Annual Update Research Articles

Differing needs for Advance Care Planning in the Veterans Health Administration: use of latent class analysis to identify subgroups to enhance Advance Care Planning via Group Visits for veterans

BackgroundAdvance Care Planning via Group Visits (ACP-GV) is a patient-centered intervention facilitated by a clinician using a group modality to promote healthcare decision-making among veterans. Participants in the group document a “Next Step” to use in planning for their future care needs. The next step may include documentation of preferences in an advance directive, discussing plans with family, or anything else to fulfill their ACP needs. This evaluation seeks to determine whether there are identifiable subgroups of group participants with differing needs prior to delivery of the ACP-GV program and, if so, to use information about the subgroups to enhance the program offered to veterans in United States Department of Veterans Affairs (VA) healthcare settings.MethodsWe conducted a secondary analysis of national data from a quality improvement evaluation. Patient- and provider-level data from administrative healthcare records for VA users in all 50 states, territories, and the District of Columbia provides data on veterans attending ACP-GV during federal fiscal years 2018–2022 (N = 26,857). Latent class analysis seeks to identify the various subgroups of veterans based on their level of ACP self-efficacy before attending ACP-GV and any demographic differences across the resulting subgroups of veterans attending ACP-GV. ACP self-efficacy is derived from seven items obtained from a participant worksheet used during the group.ResultsAnalysis revealed two distinct groups of veterans, distinguishable by their pre-ACP-GV levels of one aspect of ACP self-efficacy: prior knowledge of ACP. Veterans with higher prior knowledge of ACP are associated with an identified next step focused on checking their current AD status and updating it, and veterans with lower ACP prior knowledge are associated with identifying a next step to discuss ACP more fully with family. Differences in age, sex, race, ethnicity, and marital status exist across subgroups of veterans.ConclusionGreater attention must be paid to ACP and veterans’ prior knowledge of ACP to consistently encourage annual review and status updates.

The Decline of Medicare Reimbursement in Anatomic Pathology

Abstract Introduction/Objective Lack of an annual inflationary update for physician reimbursement from the Centers for Medicare & Medicaid Services (CMS) jeopardizes access to anatomic pathology services at healthcare institutions nationwide. The effects of recent inflationary trends on anatomic pathology physician reimbursement are unknown. Thus, our study sought to analyze trends in Medicare reimbursement rates from 2004 to 2024 for anatomic pathology procedures. Methods/Case Report The Physician Fee Schedule Look-Up Tool from the CMS was queried for the top 30 CPT codes utilized, and physician reimbursement data extracted. Monetary data was subsequently adjusted for inflation utilizing the Consumer Price Index and reported in 2024 US dollars. The average annual and total percent change in reimbursement were calculated for included procedures. The compound annual growth rate (CAGR) was calculated using 2024 and 2000 inflation-adjusted monetary data. Results (if a Case Study enter NA) Prior to adjusting for inflation, the average physician reimbursement increased by 9.7% from 2004 to 2024 for all included anatomic pathology CPT codes. After adjusting for inflation, the average physician reimbursement decreased by 34.2% for included CPT codes. The greatest decrease in reimbursement observed from 2004 to 2024 was for outside slide consultation at 60.5% ($330.12 to $130.49), followed by pathology consultation during surgery at 59.0% ($83.54 to $34.29). The average CAGR was -2.19%. Conclusion Our study demonstrates that Medicare physician reimbursement for common anatomic pathology procedures is declining annually at an unsustainable rate. This downward trend necessitates policy action to prevent access barriers to quality anatomic pathology care nationwide, especially for Medicare beneficiaries.

The Decline of Medicare Reimbursement in Clinical Pathology

Abstract Introduction/Objective Access to clinical pathology services nationwide is threatened by the lack of an annual inflationary update for physician reimbursement from the Centers for Medicare & Medicaid Services (CMS). Most recently, the 2024 Medicare Physician Fee Schedule (MPFS) implemented an overall 2.0% reduction in pathology reimbursement. The effects of recent inflationary trends on clinical pathology physician reimbursement are unknown. Thus, our study sought to analyze trends in Medicare reimbursement rates from 2004 to 2024 for clinical pathology procedures. Methods/Case Report The Physician Fee Schedule Look-Up Tool from the CMS was queried for the top 30 CPT codes utilized, and physician reimbursement data extracted. Monetary data was subsequently adjusted for inflation utilizing the Consumer Price Index and reported in 2024 US dollars. The average annual and total percent change in reimbursement were calculated for included procedures. A subset analysis was conducted to assess physician pathology clinical consultation services average annual and total percent change in reimbursement pre- and post- 2022 MPFS Update. The compound annual growth rate (CAGR) was calculated using 2024 and 2000 inflation- adjusted monetary data. Results (if a Case Study enter NA) Prior to adjusting for inflation, the average physician reimbursement decreased by 6.8% from 2004 to 2024 for included clinical pathology CPT codes. After adjusting for inflation, the average physician reimbursement decreased by 44.0% for included CPT codes. The greatest decrease in reimbursement observed from 2004 to 2024 was for flow cytometry interpretation, 2-8 minutes at 69.5% ($114.44 to $34.95) followed by flow cytometry interpretation, 9-15 minutes at 57.8% ($142.77 to $60.25) and flow cytometry interpretation, >16 minutes at 56.6% ($188.05 to $81.55). The average CAGR was -2.86%. Prior to adjusting for inflation, the average physician reimbursement for clinical pathology consultation services pre-2022 decreased by 0.9%, and when adjusted for inflation, decreased by 30.0%. Post-2022 MPFS revision, the average physician reimbursement for clinical pathology consultation services decreased by 3.5%, and when adjusted for inflation, decreased by 12.2%. The average CAGR pre-2022 was -2.0% and post-2022 was -4.3%. Conclusion Medicare physician reimbursement for common clinical pathology procedures is decreasing at an untenable rate annually. It is critical that policymakers understand these trends to ensure continued access to quality clinical pathology care at healthcare institutions.

Hydrological Data Projection Using Empirical Mode Decomposition: Applications in a Changing Climate

This paper demonstrates the effectiveness and superiority of Empirical Mode Decomposition (EMD) in projecting non-stationary hydrological data. The study focuses on daily Sea Surface Temperature (SST) sequences in the Niño 3.4 region and uses EMD to forecast the probability of El Niño events. Applying the Mann–Kendall test at the 5% significance level reveals a significant increasing trend in SST changes in this region, particularly noticeable after 1980. This trend is associated with the occurrence of El Niño and La Niña events, which have a recurrence interval of approximately 8.4 years and persist for over a year. The modified Oceanic Niño Index (ONI) proposed in this study demonstrates high forecast accuracy, with 97.56% accuracy for El Niño and 89.80% for La Niña events. Additionally, the EMD of SST data results in 13 Intrinsic Mode Functions (IMFs) and a residual component. The oscillation period increases with each IMF level, with IMF7 exhibiting the largest amplitude, fluctuating between ±1 °C. The residual component shows a significant upward trend, with an average annual increase of 0.0107 °C. These findings reveal that the EMD-based data generation method overcomes the limitations of traditional hydrological models in managing non-stationary sequences, representing a notable advancement in data-driven hydrological time series modeling. Practically, the EMD-based 5-year moving process can generate daily sea temperature sequences for the coming year in this region, offering valuable insights for assessing El Niño probabilities and facilitating annual updates.

Power system planning in the energy transition era: the case of Vietnam's power development plan 8

ABSTRACT This review examines Vietnam's eighth Power Development Plan (PDP8), analyzing how it reveals tensions between traditional energy planning concepts and emerging realities. PDP8 aimed to balance renewable energy and natural gas priorities amidst Vietnam's rapidly changing energy landscape. The planning process struggled to incorporate uncertainties like technology cost declines and global energy crises. Although following a conventional optimization approach, PDP8 underwent repeated delays and pivots, pointing to misalignment between rational planning ideals and implementation constraints. The case study highlights the limitations of ‘plan to build’ methods focused on rigid engineering blueprints. Instead, Vietnam's energy transition requires strategic approaches that embrace flexibility and scenario analysis. Based on years of participative observation, two interview surveys, and extensive corpus analysis, the review traces PDP8's evolution towards more open-ended strategies. While still detailing infrastructure projects, PDP8 defines adaptive implementation mechanisms and conditional goals dependent on external finance. This shift from project lists to navigational thinking illustrates the need for energy planning to incorporate uncertainty and maintain the capacity to adjust. PDP8 represents a transitional compromise between traditional ten-year planning and emerging ‘plan to drive’ concepts focused on navigating change with annual updates to the Plan.

Establishment of an Australian National Master Linkage Key (NMLK) between AIHW Health Linkage spine (HLS) and Jurisdictional Master Linkage Keys (MLK) - NSW example

ObjectivesThis paper describes a Population Health Research Network project establishing the NMLK as a national linkage system utilising an enduring linkage between national and jurisdictional linkage spines. It used keys from existing enduring linkages within each participating jurisdictional Data Linkage Unit (DLU). The process is demonstrated with reference to an enduring map between AIHW Health Linkage Spine (HLS) and Centre for Health Record Linkage (CHeReL) MLK. ApproachThe NMLK has jurisdictional sections. The NSW section was established in four steps. CHeReL provided data from its regularly updated MLK for the NMLK project authorised by existing project ethics approval. AIHW linked NSW MLK subset to HLS and the de-identified linkage map and report were sent to CHeReL for review. CHeReL reviewed the results, particularly the additional duplicates identified through the linkage process. The agreed links form the AIHW-NSW section of NMLK quarantined for a year. The annual update, scheduled for later in 2024, will focus only on linking the new and unlinked individuals in both datasets. ResultsThe NSW cohort was supplied with almost 50 million records, comprising over 14 million unique person ids. Of these, 12 million were matched with reasonable confidence to HLS, or 84.4% of the total (or around 97% if we exclude NSW records with missing personal information and around 140,000 individuals out of scope of HLS.) Conclusion Establishment of the NMLK enabled effective production of high-quality enduring linkage maps used across multiple cross-jurisdictional projects while minimising the privacy risks.

Annual Update on SDR Trading Operations

Annual Update on SDR Trading Operations

Accuracy of self-reported treated hypertension in the women's health initiative: Comparisons with medication inventories.

Few studies have reported on the accuracy of self-reported hypertension history among older postmenopausal women, which was this study's objective. Participants were postmenopausal women enrolled in the Osteoporosis and Periodontal Disease (OsteoPerio) study, an ancillary investigation of the Women's Health Initiative Observational Study (WHI-OS) at the Buffalo, New York, clinical site. Participants self-reported their history of physician diagnosed hypertension treated with medication at WHI-OS enrollment (1993-1998; n=1342, mean age 63 years), then 3 years later at OsteoPerio enrollment (1997-2001; n=1342), and again at OsteoPerio Year 5 follow-up (2002-2005; n=1020). At each time point, medication inventories were recorded and served as the criterion with which self-report was compared in the present study. Physician diagnosed-treated hypertension was also self-reported annually on mailed health update questionnaires in the WHI-OS and were compared against medication inventory at the subsequent clinic exam. Of those participants who self-reported a history of hypertension at WHI enrollment, OsteoPerio enrollment, and OsteoPerio Year 5 follow-up, 41.2%, 90.3%, and 94.4%, respectively, had anti-hypertensive pills in their medication inventory. Across the three time points, sensitivity and specificity ranged from 0.72 to 0.98 and from 0.85 to 0.95, and kappa coefficients ranged from 0.52 to 0.79 when comparing self-report with medication inventory. For self-reported newly physician-diagnosed and treated hypertension on the annual health update questionnaire, 88.4% and 95.2% of those reporting hypertension had anti-hypertensive pills in the subsequent medication inventory. In general, sensitivity and kappa were lower in women aged ≥70 versus<70 years and in those with history of cardiovascular disease and diabetes compared to those without these comorbidities. In this cohort of postmenopausal women, self-reported physician diagnosed and treated hypertension demonstrated moderate to high accuracy when compared against anti-hypertensive medication use documented by pill inventory, particularly for those who were younger and managing fewer comorbidities.

Normalized Difference Red-NIR-SWIR: A new Sentinel-2 three-band spectral index for mapping freshly-opened swiddens in the tropics

Swidden agriculture is undergoing a rapid but overlooked transition and transformation in the tropics, complicating global carbon budgeting and sustainable livelihood assessment of swiddeners. Remotely sensed algorithms for accurately detecting swiddening practices have been slowly developed to generate annual updates on their dynamics. This is primarily because, using medium spatial resolution imagery (≥30 m), it is challenging to identify the exact boundary of swidden patches. Spectral-based approaches have by far dominated the detection and mapping of swidden agriculture, but the potential of Sentinel-2 has not been examined. To reconstruct annual information of swidden agriculture, a new Sentinel-2 three-band spectral index, i.e., the Normalized Difference Red, Near-infrared (NIR), and Shortwave-infrared (SWIR), or NDRII, has been developed to map freshly-opened swiddens in tropical regions. As Red (visible), NIR, and SWIR spectral band combinations (i.e., the VNIR-SWIR spectroscopy) are sensitive to vegetation-moisture variations and thermal anomalies caused by slash and burn in tropical uplands during the dry season, NDRII delineates exact patches of freshly opened swiddens. The latest 20-m map facilitates probing into the landscape patterns of newly opened swiddens and underlines their prevalence in Laos for the first time. Established within the VNIR-SWIR spectroscopy of Sentinel-2 and Landsat-8 Operational Land Imager, the NDRII algorithm contributes to reconstructing historical datasets of tropical swiddens via integrating state-of-the-art approaches that use temporally stacked observations with available VNIR/SWIR satellite imagery and further understanding the dynamics of landscape pattern and disturbance due to rapid transition and transformation.

OnetoMap Meta-Data: Healthcare Analytics Through Research.

Big Data has revolutionized healthcare research through the three Vs: volume, veracity, and variety. This study introduces the OnetoMap meta-data repository, a centralized inventory developed in collaboration with the University of South Florida's Department of Surgery. The repository offers extensive details about each database, including its primary purpose, available variables, and examples of high-impact research utilizing these databases. It aims to create a centralized inventory, enabling researchers to locate and link relevant datasets efficiently. Each dataset is described using standardized criteria to ensure clarity and usability, such as data type, source, collection methods, and potential linkages to other datasets. Results: Currently, the OnetoMap repository contains descriptions of 49 datasets, with ongoing updates to include new datasets and additional data years. These datasets include a range of data types, including cross-sectional and longitudinal, gathered through claims, registries, electronic health records, and surveys. The repository is hosted on GitHub, enabling version control, collaboration, and open access. Effective search functionalities and descriptive categorization enhance the findability of datasets. The data repository includes comprehensive records of patient health statuses, socioeconomic profiles, hospital structures, and physician practices, enabling nuanced interventions and addressing complex healthcare needs. It also promotes interdisciplinary research and accelerates novel discoveries by providing a centralized source of diverse data and facilitating collaboration among research teams. The OnetoMap meta-data repository represents a significant advancement in healthcare research by providing a centralized, detailed, and easily accessible repository of clinical research databases. Future directions include implementing automatic annual updates of datasets, exploring automatic dataset linkage, providing monthly updates on published research, creating a user chat space for enhanced collaboration, and developing code applets for simplified data analysis. These efforts will ensure that the repository remains current, functional, and accessible, ultimately facilitating new discoveries and insights in healthcare outcomes research.

Tourette syndrome research highlights from 2023.

In this, the tenth annual update for the F1000Research Tics collection, we summarize research reports from 2023 on Gilles de la Tourette syndrome and other tic disorders. The authors welcome article suggestions and thoughtful feedback from readers.

History of the Surveillance, Epidemiology, and End Results (SEER) Program.

The Surveillance, Epidemiology, and End Results (SEER) Program established in 1973 was the first laboratory for experimenting with new methods for cancer data collection and translating the data into population-based cancer statistics. The SEER Program staff have been instrumental in the development of the International Classification of Disease-Oncology and successfully implemented the routine collection of anatomic and prognostic cancer stage at diagnosis. Currently the program consists of 21 central registries that generate cancer statistics covering more than 48% of the US population and an additional 10 research support registries contributing to certain research projects, such as the National Childhood Cancer Registry. In parallel with the geographical expansion, the program built an architecture of methods and tools for population-based cancer statistics, with SEER*Explorer as the most recent online tool for descriptive statistics. In addition, SEER releases annual updates for a comprehensive data product line, which includes SEER*Stat databases with an annual caseload of more than 800 000 incident cases. Furthermore, the program developed a full suite of analytical applications for population-based cancer statistics that include Joinpoint (regression-based trend analysis), DevCan (risk of diagnosis and death), CanSurv (survival models), and ComPrev and PrejPrev (cancer prevalence), among others. The future of the SEER Program is closely aligned to the overall goals of the "war on cancer." The program aims to release longitudinal treatment data coupled with a comprehensive genomic characterization of cancers with a declared goal of decreasing the cancer burden and disparities across a wide spectrum of diseases and communities.

German Heart Surgery Report 2023: The Annual Updated Registry of the German Society for Thoracic and Cardiovascular Surgery.

Based on a voluntary registry, founded by the German Society for Thoracic and Cardiovascular Surgery (DGTHG) in 1980, a well-defined but limited dataset of all cardiac and vascular surgery procedures performed in 77 German heart surgery departments is reported annually. For the year 2023, a total of 168,841 procedures were submitted to the registry. Of these operations, 100,606 are defined as heart surgery procedures in a classical sense. The unadjusted in-hospital survival rate for the 28,996 isolated coronary artery bypass grafting procedures (relationship on-/off-pump 2.8:1) was 97.6%; 97.7% for the 39,859 isolated heart valve procedures (23,727 transcatheter interventions included); and 99.2% for 19,699 pacemaker/implantable cardioverter defibrillator procedures. Concerning short and long-term mechanical circulatory support, a total of 2,982 extracorporeal life support/extracorporeal membrane oxygenation implantations and 772 ventricular assist device implantations (left/right ventricular assist device, BVAD, total artificial heart) were reported. In 2023, 324 isolated heart transplantations, 248 isolated lung transplantations, and 2 combined heart-lung transplantations were performed. This annually updated registry of the DGTHG represents nonrisk adjusted voluntary public reporting and encompasses acute data for nearly all heart surgical procedures in Germany. It constitutes trends in heart medicine and represents a basis for quality management (e.g., benchmark) for all participating institutions.

The Cancer Clinical Library Database (CCLD) from the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) Project.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea's cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Tourette syndrome research highlights from 2023

In this, the tenth annual update for the F1000Research Tics collection, we summarize research reports from 2023 on Gilles de la Tourette syndrome and other tic disorders. The authors welcome article suggestions and thoughtful feedback from readers.

Designing Effective Scripts and Resources to Support Simulated Practice, Using Basic Life Support as an Exemplar

This is the third instalment in a series of papers featured in this journal, focusing on the application of mental simulation in nursing. This specific article addresses the pervasive issue of skill decay in Basic Life Support (BLS) training, proposing an innovative solution through the integration of mental simulation. Despite mandatory annual BLS updates for nurses, evidence suggests a decline in skills over time, posing risks to patient safety. Traditional methods, reliant on face-to-face sessions, may not sufficiently prevent skill decay, particularly in time-sensitive scenarios. The article advocates for mental simulation as a complementary and accessible approach to augment traditional BLS training. Focused on the vivid mental rehearsal of actions, mental simulation offers a promising avenue for nurses, seeking to reinforce correct techniques and deepen their understanding of BLS interventions. Guided by the physical, environment, task, timing, learning, emotion, perspective (PETTLEP) framework, the discussion navigates through the practical application of mental simulation. The framework serves as a model for crafting scenario scripts, emphasising each of the PETTLEP elements. Recommendations include the incorporation of progressive scripts aligned with learners’ evolving knowledge, providing a nuanced approach to skill enhancement. Authenticity is emphasised through the integration of real experiences into scripts, adopting a first-person perspective, and incorporating sound effects. While acknowledging challenges such as empirical testing and individual differences, the paper concludes by highlighting the potential of mental simulation to bridge gaps in nursing education. In offering a practical and immersive learning experience, mental simulation emerges as a valuable tool for nurses aiming to optimise their BLS proficiency, ultimately contributing to enhanced patient safety.

The Impact of Weight Shifts on Inflation: Evidence for the Euro Area HICP

Shifts in household consumption feed into euro area inflation via the annual updating of product weights. The partial effect of weight changes on inflation is not quantified by statistical offices. We therefore propose a decomposition of the inflation rate, measured by the annual percentage change of the Harmonised Index of Consumer Prices (HICP), into the overall price change assuming weights at the previous year’s level and a weighting effect. We discuss this decomposition against a decomposition into pure price change and quantity effects. Our empirical results show that euro area inflation has been noticeably impacted by weighting effects since 2021. Before 2022, we observe a close relationship between weighting and quantity effects. As weighting effects can be calculated without delay from publicly available HICP data, we argue that this decomposition is relevant in terms of providing timely information for analysts and monetary policymakers.

Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence

Abstract. Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.11388387, Smith et al., 2024a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO2e yr−1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

Annual winter crop distribution from MODIS NDVI timeseries to improve yield forecasts for Europe

Crop yield forecasts allow policy makers to anticipate market behaviour and regulate prices. Annual updates on which crops are grown where can improve crop yield forecast accuracy. Existing efforts to map crops across the European Union resulted in late-season map availability or short time series that do not meet forecasting requirements. We propose a new approach to retrieve annual winter crop maps and improve forecasting efforts by identifying pixels with dominant winter crop signals using moderate resolution imagery. These pixels are distinguished from summer crop signals based on their senescence date. When this date precedes the theoretical maturity date of a winter crop, expressed in GDD, the pixel is labelled as having a dominant winter crop signal. Our 2018 map accurately identified 77% and 83% of dominantly winter-crop area, when compared to farmers’ declaration data and a high-resolution crop map for Europe, respectively. While the resulting annual winter crop maps underestimated winter crop area, derived region-specific annual NDVI profiles better described winter crop phenology as compared to the use of static maps. Regression analysis between these regional NDVI profiles and statistical wheat yield data indicates that our annual maps help explain more yield variability than static maps, with an RMSE reduction of 3% for the EU27 as whole. The proposed approach is applicable to long historical timeseries and provides maps before the end of the agricultural season. Those maps positively impact crop yield description, notably in eastern, northern, and northeastern European regions.

The annual update GLODAPv2.2023: the global interior ocean biogeochemical data product

Abstract. The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major changes are as follows: data from 23 new cruises were added. In addition, a number of changes were made to the data included in GLODAPv2.2022. GLODAPv2.2023 includes measurements from more than 1.4 million water samples from the global oceans collected on 1108 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on the systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 23 new cruises were derived by comparing those data with the data from the 1085 quality-controlled cruises in the GLODAPv2.2022 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2), chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data-handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA National Centers for Environmental Information (NCEI), which also provides access to the merged data product. This is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/zyrq-ht66 (Lauvset et al., 2023). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2023 methods and provides a broad overview of the secondary quality control procedures and results.