined up to ~5 km against ~10 km for the 1 Hz version. Multi-mission cross-calibration processing was also optimized with an improved long-wavelength error (LWE) correction, leading to a better consistency between tracks, with a 9–15% reduction in SLA variance at cross-overs. The new L3 product improves the overall consistency with tide gauge measurements, with a reduction in SLA differences variance by 5 and 17% compared with the 1 Hz product from the S3A and Jason-3 (J3) measurements, respectively. Primarily intended for regional applications, this product can significantly contribute to improving high-resolution numerical model output via data assimilation. It also opens new perspectives for a better understanding of regional sea-surface dynamics, with an improved representation of the coastal currents and a refined spectral content revealing the unbalanced signal. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Regional Cloud Forecast Verification Using Standard, Spatial, and Object-Oriented Methods

Author(s):
Christophersen, H.; Nachamkin, J.; Davis, W.
Publication title: Weather and Forecasting
2024
 | Volume: 39 | Issue: 3
2024
DOI: 10.1175/WAF-D-23-0197.1
Abstract:
This study assesses the accuracy of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) forecasts for clouds within stable and unstable … This study assesses the accuracy of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) forecasts for clouds within stable and unstable environments (thereafter refers as “stable” and “unstable” clouds). This evaluation is conducted by comparing these forecasts against satellite retrievals through a combination of traditional, spatial, and object-based methods. To facilitate this assessment, the Model Evaluation Tools (MET) community tool is employed. The findings underscore the significance of fine-tuning the MET parameters to achieve a more accurate representation of the features under scrutiny. The study’s results reveal that when employing traditional pointwise statistics (e.g., frequency bias and equitable threat score), there is consistency in the results whether calculated from Method for Object-Based Diagnostic Evaluation (MODE)-based objects or derived from the complete fields. Further-more, the object-based statistics offer valuable insights, indicating that COAMPS generally predicts cloud object locations accurately, though the spread of these predicted locations tends to increase with time. It tends to overpredict the object area for unstable clouds while underpredicting it for stable clouds over time. These results are in alignment with the traditional pointwise bias scores for the entire grid. Overall, the spatial metrics provided by the object-based verification methods emerge as crucial and practical tools for the validation of cloud forecasts. © 2024 American Meteorological Society. more
Application Atmosphere NWP-SAF Software for CDR development

Regional Features of the Arctic Sea Ice Area Changes in 2000–2019 versus 1979–1999 Periods

Author(s):
Matveeva, Tatiana A.; Semenov, Vladimir A.
Publication title: Atmosphere
2022
 | Volume: 13 | Issue: 9
2022
DOI: 10.3390/atmos13091434
Abstract:
One of the most striking manifestations of ongoing climate change is a rapid shrinking of the Arctic sea ice area (SIA). An important feature of the o… One of the most striking manifestations of ongoing climate change is a rapid shrinking of the Arctic sea ice area (SIA). An important feature of the observed SIA loss is a nonlinear rate of a decline with an accelerated decrease in the 2000–2019 period relative to a more gradual decline in 1979–1999. In this study, we perform a quantitative assessment and comparison of the spatial-temporal SIA changes during these two periods. It was found that winter Arctic SIA loss is primarily associated with changes in the Barents Sea, where the SIA decline in 2000–2019 has accelerated more than three-fold in comparison with 1979–1999. In summer and autumn, rates of SIA decline in 2000–2019 increased most strongly in the Kara, Beaufort Seas, the Northwestern Passage, and inner Arctic Ocean. The amplitude of the SIA seasonal cycle has also increased in 2000–2019 in comparison with the earlier period, with the largest changes in the inner Arctic Ocean, the Kara, Laptev, East Siberian and Beaufort Seas in summer and in the Barents Sea in winter. The results may reflect a transition to a new dynamic state in the recent two decades with the triggering of positive feedbacks in the Arctic climate system. more
Application Climate Data Records Cryosphere OSI-SAF

Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

Author(s):
Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; Le Gléau, H.; Lockhoff, M.; Lutz, H.-J.; Meirink, J. F.; Minnis, P.; Palikonda, R.; Roebeling, R.; Thoss, A.; Platnick, S.; Watts, P.; Wind, G.
Publication title: Atmospheric Measurement Techniques
2014
 | Volume: 7 | Issue: 9
2014
DOI: 10.5194/amt-7-2839-2014
Abstract:
Abstract. The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth… Abstract. The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 km to 0.6 km. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed. more
Atmosphere CM-SAF Climate Data Records Validation

Relationship between precipitation and cloud properties in different regions of Southwest China

Author(s):
Wang, Yuting; Zhao, Pengguo; Zhao, Chuanfeng; Xiao, Hui; Mo, Shuying; Yuan, Liang; Wei, Chengqiang; Zhou, Yunjun
Publication title: International Journal of Climatology
2024
 | Volume: 44 | Issue: 7
2024
DOI: 10.1002/joc.8455
Abstract:
The relationship between precipitation and cloud properties in Southwest China are investigated by using the CLARA-A2 cloud parameters data and TRMM-3… The relationship between precipitation and cloud properties in Southwest China are investigated by using the CLARA-A2 cloud parameters data and TRMM-3B43 precipitation data from 1998 to 2015. Ice water path (IWP) and cloud top height (CTH) are significantly and positively correlated with precipitation in all regions, indicating that ice-phase processes and cloud development processes are the critical processes influencing precipitation. Precipitation is also directly associated with cloud fractional coverage (CFC) due to the significant positive correlation between CFC and precipitation in all regions except the Sichuan Basin (SCB). A positive correlation between liquid water path (LWP) and precipitation is found in the Eastern Tibetan Plateau (ETP) and Yunnan-Kweichow Plateau (YKP), but not in the Western Tibetan Plateau (WTP) and SCB. Notably, the response of precipitation to LWP is not as good as that to IWP in SCB. Precipitation is significantly negatively correlated with ice effective radius (IREF) in WTP and ETP and positively correlated with liquid effective radius (LREF) in ETP, YKP and SCB. IREF and LREF are closely related to cloud microphysical processes. Specifically, small IREF could accelerate the Bergeron process and thus increase precipitation, while large LREF is closely related to the cloud droplets coalescence process. Results indicate that the difference in precipitation between the cold and warm seasons is related to convective available potential energy (CAPE) and low troposphere relative humidity (RH). High CAPE and RH favour the precipitation occurrence in Southwest China. The influence of CAPE and RH on precipitation is more significant in the ETP than that in the WTP, owing to the orographic lifting and moisture transport from the Indian Ocean. Thermodynamic and humidity conditions have a greater impact on precipitation by influencing LREF, LWP and IWP in YKP. In SCB, precipitation shows a strong dependence on CAPE, IWP and LREF, but not on RH. more
Application Atmosphere CM-SAF Climate Data Records

Relevance of warm air intrusions for Arctic satellite sea ice concentration time series

Author(s):
Rostosky, P.; Spreen, G.
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 9
2023
DOI: 10.5194/tc-17-3867-2023
Abstract:
Winter warm air intrusions entering the Arctic region can strongly modify the microwave emission of the snow-covered sea ice system due to temperature… Winter warm air intrusions entering the Arctic region can strongly modify the microwave emission of the snow-covered sea ice system due to temperature-induced snow metamorphism and ice crust formations, e.g., after melt-refreeze events. Common microwave radiometer satellite sea ice concentration retrievals are based on empirical models using the snow-covered sea ice emissivity and thus can be influenced by strong warm air intrusions. Here, we carry out a long-Term study analyzing 41 years of winter sea ice concentration observations from different algorithms to investigate the impact of warm air intrusions on the retrieved ice concentration. Our results show that three out of four algorithms underestimate the sea ice concentration during (and up to 10 d after) warm air intrusions which increase the 2 m air temperature (daily maximum) above-5 C. This can lead to sea ice area underestimations in the order of 104 to 105 km2. If the 2 m temperature during the warm air intrusions crosses-2 C, all algorithms are impacted. Our analysis shows that the strength of these strong warm air intrusions increased in recent years, especially in April. With a further climate change, such warm air intrusions are expected to occur more frequently and earlier in the season, and their influence on sea ice climate data records will become more important. © 2023 Copernicus GmbH. All rights reserved. more
Application Climate Data Records Cryosphere OSI-SAF Ocean
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