Description: Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño–Southern Oscillation.

Description: Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here for personal use, not for redistribution. The definitive version was published in Annual Review of Marine Science 8 (2016): 185-215, doi:10.1146/annurev-marine-052915-100829.

Description: The ocean, a central component of Earth’s climate system, is changing. Given the global scope of these changes, highly accurate measurements of physical and biogeochemical properties need to be conducted over the full water column, spanning the ocean basins from coast to coast, and repeated every decade at a minimum, with a ship-based observing system. Since the late 1970s, when the Geochemical Ocean Sections Study (GEOSECS) conducted the first global survey of this kind, the World Ocean Circulation Experiment (WOCE) and Joint Global Ocean Flux Study (JGOFS), and now the Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP) have collected these “reference standard” data that allow quantification of ocean heat and carbon uptake, and variations in salinity, oxygen, nutrients, and acidity on basin scales. The evolving GO-SHIP measurement suite also provides new global information about dissolved organic carbon, a large bioactive reservoir of carbon.

Description: Climate Observations Division of the U.S. NOAA Climate Program Office and NOAA Research; Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA10OAR4320148; U.S. National Science Foundation [OCE- 0223869; OCE-0752970; OCE-0825163; OCE-1434000; OCE 0752972; OCE-0752980; OCE-1232962; OCE-1155983; OCE-1436748]; U.S. CLIVAR Project Office; Global Environment and Marine Department, Japan Meteorological Agency; Australian Climate Change Science Program (Australian Department of Environment and CSIRO); U.K. Natural Environment Research Council; European Union’s FP7 grant agreement 264879 (CarboChange); Horizon 2020 grant agreement No 633211; ETH Zurich Switzerland.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Meyssignac, B., Boyer, T., Zhao, Z., Hakuba, M. Z., Landerer, F. W., Stammer, D., Koehl, A., Kato, S., L'Ecuyer, T., Ablain, M., Abraham, J. P., Blazquez, A., Cazenave, A., Church, J. A., Cowley, R., Cheng, L., Domingues, C. M., Giglio, D., Gouretski, V., Ishii, M., Johnson, G. C., Killick, R. E., Legler, D., Llovel, W., Lyman, J., Palmer, M. D., Piotrowicz, S., Purkey, S. G., Roemmich, D., Roca, R., Savita, A., von Schuckmann, K., Speich, S., Stephens, G., Wang, G., Wijffels, S. E., & Zilberman, N. Measuring global ocean heat content to estimate the Earth energy Imbalance. Frontiers in Marine Science, 6, (2019): 432, doi: 10.3389/fmars.2019.00432.

Description: The energy radiated by the Earth toward space does not compensate the incoming radiation from the Sun leading to a small positive energy imbalance at the top of the atmosphere (0.4–1 Wm–2). This imbalance is coined Earth’s Energy Imbalance (EEI). It is mostly caused by anthropogenic greenhouse gas emissions and is driving the current warming of the planet. Precise monitoring of EEI is critical to assess the current status of climate change and the future evolution of climate. But the monitoring of EEI is challenging as EEI is two orders of magnitude smaller than the radiation fluxes in and out of the Earth system. Over 93% of the excess energy that is gained by the Earth in response to the positive EEI accumulates into the ocean in the form of heat. This accumulation of heat can be tracked with the ocean observing system such that today, the monitoring of Ocean Heat Content (OHC) and its long-term change provide the most efficient approach to estimate EEI. In this community paper we review the current four state-of-the-art methods to estimate global OHC changes and evaluate their relevance to derive EEI estimates on different time scales. These four methods make use of: (1) direct observations of in situ temperature; (2) satellite-based measurements of the ocean surface net heat fluxes; (3) satellite-based estimates of the thermal expansion of the ocean and (4) ocean reanalyses that assimilate observations from both satellite and in situ instruments. For each method we review the potential and the uncertainty of the method to estimate global OHC changes. We also analyze gaps in the current capability of each method and identify ways of progress for the future to fulfill the requirements of EEI monitoring. Achieving the observation of EEI with sufficient accuracy will depend on merging the remote sensing techniques with in situ measurements of key variables as an integral part of the Ocean Observing System.

Description: GJ was supported by the NOAA Research. MP and RK were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. JC was partially supported by the Centre for Southern Hemisphere Oceans Research, a joint research centre between QNLM and CSIRO. CD and AS were funded by the Australian Research Council (FT130101532 and DP160103130) and its Centre of Excellence for Climate Extremes (CLEX). IQuOD team members (TB, RC, LC, CD, VG, MI, MP, and SW) were supported by the Scientific Committee on Oceanic Research (SCOR) Working Group 148, funded by the National SCOR Committees and a grant to SCOR from the U.S. National Science Foundation (Grant OCE-1546580), as well as the Intergovernmental Oceanographic Commission of UNESCO/International Oceanographic Data and Information Exchange (IOC/IODE) IQuOD Steering Group. ZZ was supported by the National Aeronautics and Space Administration (NNX17AH14G). LC was supported by the National Key Research and Development Program of China (2017YFA0603200 and 2016YFC1401800).

Description: Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 35(2), (2022): 851–875, https://doi.org/10.1175/JCLI-D-20-0603.1.

Description: The Earth system is accumulating energy due to human-induced activities. More than 90% of this energy has been stored in the ocean as heat since 1970, with ∼60% of that in the upper 700 m. Differences in upper-ocean heat content anomaly (OHCA) estimates, however, exist. Here, we use a dataset protocol for 1970–2008—with six instrumental bias adjustments applied to expendable bathythermograph (XBT) data, and mapped by six research groups—to evaluate the spatiotemporal spread in upper OHCA estimates arising from two choices: 1) those arising from instrumental bias adjustments and 2) those arising from mathematical (i.e., mapping) techniques to interpolate and extrapolate data in space and time. We also examined the effect of a common ocean mask, which reveals that exclusion of shallow seas can reduce global OHCA estimates up to 13%. Spread due to mapping method is largest in the Indian Ocean and in the eddy-rich and frontal regions of all basins. Spread due to XBT bias adjustment is largest in the Pacific Ocean within 30°N–30°S. In both mapping and XBT cases, spread is higher for 1990–2004. Statistically different trends among mapping methods are found not only in the poorly observed Southern Ocean but also in the well-observed northwest Atlantic. Our results cannot determine the best mapping or bias adjustment schemes, but they identify where important sensitivities exist, and thus where further understanding will help to refine OHCA estimates. These results highlight the need for further coordinated OHCA studies to evaluate the performance of existing mapping methods along with comprehensive assessment of uncertainty estimates.

Description: AS is supported by a Tasmanian Graduate Research Scholarship, a CSIRO-UTAS Quantitative Marine Science top-up, and by the Australian Research Council (ARC) (CE170100023; DP160103130). CMD was partially supported by ARC (FT130101532) and the Natural Environmental Research Council (NE/P019293/1). RC was supported through funding from the Earth Systems and Climate Change Hub of the Australian Government’s National Environmental Science Program. TB is supported by the Climate Observation and Monitoring Program, National Oceanic and Atmosphere Administration, U.S. Department of commerce. GCJ and JML are supported by NOAA Research and the NOAA Ocean Climate Observation Program. This is PMEL contribution number 5065. JAC is supported by the Centre for Southern Hemisphere Oceans Research (CSHOR), jointly funded by the Qingdao National Laboratory for Marine Science and Technology (QNLM, China) and the Commonwealth Scientific and Industrial Research Organization (CSIRO, Australia) and Australian Research Council’s Discovery Project funding scheme (project DP190101173). The research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). Data used in this study are available on request.

Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(8), (2021): S143–S198, https://doi.org/10.1175/BAMS-D-21-0083.1.

Description: This chapter details 2020 global patterns in select observed oceanic physical, chemical, and biological variables relative to long-term climatologies, their differences between 2020 and 2019, and puts 2020 observations in the context of the historical record. In this overview we address a few of the highlights, first in haiku, then paragraph form: La Niña arrives, shifts winds, rain, heat, salt, carbon: Pacific—beyond. Global ocean conditions in 2020 reflected a transition from an El Niño in 2018–19 to a La Niña in late 2020. Pacific trade winds strengthened in 2020 relative to 2019, driving anomalously westward Pacific equatorial surface currents. Sea surface temperatures (SSTs), upper ocean heat content, and sea surface height all fell in the eastern tropical Pacific and rose in the western tropical Pacific. Efflux of carbon dioxide from ocean to atmosphere was larger than average across much of the equatorial Pacific, and both chlorophyll-a and phytoplankton carbon concentrations were elevated across the tropical Pacific. Less rain fell and more water evaporated in the western equatorial Pacific, consonant with increased sea surface salinity (SSS) there. SSS may also have increased as a result of anomalously westward surface currents advecting salty water from the east. El Niño–Southern Oscillation conditions have global ramifications that reverberate throughout the report.

Description: Argo data used in the chapter were collected and made freely available by the International Argo Program and the national programs that contribute to it. (https://argo.ucsd.edu, https://www.ocean-ops. org). The Argo Program is part of the Global Ocean Observing System. Many authors of the chapter are supported by NOAA Research, the NOAA Global Ocean Monitoring and Observing Program, or the NOAA Ocean Acidification Program. • L. Cheng is supported by National Natural Science Foundation of China (42076202) and Strategic Priority Research Program of the Chinese Academy of Sciences (XDB42040402. • R. E. Killick is supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. PMEL contribution numbers 5214, 5215, 5216, 5217, and 5247.

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in von Schuckmann, K., Cheng, L., Palmer, M. D., Hansen, J., Tassone, C., Aich, V., Adusumilli, S., Beltrami, H., Boyer, T., Cuesta-Valero, F. J., Desbruyeres, D., Domingues, C., Garcia-Garcia, A., Gentine, P., Gilson, J., Gorfer, M., Haimberger, L., Ishii, M., Johnson, G. C., Killick, R., King, B. A., Kirchengast, G., Kolodziejczyk, N., Lyman, J., Marzeion, B., Mayer, M., Monier, M., Monselesan, D. P., Purkey, S., Roemmich, D., Schweiger, A., Seneviratne, S., I., Shepherd, A., Slater, D. A., Steiner, A. K., Straneo, F., Timmermans, M., & Wijffels, S. E. Heat stored in the Earth system: where does the energy go? Earth System Science Data, 12(3), (2020): 2013-2041, doi:10.5194/essd-12-2013-2020.

Description: Human-induced atmospheric composition changes cause a radiative imbalance at the top of the atmosphere which is driving global warming. This Earth energy imbalance (EEI) is the most critical number defining the prospects for continued global warming and climate change. Understanding the heat gain of the Earth system – and particularly how much and where the heat is distributed – is fundamental to understanding how this affects warming ocean, atmosphere and land; rising surface temperature; sea level; and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory and presents an updated assessment of ocean warming estimates as well as new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960–2018. The study obtains a consistent long-term Earth system heat gain over the period 1971–2018, with a total heat gain of 358±37 ZJ, which is equivalent to a global heating rate of 0.47±0.1 W m−2. Over the period 1971–2018 (2010–2018), the majority of heat gain is reported for the global ocean with 89 % (90 %), with 52 % for both periods in the upper 700 m depth, 28 % (30 %) for the 700–2000 m depth layer and 9 % (8 %) below 2000 m depth. Heat gain over land amounts to 6 % (5 %) over these periods, 4 % (3 %) is available for the melting of grounded and floating ice, and 1 % (2 %) is available for atmospheric warming. Our results also show that EEI is not only continuing, but also increasing: the EEI amounts to 0.87±0.12 W m−2 during 2010–2018. Stabilization of climate, the goal of the universally agreed United Nations Framework Convention on Climate Change (UNFCCC) in 1992 and the Paris Agreement in 2015, requires that EEI be reduced to approximately zero to achieve Earth's system quasi-equilibrium. The amount of CO2 in the atmosphere would need to be reduced from 410 to 353 ppm to increase heat radiation to space by 0.87 W m−2, bringing Earth back towards energy balance. This simple number, EEI, is the most fundamental metric that the scientific community and public must be aware of as the measure of how well the world is doing in the task of bringing climate change under control, and we call for an implementation of the EEI into the global stocktake based on best available science. Continued quantification and reduced uncertainties in the Earth heat inventory can be best achieved through the maintenance of the current global climate observing system, its extension into areas of gaps in the sampling, and the establishment of an international framework for concerted multidisciplinary research of the Earth heat inventory as presented in this study. This Earth heat inventory is published at the German Climate Computing Centre (DKRZ, https://www.dkrz.de/, last access: 7 August 2020) under the DOI https://doi.org/10.26050/WDCC/GCOS_EHI_EXP_v2 (von Schuckmann et al., 2020).

Description: Matthew D. Palmer and Rachel E. Killick were supported by the Met Office Hadley Centre Climate Programme funded by the BEIS and Defra. PML authors were supported by contribution number 5053. Catia M. Domingues was supported by an ARC Future Fellowship (FT130101532). Lijing Cheng is supported by the Key Deployment Project of Centre for Ocean Mega-Research of Science, CAS (COMS2019Q01). Maximilian Gorfer was supported by WEGC atmospheric remote sensing and climate system research group young scientist funds. Michael Mayer was supported by Austrian Science Fund project P33177. This work was supported by grants from the National Sciences and Engineering Research Council of Canada Discovery Grant (NSERC DG 140576948) and the Canada Research Chairs Program (CRC 230687) to Hugo Beltrami. Almudena García-García and Francisco José Cuesta-Valero are funded by Beltrami's CRC program, the School of Graduate Studies at Memorial University of Newfoundland and the Research Office at St. Francis Xavier University. Fiamma Straneo was supported by NSF OCE 1657601. Susheel Adusumilli was supported by NASA grant 80NSSC18K1424.

Description: The historical archive of global ocean subsurface temperature contains a large proportion of poorly quality-controlled as well as biased data. As a result, efforts to analyze past ocean change and variability are confounded, as is the use of ocean data assimilation systems. Currently many data centers perform automated ‘quick and dirty QC’ – redoing the same job poorly many times around the world. There have been no previous efforts to form a clean and definitive and very much needed historical archive. No single group has the manpower and resources to do the job properly – thus international cooperation is needed. The IQuOD 4th Workshop goals are to: Provide updates on recent IQuOD activities, particularly SCOR WG 148 and IOC/IODE; progress on the development and implementation of intelligent metadata, uncertainty estimates, duplicates flagging and the platform for AutoQC benchmarking tests; plans for next steps for the task teams; discussion on capacity building; establishing synergies between IQuOD and the XBT Science Team.

Description: Published

Description: Non Refereed

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〉

Description: Using an international, multi-model suite of historical forecasts from the World Climate Research Programme (WCRP) Climate-system Historical Forecast Project (CHFP), we compare the seasonal prediction skill in boreal wintertime between models that resolve the stratosphere and its dynamics (“high-top”) and models that do not (“low-top”). We evaluate hindcasts that are initialized in November, and examine the model biases in the stratosphere and how they relate to boreal wintertime (Dec-Mar) seasonal forecast skill. We are unable to detect more skill in the high-top ensemble-mean than the low-top ensemble-mean in forecasting the wintertime North Atlantic Oscillation, but model performance varies widely. Increasing the ensemble size clearly increases the skill for a given model. We then examine two major processes involving stratosphere-troposphere interactions (the El Niño-Southern Oscillation/ENSO and the Quasi-biennial Oscillation/QBO) and how they relate to predictive skill on intra-seasonal to seasonal timescales, particularly over the North Atlantic and Eurasia regions. High-top models tend to have a more realistic stratospheric response to El Niño and the QBO compared to low-top models. Enhanced conditional wintertime skill over high-latitudes and the North Atlantic region during winters with El Niño conditions suggests a possible role for a stratospheric pathway.

Description: The Earth system is accumulating energy due to human-induced activities. More than 90% of this energy has been stored in the ocean as heat since 1970, with similar to 60% of that in the upper 700 m. Differences in upper-ocean heat content anomaly (OHCA) estimates, however, exist. Here, we use a dataset protocol for 1970-2008-with six instrumental bias adjustments applied to expendable bathythermograph (XBT) data, and mapped by six research groups-to evaluate the spatiotemporal spread in upper OHCA estimates arising from two choices: 1) those arising from instrumental bias adjustments and 2) those arising from mathematical (i.e., mapping) techniques to interpolate and extrapolate data in space and time. We also examined the effect of a common ocean mask, which reveals that exclusion of shallow seas can reduce global OHCA estimates up to 13%. Spread due to mapping method is largest in the Indian Ocean and in the eddy-rich and frontal regions of all basins. Spread due to XBT bias adjustment is largest in the Pacific Ocean within 30 degrees N-30 degrees S. In both mapping and XBT cases, spread is higher for 1990-2004. Statistically different trends among mapping methods are found not only in the poorly observed Southern Ocean but also in the well-observed northwest Atlantic. Our results cannot determine the best mapping or bias adjustment schemes, but they identify where important sensitivities exist, and thus where further understanding will help to refine OHCA estimates. These results highlight the need for further coordinated OHCA studies to evaluate the performance of existing mapping methods along with comprehensive assessment of uncertainty estimates.