The years since 2000 have been a golden age in in situ ocean observing with the proliferation and organization of autonomous platforms such as surface drogued buoys and subsurface Argo profiling floats augmenting ship-based observations. Global time series of mean sea surface temperature and ocean heat content are routinely calculated based on data from these platforms, enhancing our understanding of the ocean’s role in Earth’s climate system. Individual measurements of meteorological, sea surface, and subsurface variables directly improve our understanding of the Earth system, weather forecasting, and climate projections. They also provide the data necessary for validating and calibrating satellite observations. Maintaining this ocean observing system has been a technological, logistical, and funding challenge. The global COVID-19 pandemic, which took hold in 2020, added strain to the maintenance of the observing system. A survey of the contributing components of the observing system illustrates the impacts of the pandemic from January 2020 through December 2021. The pandemic did not reduce the short-term geographic coverage (days to months) capabilities mainly due to the continuation of autonomous platform observations. In contrast, the pandemic caused critical loss to longer-term (years to decades) observations, greatly impairing the monitoring of such crucial variables as ocean carbon and the state of the deep ocean. So, while the observing system has held under the stress of the pandemic, work must be done to restore the interrupted replenishment of the autonomous components and plan for more resilient methods to support components of the system that rely on cruise-based measurements.

This paper describes the new International Comprehensive Ocean-Atmosphere Data Set (ICOADS) near-real-time (NRT) release (R3.0.2), with greatly enhanced completeness over the previous version (R3.0.1). R3.0.1 had been operationally produced monthly from January 2015 onward, with input data from the World Meteorological Organization (WMO) Global Telecommunication Systems (GTS) transmissions in the Traditional Alphanumeric Codes (TAC) format. Since the release of R3.0.1, however, many observing platforms have changed, or are in the process of transitioning, to the Binary Universal Form for Representation of Meteorological Data (BUFR) format. R3.0.2 combines input data from both BUFR and TAC formats. In this paper, we describe input data sources; the BUFR decoding process for observations from drifting buoys, moored buoys, and ships; and the data quality control of the TAC and BUFR data streams. We also describe how the TAC and BUFR streams were merged to upgrade R3.0.1 into R3.0.2 with duplicates removed. Finally, we compare the number of reports and spatial coverage of essential climate variables (ECVs) between R3.0.1 and R3.0.2. ICOADS NRT R3.0.2 shows both quantitative and qualitative gains from the inclusion of BUFR reports. The number of observations in R3.0.2 increased by nearly 1 million reports per month, and the coverage of buoy and ship sea surface temperatures (SSTs) on monthly 2 & DEG; x 2 & DEG; grids increased by 20%. The number of reported ECVs also increased in R3.0.2. For example, observations of SST and sea level pressure (SLP) increased by around 30% and 20%, respectively, as compared to R3.0.1, and salinity is a new addition to the ICOADS NRT product in R3.0.2.Significance StatementThe International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is the largest collection of surface marine observations spanning from 1662 to the present. A new version, ICOADS near-real-time 3.0.2, includes data transmitted in the Binary Universal Form for Representation of Meteorological Data (BUFR) format, in combination with Traditional Alphanumeric Codes (TAC) data. Many of the organizations that report observations in near-real time have moved to BUFR, so this update brings ICOADS into alignment with collections and archives of these international data distributions. By including the BUFR reports, the number of observations in the upgraded version of ICOADS increased by nearly one million reports per month and spatial coverage of buoy and ship SSTs increased by 20% over the previous version.

The NOAA Daily Optimum Interpolation Sea Surface Temperature dataset (DOISST) has recently been updated to v2.1 (January 2016-present). Its accuracy may impact the climate assessment, monitoring and prediction, and environment-related applications. Its performance, together with those of seven other well-known sea surface temperature (SST) products, is assessed by comparison with buoy and Argo observations in the global oceans on daily 0.25 degrees X 0.25 degrees resolution from January 2016 to June 2020. These seven SST products are NASA MUR25, GHRSST GMPE, BoM GAMSSA, UKMO OSTIA, NOAA GPB, ESA CCI, and CMC. Our assessments indicate that biases and root-mean-square difference (RMSDs) in reference to all buoys and all Argo floats are low in DOISST. The bias in reference to the independent 10% of buoy SSTs remains low in DOISST, but the RMSD is slightly higher in DOISST than in OSTIA and CMC. The biases in reference to the independent 10% of Argo observations are low in CMC, DOISST, and GMPE; also, RMSDs are low in GMPE and CMC. The biases are similar in GAMSSA, OSTIA, GPB, and CCI whether they are compared against all buoys, all Argo, or the 10% of buoy or 10% of Argo observations, while the RMSDs against Argo observations are slightly smaller than those against buoy observations. These features indicate a good performance of DOISST v2.1 among the eight products, which may benefit from ingesting the Argo observations by expanding global and regional spatial coverage of in situ observations for effective bias correction of satellite data.

Historical observational climate records are crucial in understanding climatic variability, extreme past weather and climate events and allowing us to make informed decisions for better societal adaptation to climate change. Historical observations are also a key component to derive reanalysis products and evaluate climate models.The management of both marine and land historical datasets has been highly fragmented, leading to diverse data holdings held by multiple institutions. Consequently, it is necessary to confront the challenges of: a plethora of distinct data formats; gross duplication of records with differing identifiers, names; and in many cases varying geo-location information. Within available land and marine data holdings there are greatly differing levels of completeness, data quality checks and data processing applied. There are further issues with limited data discovery metadata and sometimes a distinct lack of traceability to the underlying original data source. In light of these issues, we have produced The C3S Global Land and Marine Observations Database which is part of the Copernicus Climate Change Service, making climate data and information more easily accessible to support adaptation and mitigation policies of the European Union and the wider global community This talk outlines progress of the Global Land and Marine Observations Database service in securing data sources and introduces the data deposit component. We present details of land based data holdings inventoried, highlighting priority needs in terms of periods, regions and Essential Climate Variables (ECVs) where additional land based data could bring most benefit. These holdings are being iteratively merged and integrated to best meet user needs and are served to the user via the Copernicus Climate Data Store (CDS). Details of the current land based data release are also presented in this talk. The secure Data Deposit Service enables any data provider to share additional data and metadata with the service. We encourage all data owners to share their data with the C3S service via our Data Upload Server. All unique and relevant data acquired or submitted will be also archived at the NOAA National Centers for Environmental Information World Data Center for Meteorology, Asheville, North Carolina, USA and used in their data base curation efforts which are being jointly developed.

This paper outlines progress of the Copernicus Climate Change Service's (C3S) Global Land and Marine Observations Database service in securing data sources and introduces the data upload component. We present details of land and marine data holdings inventoried, highlighting priority needs in terms of periods, regions and Essential Climate Variables (ECVs) where additional data could bring most benefit. These holdings are being iteratively merged and integrated to best meet user needs and are served to the user via the Copernicus Climate Data Store (CDS). The secure Data Upload Server enables any data provider to share additional data and metadata with the service. We outline the process for registering as a data provider and how data sets are prioritized for integration. We encourage all data owners to share their data with the C3S service via our Data Upload Server. All unique and relevant data acquired or submitted will be also archived at the NOAA National Centers for Environmental Information World Data Center for Meteorology, Asheville, North Carolina, USA and used in their database curation efforts which are being jointly developed.

This analysis estimates uncertainty in the NOAA global surface temperature (GST) version 5 (NOAAGlobalTemp v5) product, which consists of sea surface temperature (SST) from the Extended Reconstructed SST version 5 (ERSSTv5) and land surface air temperature (LSAT) from the Global Historical Climatology Network monthly version 4 (GHCNm v4). Total uncertainty in SST and LSAT consists of parametric and reconstruction uncertainties. The parametric uncertainty represents the dependence of SST/LSAT reconstructions on selecting 28 (6) internal parameters of SST (LSAT), and is estimated by a 1000-member ensemble from 1854 to 2016. The reconstruction uncertainty represents the residual error of using a limited number of 140 (65) modes for SST (LSAT). Uncertainty is quantified at the global scale as well as the local grid scale. Uncertainties in SST and LSAT at the local grid scale are larger in the earlier period (1880s-1910s) and during the two world wars due to sparse observations, then decrease in the modern period (1950s-2010s) due to increased data coverage. Uncertainties in SST and LSAT at the global scale are much smaller than those at the local grid scale due to error cancellations by averaging. Uncertainties are smaller in SST than in LSAT due to smaller SST variabilities. Comparisons show that GST and its uncertainty in NOAAGlobalTemp v5 are comparable to those in other internationally recognized GST products. The differences between NOAAGlobalTemp v5 and other GST products are within their uncertainties at the 95% confidence level.

The NOAA/NESDIS/NCEI Daily Optimum Interpolation Sea Surface Temperature (SST), version 2.0, dataset (DOISST v2.0) is a blend of in situ ship and buoy SSTs with satellite SSTs derived from the Advanced Very High Resolution Radiometer (AVHRR). DOISST v2.0 exhibited a cold bias in the Indian, South Pacific, and South Atlantic Oceans that is due to a lack of ingested drifting-buoy SSTs in the system, which resulted from a gradual data format change from the traditional alphanumeric codes (TAC) to the binary universal form for the representation of meteorological data (BUFR). The cold bias against Argo was about −0.14°C on global average and −0.28°C in the Indian Ocean from January 2016 to August 2019. We explored the reasons for these cold biases through six progressive experiments. These experiments showed that the cold biases can be effectively reduced by adjusting ship SSTs with available buoy SSTs, using the latest available ICOADS R3.0.2 derived from merging BUFR and TAC, as well as by including Argo observations above 5-m depth. The impact of using the satellite MetOp-B instead of NOAA-19 was notable for high-latitude oceans but small on global average, since their biases are adjusted using in situ SSTs. In addition, the warm SSTs in the Arctic were improved by applying a freezing point instead of regressed ice-SST proxy. This paper describes an upgraded version, DOISST v2.1, which addresses biases in v2.0. Overall, by updating v2.0 to v2.1, the biases are reduced to −0.07° and −0.14°C in the global ocean and Indian Ocean, respectively, when compared with independent Argo observations and are reduced to −0.04° and −0.08°C in the global ocean and Indian Ocean, respectively, when compared with dependent Argo observations. The difference against the Group for High Resolution SST (GHRSST) Multiproduct Ensemble (GMPE) product is reduced from −0.09° to −0.01°C in the global oceans and from −0.20° to −0.04°C in the Indian Ocean.

The WMO-IOC Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) has devised a coordination mechanism for the fit-for-purpose delivery of an end-to-end system, from ocean observations to met-ocean operational services. This paper offers a complete overview of the activities carried out by JCOMM and the status of the achievements up to 2018. The JCOMM stakeholders consist of the research and operational institutions of WMO members and the IOC member states, which mandated JCOMM to devise an international strategy to move toward the achievement of the United Nations Sustainable Development Goals. The three areas of activity are the Observation Program Area (OPA), the Data Management Program Area (DMPA) and the Services and Forecasting Services Program Area (SFSPA), and several expert teams have been established to contribute to the international coordination efforts. OPA is organized into observing networks connected by different observing technologies, DMPA organizes the overall near-real time and delayed mode data assembly, and the delivery methodology and architecture, and the SFSPA coordinates the met-ocean services resulting from the observations and data management. Future developments should enhance coordination in these three program areas by considering the inclusion of new and emergent observing technologies, the interoperability of met-ocean data assembly centers and the establishment of efficient research to operations protocols, in addition to better fit-for-purpose customized services in both the public and private sectors.

The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a collection and archive of in situ marine observations, which has been developed over several decades as an international project and recently guided by formal international partnerships and the ICOADS Steering Committee. ICOADS contains observations from many different observing systems encompassing the evolution of measurement technology since the 18th century. ICOADS provides an integrated source of observations for a range of applications including research and climate monitoring, and forms the main marine in situ surface data source, e.g., near-surface ocean observations and lower atmospheric marine-meteorological observations from buoys, ships, coastal stations, and oceanographic sensors, for oceanic and atmospheric research and reanalysis. ICOADS has developed ways to incorporate user and reanalyses feedback information associated with permanent unique identifiers and is also the main repository for data that have been rescued from ships' logbooks and other marine data digitization activities. ICOADS has been adopted widely because it provides convenient access to a range of observation types, globally, and through the entire marine instrumental record. ICOADS has provided a secure home for such observations for decades. Because of the increased volume of observations, particularly those available in near-real-time, and an expansion of their diversity, the ICOADS processing system now requires extensive modernization. Based on user feedback, we will outline the improvements that are required, the challenges to their implementation, and the benefits of upgrading this important and diverse marine archive and distribution activity.

Historical reanalyses that span more than a century are needed for a wide range of studies, from understanding large‐scale climate trends to diagnosing the impacts of individual historical extreme weather events. The Twentieth Century Reanalysis (20CR) Project is an effort to fill this need. It is supported by the National Oceanic and Atmospheric Administration (NOAA), the Cooperative Institute for Research in Environmental Sciences (CIRES), and the U.S. Department of Energy (DOE), and is facilitated by collaboration with the international Atmospheric Circulation Reconstructions over the Earth initiative. 20CR is the first ensemble of sub‐daily global atmospheric conditions spanning over 100 years. This provides a best estimate of the weather at any given place and time as well as an estimate of its confidence and uncertainty. While extremely useful, version 2c of this dataset (20CRv2c) has several significant issues, including inaccurate estimates of confidence and a global sea level pressure bias in the mid‐19th century. These and other issues can reduce its effectiveness for studies at many spatial and temporal scales. Therefore, the 20CR system underwent a series of developments to generate a significant new version of the reanalysis. The version 3 system (NOAA‐CIRES‐DOE 20CRv3) uses upgraded data assimilation methods including an adaptive inflation algorithm; has a newer, higher‐resolution forecast model that specifies dry air mass; and assimilates a larger set of pressure observations. These changes have improved the ensemble‐based estimates of confidence, removed spin‐up effects in the precipitation fields, and diminished the sea‐level pressure bias. Other improvements include more accurate representations of storm intensity, smaller errors, and large‐scale reductions in model bias. The 20CRv3 system is comprehensively reviewed, focusing on the aspects that have ameliorated issues in 20CRv2c. Despite the many improvements, some challenges remain, including a systematic bias in tropical precipitation and time‐varying biases in southern high‐latitude pressure fields.

The role ships play in atmospheric, oceanic, and biogeochemical observations is described with a focus on measurements made within 100 m of the ocean surface. Ships include merchant and research vessels, cruise liners and ferries, fishing vessels, coast guard, military, and other government-operated ships, yachts, and a growing fleet of automated surface vessels. The present capabilities of ships to measure essential climate/ocean variables and the requirements from a broad community to address operational, commercial, and scientific needs are described. Following the guidance from the OceanObs’19 organizing committee, the authors provide a vision to expand observations needed from ships to understand and forecast the exchanges across the ocean-atmosphere interface. The vision addresses (1) recruiting vessels to improve both spatial and temporal sampling, (2) conducting multi-variate sampling on ships, (3) raising technology readiness levels of automated shipboard sensors and ship-to-shore data communications, (4) advancing quality evaluation of observations, and (5) developing a unified data management approach for observations and metadata that meets the needs of a diverse user community. Recommendations are made focusing on integrating private and autonomous vessels into the observing system, investing in sensor and communications technology development, developing an integrated data management structure that includes all types of ships, and moving towards a quality evaluation process that will result in a subset of ships being defined as mobile reference ships that will support climate studies. We envision a future where commercial, research, and privately-owned vessels are making multivariate observations using a combination of automated and human-observed measurements. All data and metadata will be documented, tracked, evaluated, distributed, and archived to benefit users of marine data. This vision looks at ships as a holistic network, not a set of disparate commercial, research, and/or third-party activities working in isolation, to bring these communities together for the mutual benefit of all.

The difficulty in effectively evaluating sea surface temperature (SST) analyses is finding independent observations, since most available observations have been used in the SST analyses. In this study, the ocean profile measurements [from reverse thermometer, CTD, mechanical bathythermograph (MBT), and XBT] above 5-m depth over 1950–2016 from the World Ocean Database (WOD) are used (data labeled pSSTW). The biases of MBT and XBT are corrected based on currently available algorithms. The bias-corrected pSSTW over 1950–2016 and satellite-based SST from the European Space Agency (ESA) Climate Change Initiative (CCI) over 1992–2010 are used to evaluate commonly available SST analyses. These SST analyses are the Extended Reconstructed SST (ERSST), versions 5, 4, and 3b, the Met Office Hadley Centre Sea Ice and SST dataset (HadISST), and the Japan Meteorological Administration (JMA) Centennial In Situ Observation-Based Estimates of SST version 2.9.2 (COBE-SST2). Our comparisons show that the SST from COBE-SST2 is the closest to pSSTW and CCI in most of the Pacific, Atlantic, and Southern Oceans, which may result from its unique bias correction to ship observations. The SST from ERSST version 5 is more consistent with pSSTW than its previous versions over 1950–2016, and is more consistent with CCI than its previous versions over 1992–2010. The better performance of ERSST version 5 over its previous versions is attributed to its improved bias correction applied to ship observations with a baseline of buoy observations, and is seen in most of the Pacific and Atlantic.

ABSTRACTWe highlight improvements to the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS) in the latest Release 3.0 (R3.0; covering 1662–2014). ICOADS is the most widely used freely available collection of surface marine observations, providing data for the construction of gridded analyses of sea surface temperature, estimates of air–sea interaction and other meteorological variables. ICOADS observations are assimilated into all major atmospheric, oceanic and coupled reanalyses, further widening its impact. R3.0 therefore includes changes designed to enable effective exchange of information describing data quality between ICOADS, reanalysis centres, data set developers, scientists and the public. These user‐driven innovations include the assignment of a unique identifier (UID) to each marine report – to enable tracing of observations, linking with reports and improved data sharing. Other revisions and extensions of the ICOADS' International Maritime Meteorological Archive common data format incorporate new near‐surface oceanographic data elements and cloud parameters. Many new input data sources have been assembled, and updates and improvements to existing data sources, or removal of erroneous data, made. Coupled with enhanced ‘preliminary’ monthly data and product extensions past 2014, R3.0 provides improved support of climate assessment and monitoring, reanalyses and near‐real‐time applications.

This special section accumulates articles from the Fourth JCOMM Workshop on Advances in Marine Climatology (CLIMAR-IV) held in Asheville, NC, USA from 9 to 12 June 2014. Since the first workshop in Vancouver in 1999, CLIMAR Workshops track the progress in marine climatology comprehensively covering scientific, methodological and data management issues of marine climatology (see e.g. Gulev, 2005; Gulev and Woodruff, 2011). Marine climatological data play a crucial role in assessing past and ongoing climate variability and change. Without long-term global and regional time series of marine climatological data, we cannot track global climate and quantify the ocean's role in climate variability and change. Besides estimation of variability of surface state variables, marine climatological data allow for computation of surface air–sea fluxes – the language of ocean and atmosphere communication. Also marine climatological archives provide invaluable contribution to the data assimilated by modern reanalyses, some of which are going back now to the 19th century, documenting the dynamically consistent history of the climate system. Marine climatological records (e.g. information about winds and waves) are also widely used for estimation of extreme events over the ocean, including storminess, storm surges and extreme sea level rise. These phenomena are of great importance for all types of marine structures, including operations of marine carriers and offshore engineering. Finally, marine climatological data provide an important source of in situ information for validation of satellite measurements of surface meteorological variables. However to be useful for all mentioned purposes, marine climatological data need to be accurately assembled, quality controlled and supplied with estimates of all types of uncertainties. These include measurement errors associated with the accuracy of instruments and with historical changes in observational practices which may affect not only climatological means but also estimates of climate variability. In addition to measurement errors, marine climatological data are subject to sampling uncertainties, originating from space and time inhomogeneities of sampling density, collected by merchant ships primarily along the major shipping routes. Unless these uncertainties are properly estimated, marine climatological data sets are more difficult to be effectively used for any purpose. For many years, starting from the late 1980s marine climatological data are assimilated in the International Comprehensive Ocean–atmosphere Data Set (ICOADS), representing now a unique freely available digital archive covering the period from the 17th century onwards including individual ship reports and Monthly Summary Group (MSG) statistical products. ICOADS has played a central role in all CLIMAR Workshops, and also with the alternate but associated Workshops on the Advances in the Use of Historical MARine Climate DATa (MARCDAT) focused on more technical issues of the analysis of marine data. Thus, it is very natural that CLIMAR-IV was organized in conjunction with the First ICOADS Value-Added Database (IVAD-I) Workshop held on 13 June 2014 at the same location. During CLIMAR-IV about 50 participants from around the world presented more than 50 oral talks and 10 posters organized in 8 sessions focused on all aspects of the use of marine climatological data from pre-processing and quality control to estimation of surface fluxes and assessment of climate variability and change. General and plenary discussions resulted in recommendations focused on best practices for estimation of uncertainties, developing metadata, cross-validation of marine climatological information and applications for different areas of climate and ocean science. Articles in this Special Section cover recent developments of ICOADS and guidance on the latest ICOADS Release 3.0 – the most recent and complete data set of marine climatological data (Freeman et al., 2017), problems of analysing spatially inhomogeneous data collected along the merchant ship routes (Berry and Kent, 2017; Carella et al., 2017) and impact of marine meteorological data on the estimates of variability in ocean heat content (Good, 2017). We note that many more results from the Workshop were and will be published in regular issues of International Journal of Climatology and the other relevant journals. We would like to take this opportunity to thank the World Meteorological Organization (WMO), Intergovernmental Oceanographic Committee (IOC) of UNESCO and the UK National Oceanography Centre in Southampton for supporting CLIMAR-IV Workshop. Our special thanks go to the NOAA Climate Program Office for their long-term support of ICOADS. We thank the Royal Meteorological Society and our publisher Wiley and Sons for nearly two decades of support for publications on marine climatology.

AbstractThe monthly Extended Reconstructed Sea Surface Temperature (ERSST) dataset, available on global 2° × 2° grids, has been revised herein to version 4 (v4) from v3b. Major revisions include updated and substantially more complete input data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) release 2.5; revised empirical orthogonal teleconnections (EOTs) and EOT acceptance criterion; updated sea surface temperature (SST) quality control procedures; revised SST anomaly (SSTA) evaluation methods; updated bias adjustments of ship SSTs using the Hadley Centre Nighttime Marine Air Temperature dataset version 2 (HadNMAT2); and buoy SST bias adjustment not previously made in v3b.Tests show that the impacts of the revisions to ship SST bias adjustment in ERSST.v4 are dominant among all revisions and updates. The effect is to make SST 0.1°–0.2°C cooler north of 30°S but 0.1°–0.2°C warmer south of 30°S in ERSST.v4 than in ERSST.v3b before 1940. In comparison with the Met Office SST product...

Described herein is the parametric and structural uncertainty quantification for the monthly Extended Reconstructed Sea Surface Temperature (ERSST) version 4 (v4). A Monte Carlo ensemble approach was adopted to characterize parametric uncertainty, because initial experiments indicate the existence of significant nonlinear interactions. Globally, the resulting ensemble exhibits a wider uncertainty range before 1900, as well as an uncertainty maximum around World War II. Changes at smaller spatial scales in many regions, or for important features such as Nino-3.4 variability, are found to be dominated by particular parameter choices.Substantial differences in parametric uncertainty estimates are found between ERSST.v4 and the independently derived Hadley Centre SST version 3 (HadSST3) product. The largest uncertainties are over the mid and high latitudes in ERSST.v4 but in the tropics in HadSST3. Overall, in comparison with HadSST3, ERSST.v4 has larger parametric uncertainties at smaller spatial and shorter time scales and smaller parametric uncertainties at longer time scales, which likely reflects the different sources of uncertainty quantified in the respective parametric analyses. ERSST.v4 exhibits a stronger globally averaged warming trend than HadSST3 during the period of 1910-2012, but with a smaller parametric uncertainty. These global-mean trend estimates and their uncertainties marginally overlap.Several additional SST datasets are used to infer the structural uncertainty inherent in SST estimates. For the global mean, the structural uncertainty, estimated as the spread between available SST products, is more often than not larger than the parametric uncertainty in ERSST.v4. Neither parametric nor structural uncertainties call into question that on the global-mean level and centennial time scale, SSTs have warmed notably.

Release 2.5 of the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS) is a major update (covering 1662–2007) of the world's most extensive surface marine meteorological data collection. Building on extensive national and international partnerships, many new and improved contributing datasets have been processed into a uniform format and combined with the previous Release 2.4. The new data range from early non‐instrumental ship observations to measurements initiated in the twentieth century from buoys and other automated platform types. Improvements to existing data include replacing preliminary Global Telecommunication System (GTS) receipts with more reliable, delayed mode reports for post‐1997 data, and in the processing and quality control (QC) of humidity observations. Over the entire period of record, spatial and temporal coverage has been enriched and data and metadata quality has been improved. Along with the observations, now updated monthly in near real time, Release 2.5 includes quality‐controlled monthly summary products for 2° latitude × 2° longitude (since 1800) and 1° × 1° boxes (since 1960), together with multiple options for access to the data and products. The measured and estimated data in Release 2.5 are subject to many technical changes, multiple archive sources, and historical events throughout the more than three‐century record. Some of these data characteristics are highlighted, including known unresolved errors and inhomogeneities, which may impact climate and other research applications. Anticipated future directions for ICOADS aim to continue adding scientific value to the observations, products, and metadata, as well as strengthen the cooperative enterprise through expanded linkages to international initiatives and organisations. Copyright © 2010 Royal Meteorological Society

The RECovery of Logbooks and International Marine data (RECLAIM) project is a concerted, international effort to facilitate and encourage the recovery—through imaging and digitisation—of archived marine weather observations, platform and instrumental metadata and historical documentation, from many different countries. Non‐instrumental observations of wind and weather have been recorded in ships' logbooks for hundreds of years, augmented by systematic instrumental observations of sea surface and air temperatures, barometric pressure and other meteorological (and oceanographic) elements largely since the mid‐nineteenth century. Once digitised, these data are widely useful for climate studies and other avenues of scientific research—including oceanography, fisheries, maritime history and ecology—thus improvements seeking to address gaps and weaknesses in the currently available data record can be of major importance. In addition to documenting and prioritising archived ship logbook records for imaging and digitisation in support of that goal, RECLAIM provides expert assistance in the interpretation of historical marine records in relation to navigation, observational practices and recording. Since the project inception in 2005, RECLAIM has facilitated, for example, recovery of logbooks of the Dutch and English East India Companies in the nineteenth century, and of the British Royal Navy of the twentieth century. Currently the project website includes reference lists, rescued UK and US marine documents, extensive UK archive reports and detailed inventories of ship movements. A variety of other developing international linkages are discussed, including to Chilean, Dutch, French, German, Finnish, Norwegian, Swedish and US historical records. © Royal Meteorological Society and Crown Copyright 2010.

Weather observations are vital for climate change monitoring and prediction. For the world's oceans, there are many meteorological and oceanographic observations available back to the mid-twentieth century, but coverage is limited in earlier periods, and particularly also during the two world wars. Before 1850 there are currently very few instrumental observations available. Consequently, detailed observational estimates of surface climate change can be made only back to the mid-nineteenth century. To improve and extend this early coverage, scientists need more observations from these periods. Fortunately, many such observations exist in logbooks, reports, and other paper records, but their inclusion in the climatic datasets requires that these paper records be abstracted from the world's archives, digitized into an electronic form, and blended into existing climate databases.As a first step in this direction, selected Royal Navy logbooks from the period of 1938-47, kept in the U.K. National Archives, have been photographed and digitized. These have provided more than 1,500,000 new observations for this period, and a preliminary analysis has shown significant improvements to the record of climate change in the mid-twentieth century.