| 1. |
- Assmann, Karen, et al.
(författare)
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Warm. Circumpolar Deep Water at the Western Getz Ice Shelf Front, Antarctica
- 2019
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Ingår i: Geophysical Research Letters. - : American Geophysical Union (AGU). - 0094-8276 .- 1944-8007. ; 46:2, s. 870-878
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Tidskriftsartikel (refereegranskat)abstract
- The Getz Ice Shelf is one of the largest sources of fresh water from ice shelf basal melt in Antarctica. We present new observations from three moorings west of Siple Island 2016-2018. All moorings show a persistent flow of modified Circumpolar Deep Water toward the western Getz Ice Shelf. Unmodified Circumpolar Deep Water with temperatures up to 1.5 degrees C reaches the ice shelf front in frequent episodes. These represent the warmest water observed at any ice shelf front in the Amundsen Sea. Mean currents within the warm bottom layer of 18-20 cm/s imply an advection time scale of 7 days from shelf break to ice shelf front. Zonal wind stress at the shelf break affects heat content at the ice shelf front on weekly to monthly time scales. Our 2-year mooring records also evince that upwelling over the shelf break controls thermocline depth on subannual to annual time scales. Plain Language Summary The recent retreat of the West Antarctic Ice Sheet has been linked to changes in the transport of warm ocean water up to 1.5 degrees C to the floating ice shelves in the Amundsen Sea. One of these is the Getz Ice Shelf that produces one of the largest amounts of ice shelf melt water in Antarctica. To measure how much ocean heat is transported toward this ice shelf, we deployed a series of temperature, salinity, and current sensors at its western end from 2016 to 2018. We find a constant flow of warm water toward the ice shelf cavity. Comparing our ocean observations with wind data from the area, we found that stronger easterly winds in the area make it harder for the warm water to reach the ice shelf front by depressing the warm bottom layer over the shelf break. Climate projections indicate that these easterlies will weaken in future, making it easier for the warm water to reach the ice shelf base. Gradients in the wind field over the shelf break control the thickness of the warm layer on longer time scales. This provides the missing ocean evidence for previous studies that have linked this wind mechanism to ice sheet changes.
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| 2. |
- Bannan, T. J., et al.
(författare)
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A Large Source of Atomic Chlorine From ClNO2 Photolysis at a UK Landfill Site
- 2019
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Ingår i: Geophysical Research Letters. - : American Geophysical Union (AGU). - 0094-8276 .- 1944-8007. ; 46:14, s. 8508-8516
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Tidskriftsartikel (refereegranskat)abstract
- Nitryl chloride (ClNO2) acts as a source of highly reactive chlorine atoms as well as an important NOx reservoir. Measurements of ClNO2 at an operational U.K. landfill site are reported here for the first time. A peak concentration of 4 ppb of ClNO2 was found with a peak mean nighttime maximum of 0.9 ppb. Using models based upon the photolysis of observed ClNO2 and atmospheric chlorine chemistry, chlorine atom concentrations reaching in excess of 1.20 x 10(5) molecules/cm(3) in the early morning following sunrise are calculated. These concentrations are approximately 10 times higher than previously reported in the United Kingdom, suggesting a significant impact on the oxidizing capacity around such sites. Given the ubiquity of landfill sites regionally and globally, and the large abundances of Cl atoms from the photolysis of ClNO2, chlorine chemistry has a significant impact on ozone formation and volatile organic compounds oxidation as shown by WRF-Chem modeling. Plain Language Summary Landfill sites are a known source of traces gases into the atmosphere, but measurements often focus predominately on methane and carbon dioxide. A small subsection of trace gas measurements at landfill sites have shown, however, that these sites may be important halogen sources that could have subsequent impacts on air quality and climate. Spatially limited field measurements have previously been reported of a halogen species, ClNO2, showing that this species is consistently formed during nighttime hours, but no such measurements before now have been made at any landfill site. ClNO2 undergoes photolysis upon sunrise, releasing the extremely reactive Cl as well as NO2 into the atmosphere and therefore plays an important part in the total budget and distribution of tropospheric oxidants, halogens, and reactive nitrogen species, all of which are important to air quality. Here we present mass spectrometry measurements of ClNO2 taken at an undisclosed landfill, which show high concentrations in comparison to any other global study of this type. We use predictive modeling techniques to show the importance of this halogen species to air quality, using indicators such as ozone formation. Based on these results we recommend that landfill sources of Cl should be included in future air quality studies.
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| 3. |
- Bao, Fangling, et al.
(författare)
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Advancing Cloud Classification Over the Tibetan Plateau: A New Algorithm Reveals Seasonal and Diurnal Variations
- 2024
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Ingår i: GEOPHYSICAL RESEARCH LETTERS. - 0094-8276 .- 1944-8007. ; 51:13
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Tidskriftsartikel (refereegranskat)abstract
- The cloud classification algorithm widely used in the International Satellite Cloud Climatology Project (ISCCP) tends to underestimate low clouds over the Tibetan Plateau (TP), often mistaking water clouds for high-level clouds. To address this issue, we propose a new algorithm based on cloud-top temperature and optical thickness, which we apply to TP using Advanced Himawari Imager (AHI) geostationary satellite data. Compared with Clouds and the Earth's Radiant Energy System cloud-type products and ISCCP results obtained from AHI data, this new algorithm markedly improved low-cloud detection accuracy and better aligned with cloud phase results. Validation with lidar cloud-type products further confirmed the superiority of this new algorithm. Diurnal cloud variations over the TP show morning dominance shifting to afternoon high clouds and evening mid-level clouds. Winter is dominated by high clouds, summer by mid-level clouds, spring by daytime low clouds and nighttime high clouds, and autumn by low and mid-level clouds. The accurate identification of low clouds over the Tibetan Plateau (TP) is crucial for climate regulation, ecosystems, aviation safety, research, and modeling. However, satellite-based methods often miss these clouds, misclassifying them as high-level clouds. To remedy this, we developed a new algorithm using cloud-top temperature and optical thickness, applied to Advanced Himawari Imager data. This significantly improves low-cloud detection, better aligning with actual cloud phases. Simultaneously, we analyzed diurnal cloud variations over the TP with the new algorithm. Cloud types at different altitudes in the TP exhibit strong seasonality. The dominant cloud types in winter and summer are high and mid-level, respectively. In spring, low clouds dominate during the day (2:00-10:00 UTC), transitioning to high clouds at night (10:00-18:00 UTC), with mid-level clouds prevailing at other times. In autumn, low clouds dominate during the day, transitioning to mid-level clouds at other times, with fewer occurrences of high clouds. Employing cloud-top temperature instead of pressure resolves classification-phase inconsistencies for clouds in the Tibetan Plateau (TP) Lidar validation shows new algorithm's low cloud detection outperforms the conventional International Satellite Cloud Climatology Project algorithm for both TP and plains The study reveals significant diurnal and seasonal variations in low clouds over the TP
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| 4. |
- Chaudhary, N., et al.
(författare)
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Modeling Pan-Arctic Peatland Carbon Dynamics Under Alternative Warming Scenarios
- 2022
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Ingår i: Geophysical Research Letters. - : American Geophysical Union (AGU). - 0094-8276 .- 1944-8007. ; 49:10
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Tidskriftsartikel (refereegranskat)abstract
- Peatlands store large amounts of carbon in terrestrial ecosystems and they are vulnerable to recent warming. The ongoing warming may change their carbon sink capacity and could reduce their potential to sequester carbon. In this study, we simulated peatland carbon dynamics in distinct future climate conditions using the peatland-vegetation model (LPJ-GUESS). The study examined whether less pronounced warming could further enhance the peatland carbon sink capacity and buffer the effects of climate change. It also determined which trajectory peatland carbon balance would follow, what the main drivers were, and which one would dominate in the future. We found that peatlands will largely retain their carbon sink capacity under the climate scenario RCP2.6 to RCP6.0. They are projected to shift from a carbon sink to a carbon-neutral (5-10 gC m(-2) yr(-1)) in RCP8.5. Higher respiration rates will dominate the net productivity in a warmer world leading to a reduction in carbon sink capacity.
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| 5. |
- Chen, Hans, 1988, et al.
(författare)
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A robust mode of climate variability in the Arctic: The Barents Oscillation
- 2013
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Ingår i: Geophysical Research Letters. - : American Geophysical Union (AGU). - 0094-8276 .- 1944-8007. ; 40:11, s. 2856-2861
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Tidskriftsartikel (refereegranskat)abstract
- The Barents Oscillation (BO) is an anomalous wintertime atmospheric circulation pattern in the Northern Hemisphere that has been linked to the meridional flow over the Nordic Seas. There are speculations that the BO has important implications for the Arctic climate; however, it has also been suggested that the pattern is an artifact of Empirical Orthogonal Function (EOF) analysis due to an eastward shift of the Arctic Oscillation/North Atlantic Oscillation (AO/NAO). In this study, EOF analyses are performed to show that a robust pattern resembling the BO can be found during different time periods, even when the AO/NAO is relatively stationary. This BO has a high and stable temporal correlation with the geostrophic zonal wind over the Barents Sea, while the contribution from the AO/NAO is small. The surface air temperature anomalies over the Barents Sea are closely associated with this mode of climate variability.
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| 6. |
- Chylek, P., et al.
(författare)
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Annual Mean Arctic Amplification 1970-2020: Observed and Simulated by CMIP6 Climate Models
- 2022
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Ingår i: Geophysical Research Letters. - : American Geophysical Union (AGU). - 0094-8276 .- 1944-8007. ; 49:13
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Tidskriftsartikel (refereegranskat)abstract
- While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970-2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the "best" CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step-like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time.
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| 7. |
- Chylek, P., et al.
(författare)
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CMIP5 Climate Models Overestimate Cooling by Volcanic Aerosols
- 2020
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Ingår i: Geophysical Research Letters. - : American Geophysical Union (AGU). - 0094-8276 .- 1944-8007. ; 47:3
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Tidskriftsartikel (refereegranskat)abstract
- We compare projections of the observed hemispherical mean surface temperature (HadCRUT4.6.0.0) and the ensemble mean of CMIP5 climate models' simulations on a set of standard regression model forcing variables. We find that the volcanic aerosol regression coefficients of the CMIP5 simulations are consistently significantly larger (by 40-49%) than the volcanic aerosol coefficients of the observed temperature. The probability that the observed differences are caused just by chance is much less than 0.01. The overestimate is due to the climate models' response to volcanic aerosol radiative forcing. The largest overestimate occurs in the winter season of each hemisphere. We hypothesize that the models' parameterization of aerosol-cloud interactions within ice and mixed phase clouds is a likely source of this discrepancy. Furthermore, the models significantly underestimate the effect of solar variability on temperature for both hemispheres. Plain Language Summary We compare the observed and climate models' simulated hemispherical mean temperature projections on a set of influencing factors. The influencing factors include the man-made greenhouse gases and aerosols as well as natural solar variability, volcanic eruptions, and internal climate variability. If the observed and model-simulated temperatures were the same, the projections would be very similar. We find that the projections are not similar. The climate models overestimate the cooling effect of volcanic activity and underestimate the effect of the variability of solar radiation. Our results point out that future models should improve the treatment of volcanic aerosols and solar variability to increase the reliability of climate change projections.
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| 8. |
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| 9. |
- Folland, Chris K., et al.
(författare)
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High predictive skill of global surface temperature a year ahead
- 2013
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Ingår i: Geophysical Research Letters. - : American Geophysical Union (AGU). - 0094-8276. ; 40:4, s. 761-767
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Tidskriftsartikel (refereegranskat)abstract
- [1] We discuss 13 real-time forecasts of global annual-mean surface temperature issued by the United Kingdom Met Office for 1year ahead for 2000–2012. These involve statistical, and since 2008, initialized dynamical forecasts using the Met Office DePreSys system. For the period when the statistical forecast system changed little, 2000–2010, issued forecasts had a high correlation of 0.74 with observations and a root mean square error of 0.07°C. However, the HadCRUT data sets against which issued forecasts were verified were biased slightly cold, especially from 2004, because of data gaps in the strongly warming Arctic. This observational cold bias was mainly responsible for a statistically significant warm bias in the 2000–2010 forecasts of 0.06°C. Climate forcing data sets used in the statistical method, and verification data, have recently been modified, increasing hindcast correlation skill to 0.80 with no significant bias. Dynamical hindcasts for 2000–2011 have a similar correlation skill of 0.78 and skillfully hindcast annual mean spatial global surface temperature patterns. Such skill indicates that we have a good understanding of the main factors influencing global mean surface temperature.
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| 10. |
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