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  • 1
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    American Meteorological Society
    In:  EPIC3Bulletin of the American Meteorological Society, American Meteorological Society, 104(9), pp. s1-s10, ISSN: 0003-0007
    Publication Date: 2024-05-08
    Description: 〈jats:title〉Abstract〈/jats:title〉 〈jats:p〉—J. BLUNDEN, T. BOYER, AND E. BARTOW-GILLIES〈/jats:p〉 〈jats:p〉Earth’s global climate system is vast, complex, and intricately interrelated. Many areas are influenced by global-scale phenomena, including the “triple dip” La Niña conditions that prevailed in the eastern Pacific Ocean nearly continuously from mid-2020 through all of 2022; by regional phenomena such as the positive winter and summer North Atlantic Oscillation that impacted weather in parts the Northern Hemisphere and the negative Indian Ocean dipole that impacted weather in parts of the Southern Hemisphere; and by more localized systems such as high-pressure heat domes that caused extreme heat in different areas of the world. Underlying all these natural short-term variabilities are long-term climate trends due to continuous increases since the beginning of the Industrial Revolution in the atmospheric concentrations of Earth’s major greenhouse gases.〈/jats:p〉 〈jats:p〉In 2022, the annual global average carbon dioxide concentration in the atmosphere rose to 417.1±0.1 ppm, which is 50% greater than the pre-industrial level. Global mean tropospheric methane abundance was 165% higher than its pre-industrial level, and nitrous oxide was 24% higher. All three gases set new record-high atmospheric concentration levels in 2022.〈/jats:p〉 〈jats:p〉Sea-surface temperature patterns in the tropical Pacific characteristic of La Niña and attendant atmospheric patterns tend to mitigate atmospheric heat gain at the global scale, but the annual global surface temperature across land and oceans was still among the six highest in records dating as far back as the mid-1800s. It was the warmest La Niña year on record. Many areas observed record or near-record heat. Europe as a whole observed its second-warmest year on record, with sixteen individual countries observing record warmth at the national scale. Records were shattered across the continent during the summer months as heatwaves plagued the region. On 18 July, 104 stations in France broke their all-time records. One day later, England recorded a temperature of 40°C for the first time ever. China experienced its second-warmest year and warmest summer on record. In the Southern Hemisphere, the average temperature across New Zealand reached a record high for the second year in a row. While Australia’s annual temperature was slightly below the 1991–2020 average, Onslow Airport in Western Australia reached 50.7°C on 13 January, equaling Australia's highest temperature on record.〈/jats:p〉 〈jats:p〉While fewer in number and locations than record-high temperatures, record cold was also observed during the year. Southern Africa had its coldest August on record, with minimum temperatures as much as 5°C below normal over Angola, western Zambia, and northern Namibia. Cold outbreaks in the first half of December led to many record-low daily minimum temperature records in eastern Australia.〈/jats:p〉 〈jats:p〉The effects of rising temperatures and extreme heat were apparent across the Northern Hemisphere, where snow-cover extent by June 2022 was the third smallest in the 56-year record, and the seasonal duration of lake ice cover was the fourth shortest since 1980. More frequent and intense heatwaves contributed to the second-greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Glaciers in the Swiss Alps lost a record 6% of their volume. In South America, the combination of drought and heat left many central Andean glaciers snow free by mid-summer in early 2022; glacial ice has a much lower albedo than snow, leading to accelerated heating of the glacier. Across the global cryosphere, permafrost temperatures continued to reach record highs at many high-latitude and mountain locations.〈/jats:p〉 〈jats:p〉In the high northern latitudes, the annual surface-air temperature across the Arctic was the fifth highest in the 123-year record. The seasonal Arctic minimum sea-ice extent, typically reached in September, was the 11th-smallest in the 43-year record; however, the amount of multiyear ice—ice that survives at least one summer melt season—remaining in the Arctic continued to decline. Since 2012, the Arctic has been nearly devoid of ice more than four years old.〈/jats:p〉 〈jats:p〉In Antarctica, an unusually large amount of snow and ice fell over the continent in 2022 due to several landfalling atmospheric rivers, which contributed to the highest annual surface mass balance, 15% to 16% above the 1991–2020 normal, since the start of two reanalyses records dating to 1980. It was the second-warmest year on record for all five of the long-term staffed weather stations on the Antarctic Peninsula. In East Antarctica, a heatwave event led to a new all-time record-high temperature of −9.4°C—44°C above the March average—on 18 March at Dome C. This was followed by the collapse of the critically unstable Conger Ice Shelf. More than 100 daily low sea-ice extent and sea-ice area records were set in 2022, including two new all-time annual record lows in net sea-ice extent and area in February.〈/jats:p〉 〈jats:p〉Across the world’s oceans, global mean sea level was record high for the 11th consecutive year, reaching 101.2 mm above the 1993 average when satellite altimetry measurements began, an increase of 3.3±0.7 over 2021. Globally-averaged ocean heat content was also record high in 2022, while the global sea-surface temperature was the sixth highest on record, equal with 2018. Approximately 58% of the ocean surface experienced at least one marine heatwave in 2022. In the Bay of Plenty, New Zealand’s longest continuous marine heatwave was recorded.〈/jats:p〉 〈jats:p〉A total of 85 named tropical storms were observed during the Northern and Southern Hemisphere storm seasons, close to the 1991–2020 average of 87. There were three Category 5 tropical cyclones across the globe—two in the western North Pacific and one in the North Atlantic. This was the fewest Category 5 storms globally since 2017. Globally, the accumulated cyclone energy was the lowest since reliable records began in 1981. Regardless, some storms caused massive damage. In the North Atlantic, Hurricane Fiona became the most intense and most destructive tropical or post-tropical cyclone in Atlantic Canada’s history, while major Hurricane Ian killed more than 100 people and became the third costliest disaster in the United States, causing damage estimated at $113 billion U.S. dollars. In the South Indian Ocean, Tropical Cyclone Batsirai dropped 2044 mm of rain at Commerson Crater in Réunion. The storm also impacted Madagascar, where 121 fatalities were reported.〈/jats:p〉 〈jats:p〉As is typical, some areas around the world were notably dry in 2022 and some were notably wet. In August, record high areas of land across the globe (6.2%) were experiencing extreme drought. Overall, 29% of land experienced moderate or worse categories of drought during the year. The largest drought footprint in the contiguous United States since 2012 (63%) was observed in late October. The record-breaking megadrought of central Chile continued in its 13th consecutive year, and 80-year record-low river levels in northern Argentina and Paraguay disrupted fluvial transport. In China, the Yangtze River reached record-low values. Much of equatorial eastern Africa had five consecutive below-normal rainy seasons by the end of 2022, with some areas receiving record-low precipitation totals for the year. This ongoing 2.5-year drought is the most extensive and persistent drought event in decades, and led to crop failure, millions of livestock deaths, water scarcity, and inflated prices for staple food items.〈/jats:p〉 〈jats:p〉In South Asia, Pakistan received around three times its normal volume of monsoon precipitation in August, with some regions receiving up to eight times their expected monthly totals. Resulting floods affected over 30 million people, caused over 1700 fatalities, led to major crop and property losses, and was recorded as one of the world’s costliest natural disasters of all time. Near Rio de Janeiro, Brazil, Petrópolis received 530 mm in 24 hours on 15 February, about 2.5 times the monthly February average, leading to the worst disaster in the city since 1931 with over 230 fatalities.〈/jats:p〉 〈jats:p〉On 14–15 January, the Hunga Tonga-Hunga Ha'apai submarine volcano in the South Pacific erupted multiple times. The injection of water into the atmosphere was unprecedented in both magnitude—far exceeding any previous values in the 17-year satellite record—and altitude as it penetrated into the mesosphere. The amount of water injected into the stratosphere is estimated to be 146±5 Terragrams, or ∼10% of the total amount in the stratosphere. It may take several years for the water plume to dissipate, and it is currently unknown whether this eruption will have any long-term climate effect.〈/jats:p〉
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 2
    Publication Date: 2023-04-26
    Description: Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 3
    Publication Date: 2023-01-30
    Keywords: ABN1314-103 ice core; Age; AGE; Age-depth model (ALC01112018); Ant_ABN-1314; Antarctica; Calculated from density and age-depth model; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; density; Density, ice; Depth, bottom/max; DEPTH, ice/snow; Depth, top/min; East Antarctica; IC; Ice core; Ice corer; nitrate; nitrogen isotope ratio (δ15N); Physical measurement; Sample ID; surface mass balance; Surface mass balance; Time in years
    Type: Dataset
    Format: text/tab-separated-values, 774 data points
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  • 4
    Publication Date: 2023-01-30
    Description: Nitrate concentration and isotopic (δ15NNO3) data, ice density, and surface mass balance estimates from the ABN1314-103 ice core. This 103 m long core was drilled beginning on 07 January 2014 as one of three ice cores at Aurora Basin North, Antarctica (-71.17, 111.37, 2679 m.a.s.l), in the 2013-2014 field season. The age-depth model for ABN1314-103 was matched through ion profiles from an annually-resolved model (ALC01112018) originally developed for one of the other ABN cores through seasonal ion and water isotope cycles and constrained by volcanic horizons. Each 1 m segment of the core was weighed and measured for ice density calculations, and then sampled for nitrate at 0.33 m resolution. Nitrate concentrations were taken on melted ice aliquots with ion chromatography, while isotopic analysis was achieved through bacterial denitrification and MAT 253 mass spectrometry after concentrating with anionic resin. Using the density data and the age-depth model's dates for the top and bottom of each 1 m core segment, we reconstructed a history of surface mass balance changes as recorded in ABN1314-103. Additionally, we also estimated the effect of upstream topographic changes on the ice core's surface mass balance record through a ground penetrating radar transect that extended 11.5 km against the direction of glacial ice flow. The modern SMB changes along this upstream transect were linked to ABN1314-103 core depths by through the local horizontal ice flow rate (16.2 m a-1) and the core's age-depth model, and included here for comparative analysis. See Akers et al., 2022 for more analytical details.
    Keywords: Antarctica; density; Ice core; nitrate; nitrogen isotope ratio (δ15N); surface mass balance
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 5
    Publication Date: 2023-01-30
    Description: This study presents data collected from International Ocean Discovery Program (IODP) Expedition 355 Arabian Sea Monsoon to investigate changes in sediment provenance as well as the effect of sediment transport processes on deep-sea sediment samples. From Site U1457, 83 sediment samples were analyzed, complemented by 44 samples from Site U1456. Samples were analyzed for bulk grain-size using a Malvern Mastersizer 2000. The clay fraction was separated, digested, and analyzed for K/Al ratios using inductively couple plasma optical emission spectroscopy (ICP-OES). Radiogenic strontium (87Sr/86Sr) was measured using a Neptune Plus multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS) and a Triton Plus multicollector thermal ionization mass spectrometer (TIMS). A subset of 38 samples were analyzed for radiogenic neodymium composition (143Nd/144Nd) using TIMS.
    Keywords: Arabian Sea; clay; erosion; Expedition 355; neodymium (Nd); physical fractionation; Site U1456; Site U1457; Strontium (Sr)
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 6
    Publication Date: 2023-02-13
    Keywords: ABN1314-103 ice core; Age; AGE; Age-depth model (ALC01112018); Ant_ABN-1314; Antarctica; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; Colorimetry and/or ion chromatography; density; Depth, bottom/max; DEPTH, ice/snow; Depth, top/min; East Antarctica; Ground-penetrating radar (GPR); IC; Ice core; Ice corer; Mass spectrometer, Finnigan, MAT 253; nitrate; Nitrate; nitrogen isotope ratio (δ15N); Physical measurement; Sample ID; surface mass balance; Surface mass balance; Time in years; δ15N; δ15N, standard error
    Type: Dataset
    Format: text/tab-separated-values, 3207 data points
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  • 7
    Publication Date: 2023-07-03
    Keywords: 355-U1456A; 355-U1456C; 355-U1456D; AGE; Arabian Sea; clay; Cumulative Offset; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; erosion; Event label; Exp355; Expedition 355; ICP-OES; Instrument; Joides Resolution; Lithologic unit/sequence; neodymium (Nd); Neodymium-143/Neodymium-144 ratio; Neodymium-143/Neodymium-144 ratio, error; Neptune Plus multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS) + Triton Plus multicollector thermal ionization mass spectrometer (TIMS); physical fractionation; Potassium/Aluminium ratio; Potassium/Aluminium ratio, error; Sample code/label; Sample comment; Site U1456; Site U1457; Strontium (Sr); Strontium-87/Strontium-86 ratio; Strontium-87/Strontium-86 ratio, error; Thermal Ionization Mass Spectrometry (TIMS); ε-Neodymium
    Type: Dataset
    Format: text/tab-separated-values, 404 data points
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  • 8
    Publication Date: 2023-07-03
    Keywords: -; 355-U1457A; 355-U1457B; 355-U1457C; AGE; Arabian Sea; clay; Clay minerals; DEPTH, sediment/rock; Diameter; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; erosion; Event label; Exp355; Expedition 355; ICP-OES; Joides Resolution; Laser diffraction particle size analyser (Malvern Mastersizer 2000); Mode, grain size; neodymium (Nd); physical fractionation; Sample code/label; Sand; Silt; Site U1456; Site U1457; Size fraction 〈 0.020 µm; Size fraction 〉 2 mm, gravel; Size fraction 0.02-0.2 µm; Size fraction 0.20-0.24 µm; Size fraction 0.24-0.28 µm; Size fraction 0.28-0.32 µm; Size fraction 0.32-0.36 µm; Size fraction 0.36-0.42 µm; Size fraction 0.42-0.48 µm; Size fraction 0.48-0.55 µm; Size fraction 0.55-0.63 µm; Size fraction 0.63-0.72 µm; Size fraction 0.72-0.83 µm; Size fraction 0.83-0.96 µm; Size fraction 0.96-1.1 µm; Size fraction 1.10-1.26 µm; Size fraction 1.26-1.45 µm; Size fraction 1.45-1.66 µm; Size fraction 1.66-1.91 µm; Size fraction 1.91-2.19 µm; Size fraction 10.00-11.48 µm; Size fraction 104.71-120.23 µm; Size fraction 1096.48-1258.93 µm; Size fraction 11.48-13.18 µm; Size fraction 120.23-138.04 µm; Size fraction 1258.93-1445.44 µm; Size fraction 13.18-15.14 µm; Size fraction 138.04-158.49 µm; Size fraction 1445.44-1659.59 µm; Size fraction 15.14-17.38 µm; Size fraction 158.49-181.97 µm; Size fraction 1659.59-1905.46 µm; Size fraction 17.38-19.95 µm; Size fraction 181.97-208.93 µm; Size fraction 19.95-22.91 µm; Size fraction 1905.46-2000 µm; Size fraction 2.19-2.51 µm; Size fraction 2.51-2.88 µm; Size fraction 2.88-3.31 µm; Size fraction 208.93-239.88 µm; Size fraction 22.91-26.3 µm; Size fraction 239.88-275.42 µm; Size fraction 26.30-30.2 µm; Size fraction 275.42-316.23 µm; Size fraction 3.31-3.8 µm; Size fraction 3.80-4.37 µm; Size fraction 30.20-34.67 µm; Size fraction 316.23-363.08 µm; Size fraction 34.67-39.81 µm; Size fraction 363.08-416.87 µm; Size fraction 39.81-45.71 µm; Size fraction 4.37-5.01 µm; Size fraction 416.87-478.63 µm; Size fraction 45.71-52.48 µm; Size fraction 478.63-549.54 µm; Size fraction 5.01-5.75 µm; Size fraction 5.75-6.61 µm; Size fraction 52.48-60.26 µm; Size fraction 549.54-630.96 µm; Size fraction 6.61-7.59 µm; Size fraction 60.26-69.18 µm; Size fraction 630.96-724.44 µm; Size fraction 69.18-79.43 µm; Size fraction 7.59-8.71 µm; Size fraction 724.44-831.76 µm; Size fraction 79.43-91.2 µm; Size fraction 8.71-10 µm; Size fraction 831.76-954.99 µm; Size fraction 91.20-104.71 µm; Size fraction 954.99-1096.48 µm; Standard deviation; Strontium (Sr)
    Type: Dataset
    Format: text/tab-separated-values, 6308 data points
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  • 9
    Publication Date: 2023-07-03
    Keywords: -; 355-U1456A; 355-U1456C; 355-U1456D; AGE; Arabian Sea; clay; Clay minerals; DEPTH, sediment/rock; Diameter; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; erosion; Event label; Exp355; Expedition 355; ICP-OES; Joides Resolution; Laser diffraction particle size analyser (Malvern Mastersizer 2000); Mode, grain size; neodymium (Nd); physical fractionation; Sample code/label; Sand; Silt; Site U1456; Site U1457; Size fraction 〈 0.020 µm; Size fraction 〉 2 mm, gravel; Size fraction 0.02-0.2 µm; Size fraction 0.20-0.24 µm; Size fraction 0.24-0.28 µm; Size fraction 0.28-0.32 µm; Size fraction 0.32-0.36 µm; Size fraction 0.36-0.42 µm; Size fraction 0.42-0.48 µm; Size fraction 0.48-0.55 µm; Size fraction 0.55-0.63 µm; Size fraction 0.63-0.72 µm; Size fraction 0.72-0.83 µm; Size fraction 0.83-0.96 µm; Size fraction 0.96-1.1 µm; Size fraction 1.10-1.26 µm; Size fraction 1.26-1.45 µm; Size fraction 1.45-1.66 µm; Size fraction 1.66-1.91 µm; Size fraction 1.91-2.19 µm; Size fraction 10.00-11.48 µm; Size fraction 104.71-120.23 µm; Size fraction 1096.48-1258.93 µm; Size fraction 11.48-13.18 µm; Size fraction 120.23-138.04 µm; Size fraction 1258.93-1445.44 µm; Size fraction 13.18-15.14 µm; Size fraction 138.04-158.49 µm; Size fraction 1445.44-1659.59 µm; Size fraction 15.14-17.38 µm; Size fraction 158.49-181.97 µm; Size fraction 1659.59-1905.46 µm; Size fraction 17.38-19.95 µm; Size fraction 181.97-208.93 µm; Size fraction 19.95-22.91 µm; Size fraction 1905.46-2000 µm; Size fraction 2.19-2.51 µm; Size fraction 2.51-2.88 µm; Size fraction 2.88-3.31 µm; Size fraction 208.93-239.88 µm; Size fraction 22.91-26.3 µm; Size fraction 239.88-275.42 µm; Size fraction 26.30-30.2 µm; Size fraction 275.42-316.23 µm; Size fraction 3.31-3.8 µm; Size fraction 3.80-4.37 µm; Size fraction 30.20-34.67 µm; Size fraction 316.23-363.08 µm; Size fraction 34.67-39.81 µm; Size fraction 363.08-416.87 µm; Size fraction 39.81-45.71 µm; Size fraction 4.37-5.01 µm; Size fraction 416.87-478.63 µm; Size fraction 45.71-52.48 µm; Size fraction 478.63-549.54 µm; Size fraction 5.01-5.75 µm; Size fraction 5.75-6.61 µm; Size fraction 52.48-60.26 µm; Size fraction 549.54-630.96 µm; Size fraction 6.61-7.59 µm; Size fraction 60.26-69.18 µm; Size fraction 630.96-724.44 µm; Size fraction 69.18-79.43 µm; Size fraction 7.59-8.71 µm; Size fraction 724.44-831.76 µm; Size fraction 79.43-91.2 µm; Size fraction 8.71-10 µm; Size fraction 831.76-954.99 µm; Size fraction 91.20-104.71 µm; Size fraction 954.99-1096.48 µm; Standard deviation; Strontium (Sr)
    Type: Dataset
    Format: text/tab-separated-values, 3484 data points
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  • 10
    Publication Date: 2023-07-06
    Description: The SOAP voyage examined air-sea interactions over the productive waters of the Chatham Rise, east of New Zealand onboard the RV Tangaroa (New Zealand National Institute of Water and Atmospheric Research, Wellington) from February 12 to March 7 (Law et al., 2017: doi:10.5194/acp-17-13645-2017). 23 seawater samples were collected throughout the voyage for the purpose of generating nascent SSA. Seawater samples were collected from the ocean surface during workboat operations (approximately 10 cm depth) or from the mixed layer (3 - 12 m depth, always less than the measured mixed layer depth) or deep water samples. Surface samples were collected in prewashed 5L PTFE bottles, subsurface measurements were colected in Niskin bottles onboard a CTD rosette. Nascent SSA was generated in-situ in a 0.45 m3 cylindrical polytetrafluoroethylene chamber housing four sintered glass filters with porosities between 16 and 250 μm (Cravigan et al., 2019: https://doi.org/10.5194/acp-2019-797). Dried and filtered compressed air was passed through the glass filters at a flow rate of 15.5 ± 3 L/min and resulting SSA was sampled from the headspace of the chamber. The volatility and hygroscopicity of nascent SSA was determined with a volatility and hygroscopicity tandem differential mobility analyser (VH-TDMA) (Johnson et al., 2004: doi:10.1016/j.jaerosci.2003.10.008, 2008: doi:10.1016/j.jaerosci.2008.05.005). A diffusion drier was used to dry the sample flow to 20 ± 5 % RH prior to characterisation by the VH-TDMA. The VH-TDMA used two TSI 3010 condensation particle counters. The aerosol sample flow rate for each scanning mobility particle sizer was 1 L/min, resulting in a total inlet flow of 2 L/min, the sheath flow for the pre-DMA, V-DMA and H-DMA were 11, 6 and 6 L/min, respectively. The dependence of HGF on RH at ambient temperature was measured for one water sample (workboat 9) to provide the deliquescence relative humidity (DRH). All VH-TDMA data were inverted using the TDMAinv algorithm (Gysel et al., 2009: doi:10.1016/j.jaerosci.2008.07.013). The seawater chlorophyll-a concentration was measured by filtering 2 litres of sample water onto GF/F Whatman filters, with immediate freezing in liquid nitrogen and subsequent analysis within 3 months of collection. Filters were ground and chlorophyll-a extracted in 90 % acetone with concentration determined by a calibrated fluorometer (Perkin-Elmer), with an analytical precision of 0.001 mg/m3 (Law et al., 2011: doi:10.1016/j.dsr2.2010.10.018).
    Keywords: aerosols; ccn; Chatham Rise; DATE/TIME; Depth, description; FTIR; functional groups; Humidity, relative; Humidity, relative, maximum; Humidity, relative, minimum; Hygroscopic growth factor; Hygroscopic growth factor, raw counts; hygroscopicity; IBA; ion beam; Particle, geometric median diameter; PTFE bottle, 5L; sea spray; SOAP; SOAP (Surface Ocean Aerosol Production); SSA; TAN1203; Tangaroa; TDMA; Temperature, water; volatility; Volatility-Hygroscopicity Tandem Differential Mobility Analyser (VH-TDMA); WB9
    Type: Dataset
    Format: text/tab-separated-values, 42292 data points
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