Author(s):
Lelli, L.; Vountas, M.; Khosravi, N.; Burrows, J.P.
Publication title: Atmospheric Chemistry and Physics
2023
| Volume: 23 | Issue: 4
2023
Abstract:
Two decades of measurements of spectral reflectance of solar radiation at the top of the atmosphere and a complementary record of cloud properties fro… Two decades of measurements of spectral reflectance of solar radiation at the top of the atmosphere and a complementary record of cloud properties from satellite passive remote sensing have been analyzed for their pan-Arctic, regional, and seasonal changes. The pan-Arctic loss of brightness, which is explained by the retreat of sea ice during the current warming period, is not compensated by a corresponding increase in cloud cover. A systematic change in the thermodynamic phase of clouds has taken place, shifting towards the liquid phase at the expense of the ice phase. Without significantly changing the total cloud optical thickness or the mass of condensed water in the atmosphere, liquid water content has increased, resulting in positive trends in liquid cloud optical thickness and albedo. This leads to a cooling trend by clouds being superimposed on top of the pan-Arctic amplified warming, induced by the anthropogenic release of greenhouse gases, the ice-albedo feedback, and related effects. Except over the permanent and parts of the marginal sea ice zone around the Arctic Circle, the rate of surface cooling by clouds has increased, both in spring (-32 % in total radiative forcing for the whole Arctic) and in summer (-14 %). The magnitude of this effect depends on both the underlying surface type and changes in the regional Arctic climate. Copyright: © 2023 Luca Lelli et al. more
Author(s):
Embury, O; Merchant, CJ; Good, SA; Rayner, NA; Hoyer, JL; Atkinson, C; Block, T; Alerskans, E; Pearson, KJ; Worsfold, M; Mccarroll, N; Donlon, C
Publication title: SCIENTIFIC DATA
2024
| Volume: 11 | Issue: 1
2024
Abstract:
A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high… A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 x 1013 locations are processed, yielding 1.4 x 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km-2 yr-1 in 1980 to over 100 km-2 yr-1 after 2007. Data are provided at their native resolution, averaged on a global 0.05 degrees latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05 degrees. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods. more
Author(s):
Ji, W.; Fang, Z.; Liu, D.; Yu, R.; Feng, D.
Publication title: International Journal of Remote Sensing
2024
| Volume: 45 | Issue: 22
2024
Abstract:
Rotating fan-beam scatterometer (RFSCAT) is a radar scatterometer system for sea surface wind vector measurement. Compared with other available scatte… Rotating fan-beam scatterometer (RFSCAT) is a radar scatterometer system for sea surface wind vector measurement. Compared with other available scatterometers, RFSCAT can provide more combination of azimuth angles and incidence angles for a single WVC (wind vector cell), this observation mechanism is more conducive to the sea surface wind direction retrieval. In this paper, the NSCAT-4DS GMF (geophysical model function) with SST (sea surface temperature) correction, and the MSS (Multiple Solution Scheme) combination with a 2DVAR (2-dimensional variational analysis) are adopted to retrieve the sea surface winds from RFSCAT on the CFOSAT (Chinese-French Oceanography Satellite). The retrieved RFSCAT sea surface winds and ASCAT (advanced scatterometer) sea surface winds are compared and tested, and the feasibility of the RFSCAT measuring sea surface winds under high wind speeds is analysed. The results show that the RMSE of the RFSCAT sea surface wind speed using improved algorithm has decreased by 0.292 m s−1, the correlation coefficient has increased by 0.032, and the residual standard deviation has decreased by 0.194 m s−1. The RMSE of RFSCAT sea surface wind direction has decreased by 5.950°, the correlation coefficient has increased by 0.002, and the residual standard deviation has decreased by 5.567°. It is shown that the changes in winds RMSE using pre-improved and improved algorithms have statistical significance. In a word, the spaceborne Ku-band rotating fan-beam scatterometer can capture the winds structure of ocean cyclones. Although there may be high wind speeds saturation phenomena, the detecting sea surface winds at high wind speeds show preferable performance. © 2024 Informa UK Limited, trading as Taylor & Francis Group. more
Author(s):
Stoffelen, Ad; Aaboe, Signe; Calvet, Jean-Christophe; Cotton, James; De Chiara, Giovanna; Saldana, Julia Figa; Mouche, Alexis Aurelien; Portabella, Marcos; Scipal, Klaus; Wagner, Wolfgang
Publication title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
2017
| Volume: 10 | Issue: 5
2017
Abstract:
The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned … The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned for launch in 2022, has a direct heritage from the successful advanced scatterometer (ASCAT) flown on the current EPS satellites. In addition, SCA will represent three major innovations with respect to ASCAT, namely: 1) Cross polarization and horizontal copolarization; 2) a nominal spatial resolution of 25 km; and 3) 20% greater spatial coverage than ASCAT. The associated expected science and application benefits that led the SCA design are discussed with respect to ocean, land, and sea ice applications for near-real time, climate monitoring, and research purposes. Moreover, an option to implement an ocean Doppler capability to retrieve the ocean motion vector is briefly discussed as well. In conclusion, the SCA instrument innovations are well set to provide timely benefits in all the main application areas of the scatterometer (winds, soil moisture, sea ice) and can be expected to contribute to new and more sophisticated meteorological, oceanographic, land, sea ice, and climate services in the forthcoming SCA era. more
Author(s):
Batrak, Y.; Cheng, B.; Kallio-Myers, V.
Publication title: Cryosphere
2024
| Volume: 18 | Issue: 3
2024
Abstract:
The Copernicus Arctic Regional Reanalysis (CARRA) is a novel regional high-resolution atmospheric reanalysis product that covers a considerable part o… The Copernicus Arctic Regional Reanalysis (CARRA) is a novel regional high-resolution atmospheric reanalysis product that covers a considerable part of the European Arctic including substantial amounts of ice-covered areas. Sea ice in CARRA is modelled by means of a one-dimensional thermodynamic sea ice parameterisation scheme, which also explicitly resolves the evolution of the snow layer over sea ice. In the present study, we assess the representation of sea ice cover in CARRA and validate it against a wide set of satellite products and observations from ice mass balance buoys. We show that CARRA adequately represents general interannual trends towards thinner and warmer ice in the Arctic. Compared to ERA5, sea ice in CARRA shows a reduced warm bias in the ice surface temperature. The strongest improvement was observed for winter months over the central Arctic and the Greenland and Barents seas where a 4.91ĝ€¯°C median ice surface temperature error in ERA5 is reduced to 1.88ĝ€¯°C in CARRA on average. Over Baffin Bay, intercomparisons suggest the presence of a cold winter-time ice surface temperature bias in CARRA. No improvement over ERA5 was found in the ice surface albedo with spring-time errors in CARRA being up to 0.08 higher on average than those in ERA5 when computed against the CLARA-A2 satellite retrieval product. Summer-time ice surface albedos are comparable in CARRA and ERA5. Sea ice thickness and snow depth in CARRA adequately resolve the annual cycle of sea ice cover in the Arctic and bring added value compared to ERA5. However, limitations of CARRA indicate potential benefits of utilising more advanced approaches for representing sea ice cover in next-generation reanalyses. © Copyright: more
Author(s):
Andersson, T.R.; Hosking, J.S.; Pérez-Ortiz, M.; Paige, B.; Elliott, A.; Russell, C.; Law, S.; Jones, D.C.; Wilkinson, J.; Phillips, T.; Byrne, J.; Tietsche, S.; Sarojini, B.B.; Blanchard-Wrigglesworth, E.; Aksenov, Y.; Downie, R.; Shuckburgh, E.
Publication title: Nature Communications
2021
| Volume: 12 | Issue: 1
2021
Abstract:
Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and… Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss. © 2021, The Author(s). more
Author(s):
Marquardt, Miriam; Goraguer, Lucie; Assmy, Philipp; Bluhm, Bodil A.; Aaboe, Signe; Down, Emily; Patrohay, Evan; Edvardsen, Bente; Tatarek, Agnieszka; Smoła, Zofia; Wiktor, Jozef; Gradinger, Rolf
Publication title: Progress in Oceanography
2023
| Volume: 218
2023
Abstract:
The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known… The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known seasonality of sea-ice protist and meiofauna community composition, abundance and biomass in the bottom 30 cm of sea ice in relation to ice properties and ice drift trajectories in the northwestern Barents Sea. We expected low abundances during the polar night and highest values during spring prior to ice melt. Sea ice conditions and Chlorophyll a concentrations varied strongly seasonally, while particulate organic carbon concentrations were fairly stable throughout the seasons. In December to May we sampled growing first-year ice, while in July and August melting older sea ice dominated. Low sea-ice biota abundances in March could be related to the late onset of ice formation and short time period for ice algae and uni- and multicellular grazers to establish themselves. Pennate diatoms, such as Navicula spp. and Nitzschia spp., dominated the bottom ice algal communities and were present during all seasons. Except for May, ciliates, dinoflagellates, particularly of the order Gymnodiales, and small-sized flagellates were co-dominant. Ice meiofauna (here including large ciliates and foraminifers) was comprised mainly of harpacticoid copepods, copepod nauplii, rotifers, large ciliates and occasionally acoels and foraminifers, with dominance of omnivore species throughout the seasons. Large ciliates comprised the most abundant meiofauna taxon at all ice stations and seasons (50–90 %) but did not necessarily dominate the biomass. While ice melt might have released and reduced ice algal biomass in July, meiofauna abundance remained high, indicating different annual cycles of protist versus meiofauna taxa. In May highest Chlorophyll a concentrations (29.4 mg m−2) and protist biomass (107 mg C m−2) occurred, while highest meiofauna abundance was found in August (23.9 × 103 Ind. m−2) and biomass in December (0.6 mg C m−2). The abundant December ice biota community further strengthens the emerging notion of an active biota during the dark Arctic winter. The data demonstrated a strong and partially unexpected seasonality in the Barents Sea ice biota, indicating that changes in ice formation, drift and decay will significantly impact the functioning of the ice-associated ecosystem. more
Author(s):
Zhang, SY; Wang, MH; Wang, LN; Liang, XZ; Sun, C; Li, QQ
Publication title: ATMOSPHERIC RESEARCH
2023
| Volume: 285
2023
Abstract:
The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant bias… The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant biases for the simulation of extreme precipitation. To understand the causes of these biases, we used five different cumulus parameterization schemes in the regional Climate-Weather Research and Forecasting (CWRF) model to investigate its performance and biases in the simulation of extreme precipi-tation events in China. In general, the ensemble cumulus parameterization (ECP) scheme was the most skillful in reproducing the spatial distribution of the 95th percentile daily precipitation (P95) and the other four schemes either overestimated (the Kain-Fritsch Eta and Tiedtke schemes) or underestimated (the Betts-Miller-Janjic and New Simplified Arakawa-Schubert schemes) P95. Compared with the observational data, ECP scheme signifi-cantly improved the simulation of extreme precipitation in China and had the highest correlation and the smallest root-mean-square error in most areas and seasons. To clarify the underlying physical processes of P95 simulation biases, we established a regression model of extreme precipitation based on ECP scheme. This showed that P95 in North China is mainly affected by moisture convergence, planetary boundary layer height and lifting condensation level (relative importance 18-32%). In Central China, the vertical upward motion of water vapor, sensible heat flux and planetary boundary layer height (relative importance 18-30%) are main factors associated with P95. In South China, the vertical upward motion and horizontal transport of water vapor are predominant (relative importance 26-37%). In addition, the net surface energy, surface and atmospheric radiation flux, total precipitable water, convective available potential energy and cloud water path also have a high correlation with P95 (the second most important factor; relative importance 14-31%). The influence of each factor on the simulation of P95 is different when using different cumulus parameterization schemes and the interaction among the different factors determines the ability of CWRF model to simulate extreme precipitation. These results provide important references for future model evaluations and improvements. more
Author(s):
Han, Cunbo; Hoose, Corinna; Stengel, Martin; Coopman, Quentin; Barrett, Andrew
Publication title: Atmospheric Chemistry and Physics
2023
| Volume: 23 | Issue: 22
2023
Abstract:
The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strong… The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strongly depend on their partitioning between the liquid and ice phases. In this study, we investigated the sensitivities of the cloud phase to the ice-nucleating particle (INP) concentration and thermodynamics. Moreover, passive satellite retrieval algorithms and cloud products were evaluated to identify whether they could detect cloud microphysical and thermodynamical perturbations. Experiments were conducted using the ICOsahedral Nonhydrostatic (ICON) model at the convection-permitting resolution of about 1.2 km on a domain covering significant parts of central Europe, and they were compared to two different retrieval products based on Spinning Enhanced Visible and InfraRed Imager (SEVIRI) measurements. We selected a day with multiple isolated deep convective clouds, reaching a homogeneous freezing temperature at the cloud top. The simulated cloud liquid pixel fractions were found to decrease with increasing INP concentration, both within clouds and at the cloud top. The decrease in the cloud liquid pixel fraction was not monotonic and was stronger in high-INP cases. Cloud-top glaciation temperatures shifted toward warmer temperatures with an increasing INP concentration by as much as 8 ∘C. Moreover, the impact of the INP concentration on cloud-phase partitioning was more pronounced at the cloud top than within the cloud. Furthermore, initial and lateral boundary temperature fields were perturbed with increasing and decreasing temperature increments from 0 to ±3 and ±5 K between 3 and 12 km, respectively. Perturbing the initial thermodynamic state was also found to systematically affect the cloud-phase distribution. However, the simulated cloud-top liquid pixel fraction, diagnosed using radiative transfer simulations as input to a satellite forward operator and two different satellite remote-sensing retrieval algorithms, deviated from one of the satellite products regardless of perturbations in the INP concentration or the initial thermodynamic state for warmer subzero temperatures while agreeing with the other retrieval scheme much better, in particular for the high-INP and high-CAPE (convective available potential energy) scenarios. Perturbing the initial thermodynamic state, which artificially increases the instability of the mid- and upper-troposphere, brought the simulated cloud-top liquid pixel fraction closer to the satellite observations, especially in the warmer mixed-phase temperature range. more