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

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
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