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WMo is beta Np-derived structured and crystallizes in the orthorhombic Cmmm space group. The structure is two-dimensional and consists of two WMo sheets oriented in the (0, 1, 0) direction. W is bonded in a 8-coordinate geometry to four equivalent Mo atoms. All W–Mo bond lengths are 2.75 Å. Mo is bonded in a 8-coordinate geometry to four equivalent W atoms.
Explaining the observed ozone trends discussed in an earlier update and predicting future trends requires an understanding of the stratospheric processes that affect ozone. Stratospheric processes occur on both large and small spatial scales and over both long and short periods of time. Because these diverse processes interact with each other, only in rare cases can individual processes be studied by direct observation. Generally the cause and effect relationships for ozone changes were established by comparisons between observations and model simulations. Increasingly, these comparisons rely on the developing, observed relationships among trace gases and dynamical quantities to initialize and constrain the simulations. The goal of this discussion of stratospheric processes is to describe the causes for the observed ozone trends as they are currently understood. At present, we understand with considerable confidence the stratospheric processes responsible for the Antarctic ozone hole but are only beginning to understand the causes of the ozone trends at middle latitudes. Even though the causes of the ozone trends at middle latitudes were not clearly determined, it is likely that they, just as those over Antarctica, involved chlorine and bromine chemistry that was enhanced by heterogeneous processes. This discussion generally presents only an update of the observations that have occurred for stratospheric processes since the last assessment (World Meteorological Organization (WMO), 1990), and is not a complete review of all the new information about stratospheric processes. It begins with an update of the previous assessment of polar stratospheres (WMO, 1990), followed by a discussion on the possible causes for the ozone trends at middle latitudes and on the effects of bromine and of volcanoes.
An international comparison of Dobson ozone spectrophotometers, organized and partially funded by the World Meteorological Organization (WMO), was held at the Lichtklimatisches Observatorium (LKO) in Arosa, Switzerland, July-August 1990. Countries participating with a total of 18 Dobson instruments were Belgium, Czechoslovakia, Denmark, Germany, Greece, Hungary, Iceland, Norway, Poland, Portugal, Rumania, Spain, Switzerland, the United Kingdom, the United States, and the United Soviet Socialist Republics. The reference standard instrument for the comparison was U.S.A. Secondary Standard Dobson Spectrophotometer 65 maintained by the NOAA Climate and Monitoring and Diagnostics Laboratory, Boulder, Colorado. The mean difference in ozone obtained with the Dobson instruments relative to Dobson instrument 65, calculated from ADDSGQP observations in the air mass range 1.15-3.2, was minus 1.0 plus or minus 1.2 (1 sigma) percent. The WMO Standard Brewer Spectrometer 39 also participated. In the mean, the Brewer instrument measured 0.6 plus or minus 0.2 (1 sigma) percent more ozone than did Dobson instrument 65. Results are presented, also, of ozone vertical profile measurements made with the Dobson instruments, two Brewer spectrometers, a LIDAR, a balloon ozonesonde flown from Hohenpeissenberg, Germany, and balloon ozonesondes flown from Payerne, Switzerland.
The total ozone mapping spectrometer (TOMS) and stratospheric aerosol and gas experiment (SAGE) measurements show a significant reduction in the stratospheric ozone over the middle and high latitudes of both hemispheres between the years 1979 and 1991 (WMO, 1992). This change in ozone will effect both the solar and longwave radiation with climate implications. However, recent studies (Ramaswamy et al., 1992; WMO, 1992) indicate that the net effect depends not only on latitudes and seasons, but also on the response of the lower stratospheric temperature. In this study we use a general circulation model (GCM) to calculate the climatic effect due to stratospheric ozone depletion and compare the effect with that due to observed increases of trace gases CO2, CH4, N2O, and CFC's for the period 1980-1990. In the simulations, we use the observed changes in ozone derived from the TOMS data. The GCM used is a version of the NCAR community climate model referenced in Wang et al. (1991). For the present study we run the model in perpetual January and perpetual July modes in which the incoming solar radiation and climatological sea surface temperatures are held constant.
Extensive analyses of ozone observations between 1978 and 1998 measured by Dobson Umkehr, Stratospheric Aerosol and Gas Experiment (SAGE) I and II, and Solar Backscattered Ultraviolet (SBUV) and (SBUV)/2 indicate continued significant ozone decline throughout the extratropical upper stratosphere from 30-45 km altitude. The maximum annual linear decline of -0.8 +/- 0.2 %/yr(2sigma) occurs at 40 km and is well described in terms of a linear decline modulated by the 11-year solar variation. The minimum decline of -0.110.1% yr-1(2o) occurs at 25 km in midlatitudes, with remarkable symmetry between the Northern and Southern Hemispheres at 40 km altitude. Midlatitude upper-stratospheric zonal trends exhibit significant seasonal variation (+/- 30% in the Northern Hemisphere, +/- 40% in the Southern Hemisphere) with the most negative trends of -1.2%/yr occurring in the winter. Significant seasonal trends of -0.7 to -0.9%/yr occur at 40 km in the tropics between April and September. Subjecting the statistical models used to calculate the ozone trends to intercomparison tests on a variety of common data sets yields results that indicate the standard deviation between trends estimated by 10 different statistical models is less than 0.1%/yr in the annual-mean trend for SAGE data and less than 0.2%/yr in the most demanding conditions (seasons with irregular, sparse data) [World Meteorological Organization (WMO), 1998]. These consistent trend results between statistical models together with extensive consistency between the independent measurement-system trend observations by Dobson Umkehr, SAGE I and II, and SBUV and SBUV/2 provide a high degree of confidence in the accuracy of the declining ozone amounts reported here. Additional details of ozone trend results from 1978 to 1996 (2 years shorter than reported here) along with lower-stratospheric and tropospheric ozone trends, extensive intercomparisons to assess relative instrument drifts, and retrieval algorithm details are given by WMO [1998].
Weather radar imagery is a valuable new technique for the rapid recovery of meteorite falls, to include falls which would not otherwise be recovered (e.g. Battle Mountain). Weather radar imagery reveals about one new meteorite fall per year (18 falls since 1998), using weather radars in the United States alone. However, an additional ~75 other nations operate weather radar networks according to the UN World Meteorological Organization (WMO). If the imagery of those radars were analyzed, the current rate of meteorite falls could be improved considerably, to as much as ~3.6 times the current recovery rate based on comparison of total radar areal coverage. Recently, the addition of weather radar imagery, seismometry and internet-based aggregation of eyewitness reports has improved the speed and accuracy of fresh meteorite fall recovery [e.g. 1,2]. This was demonstrated recently with the radar-enabled recovery of the Sutter's Mill fall [3]. Arguably, the meteorites recovered via these methods are of special scientific value as they are relatively unweathered, fresh falls. To illustrate this, a recent SAO/NASA ADS search using the keyword "meteorite" shows that all 50 of the top search results included at least one named meteorite recovered from a meteorite fall. This is true even though only ~1260 named meteorite falls are recorded among the >49,000 individual falls recorded in the Meteoritical Society online database. The US NEXRAD system used thus far to locate meteorite falls covers most of the United States' surface area. Using a WMO map of the world's weather radars, we estimate that the total coverage of the other ~75 national weather radar networks equals about 3.6x NEXRAD's coverage area. There are two findings to draw from this calculation: 1) For the past 16 years during which 18 falls are seen in US radar data, there should be an additional ~65 meteorite falls recorded in worldwide radar imagery. Also: 2) if all of the world's radar data could be analyzed, the rate of recovery of fresh meteorite falls can increase by as much as ~3.6x the current rate. The authors' experience to date indicates that the most effective course of action would be to have local meteorite research groups (outside of the US) form research consortia and develop a working relationship with their nation's weather bureau for access to data. These research consortia could utilize the same, proven methods used for US NEXRAD imagery, internet eyewitness report aggregation, seismometry analysis, etc. to locate meteorite falls. The consortia could then recover and analyze meteorite falls and enrich their own research efforts. It would be beneficial to conduct a global program to coordinate the development of methods and data tools, as well as to coordinate meteorite sample sharing and research. Perhaps an institution such as the Meteoritical Society could lead such an effort.
Ozonesonde data constitute a mainstay of satellite calibration and are used for climatologies and analysis of trends, especially in the lower stratosphere where satellites are most uncertain. The electrochemical-concentration cell (ECC) ozonesonde has been deployed at ~100 stations worldwide since the 1960s, with changes over time in manufacture and procedures, including details of the cell chemical solution and data processing. As a consequence, there are biases among different stations and discontinuities in profile timeseries from individual site records. Since 1996 the Jülich [Germany] Ozone Sonde Intercomparison Experiment (JOSIE) has periodically tested ozonesondes in a simulation chamber designated the World Calibration Centre for Ozonesondes by WMO. In October- November 2017 a JOSIE campaign evaluated the sondes and procedures used in SHADOZ (Southern Hemisphere Additional Ozonesondes), a 14-station tropical and subtropical network. A distinctive feature of the 2017 JOSIE was that the tests were conducted by operators from eight SHADOZ stations; Nairobi, Natal, Irene, Costa Rica, Paramaribo, Reunion, Hanoi, Kuala Lumpur. Experimental protocols and preliminary results for the SHADOZ sonde configurations, which represent most of those in use today, are described. SHADOZ stations that follow WMO-recommended protocols record total ozone within 3% of the JOSIE reference instrument. Instrument biases noted in prior JOSIE and field tests like BESOS (2004) were noted in JOSIE-2017, with maximum effect in the stratosphere. In June 2018 we organized a series of dual launches during the OWLETS II campaign in the Maryland and Chesapeake Bay area (SHALLOTS = SHADOZ-OWLETS ParaLLel Ozonesonde Test Study). Instrument and solution types were varied as in JOSIE-2017 and three radiosonde-ozonesonde variants were tested. An example of a parallel sampling in SHALLOTS, from a Greenbelt EnSCI-iMet sonde combination flown with the Wallops SPCLMS package, is illustrated in the Figure. The result was a range of biases but in general the instrument combination (EnSCI-iMet) deployed at 11 SHADOZ stations recorded ~5-10% less ozone in the stratosphere than the SPC ECC sonde flown with a Vaisala or LMS system. These 2017 and 2018 results and prior JOSIEs demonstrate that regular testing is essential to maintain best practices in ozonesonde operations and to ensure high-quality data for the ozone assessment communities.
The United Nations Committee for the Peaceful Uses of Outer Space(UN-COPUOS) in its 2022 Space Weather Expert Group report, called upon the World Meteorological Organization (WMO), the InternationalSpace Environment Service (ISES) and the Committee on Space Research (COSPAR) to take a leadership role in improving the global coordination of space weather activities in consultation and collaboration with other relevant actors and international organizations. The three organizations have established a framework for trusting partnership while minimizing duplication of efforts and have agreed on three distinct domains in which the particular expertise and strengths of each of the three were identified: Research and Development (COSPAR), Facilitating Integration (WMO), andServices (ISES). The next stage in building a pathway to improved coordination is to lay the same foundation with other relevant organizations and actors engaged in space weather. We will present outcomes of the first International Space Weather Coordination Forum intending to shape the future of international collaboration on space weather with the ultimate aim of increasing the community’s ability to mitigate space environment threats. We will discuss approaches to alignments of bottom-up initiatives and community-driven roadmaps with national/regional strategic planning activities and funding programs. We will also review opportunities for taking advantage ofInternational Space Weather Action Teams (ISWAT) for planning pilot projects to demonstrate the value of collaboration and coordination.
Lightning is a natural hazard, an indicator of changes in convective storm behavior across multiple spatial and temporal scales, and a major influence on climate-affecting chemicals such as ozone and methane. Lightning also has substantial impacts on the near-space environment. As such, the World Meteorological Organization (WMO) has designated lightning as an Essential Climate Variable (ECV); that is, a measurement that is really important for understanding Earth’s climate. Spaceborne lightning observations are the gold standard for measuring global lightning, as the detection efficiency is more spatially uniform compared to ground-based lightning measurements. In addition, spaceborne is the only practical method for measuring total lightning (i.e., both intracloud and cloud-to-ground) at the global scale, as ground-based networks have limited ability to detect intracloud lightning at long distances (e.g., over oceans, far from land-based sensors). Since 1995, with only a two-year gap (2015-2017), lightning has been observed globally using a combination of Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) instruments. However, the year 2023 is the planned end for the International Space Station (ISS) LIS mission, and there is no designated low-Earth orbit (LEO) successor yet identified. Since 2017, geostationary (GEO) observations of lightning have become increasingly available. These include the U.S. Geostationary Lightning Mappers (GLMs), China’s Lightning Mapping Imager (LMI), and Europe’s Lightning Imager (LI). While GEO provides continuous, quasi-hemispheric coverage of lightning and thunderstorms, there are current gaps preventing global coverage, particularly in portions of Asia and the western Pacific, as well as high-latitude regions. Moreover, integration of the GEO constellation into a Climate Data Record (CDR) of lightning is a major challenge only recently begun to be addressed by the WMO. Furthermore, recent work has demonstrated some deficiencies in the global record of lightning from space. For example, small lightning flashes are very common in severe weather, but are difficult to observe using the present set of spaceborne lightning imagers. Moreover, some types of lightning are best observed using frequencies other than the commonly used near-infrared (777-nm), including ultraviolet and the radio spectrum. Finally, it is not possible to assess the vertical distribution of lightning globally, even though this measurement is highly relevant to thunderstorm behavior as well as lightning’s effects on greenhouse gases and the near-space environment. This presentation will provide a current assessment of lightning measurements from space, will identify significant current and future gaps in these observations, and will evaluate potential solutions for improving the overall CDR of global lightning.
The conference clearly demonstrated the increasing interest and growth of the scientific community working on the development and application of sub-seasonal to seasonal prediction since the start of the World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP) sub-seasonal to seasonal (S2S) prediction project in 2013. The conference, which was held at the University of Reading (United Kingdom), was organized into three main themes as briefly summarized below, with eleven invited talks, 74 oral contributed talks, and 101 posters. The conference also included a two-hour breakout session, wherein eight groups discussed the current state and prospect for S2S prediction, and an early career researcher event. A summary of these discussions and recommendations is presented below. The conference web page (https://research.reading.ac.uk/s2s-summit2023/) is archived at the University of Reading. Introductory comments by representatives of the World Meteorological Organization (WMO) WWRP and WCRP emphasized the importance of the weather–climate linkage, targeted by S2S forecasts (from 2 weeks to a season ahead), addressing the challenges of creating “end-to-end” forecasts that encompass the entire climate-services chain from the prediction science and forecast, to the development and issuing of forecast products tailored to informing user-decisions. They also emphasized the efficacy of multi-model ensemble efforts and databases to foster collaborations internationally and between operational centres and academia. Although the WWRP/WCRP S2S project comes to an end in 2023, S2S prediction will remain an important focus for WWRP and WCRP. In WWRP, a new project called SAGE (Sub-seasonal to seasonal predictions for Agriculture and Environment) will start in 2024. Another important legacy of the S2S project will be the maintenance of the S2S database (Vitart et al. 2017) and the establishment of a WMO Lead Center for sub-seasonal prediction multi-model ensemble (LC-SSPMME) which will provide real-time multi-model S2S climate information. In two keynote presentations, Prof. Brian Hoskins (University of Reading) and Dr. Gilbert Brunet (Australian Bureau of Meteorology) discussed the potential of S2S predictability and the ongoing journey for understanding and improving these predictions. This conference was a sequel to the International Conference on Sub-seasonal to Seasonal Prediction (Robertson et al., 2014) which took place in College Park (Maryland, USA) in February 2014 to celebrate the start of the WWRP/WCRP S2S project, and to WCRP and WWRP conferences in Boulder, USA, in 2018 (Merryfield et al., 2020). A significant development compared to the previous S2S conferences was the large number of presentations on research to operation (R2O) and S2S applications and on the use of artificial intelligence and machine learning (AI/ML) methods for S2S prediction. Some of these methods provide empirical S2S forecasts which are competitive with state-of-the-art dynamical models. Other presentations demonstrated that AI/ML can provide alternative calibration of dynamical model outputs to traditional methods. Several talks and posters highlighted the increasing use of AI/ML, including deep learning, in S2S forecast post-processing and using AI to identify higher flow-dependent skill. Finally, some presentations demonstrated the value of AI/ML methods for a better understanding of S2S sources of predictability and attribution of extreme events.
The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance Earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A 2022 WMO report on exascale computing recommends “urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities.” Further, the explosive growth in data from observations, model and ensemble output, and postprocessing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision-making. Artificial intelligence (AI) offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems, and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.
Accurate measurements of direct normal (beam) solar irradiance from pyrheliometers are important for developing and deploying solar energy conversion systems, for improving our understanding of Earth's energy budget for climate change studies, and for other science and technology applications involving solar flux. Providing these measurements places many demands on the quality system used by the operator of commercially available radiometers. Maintaining accurate radiometer calibrations that are traceable to an international standard is the first step in producing research-quality solar irradiance measurements. In 1977, the World Meteorological Organization (WMO) established the World Radiometric Reference (WRR) as the international standard for the measurement of direct normal solar irradiance (Frohlich 1991). The WRR is an internationally recognized, detector-based measurement standard determined by the collective performance of six electrically self-calibrated absolute cavity radiometers comprising the World Standard Group (WSG). Various countries, including the United States, have contributed these specialized radiometers to the Physikalisch-Meteorologisches Observatorium Davos - World Radiation Center (PMOD/WRC) to establish the WSG. As with all measurement systems, Absolute Cavity Radiometers (ACR) are subject to performance changes over time. Therefore, PMOD/WRC in Davos, Switzerland, hosts an quinquennial International Pyrheliometer Comparison (IPC) event for transferring the WRR to participating radiometers by invitation. The National Renewable Energy Laboratory (NREL) has represented the U.S. Department of Energy (DOE) in each IPC since 1980. And NREL has developed and maintained a select group of absolute cavity radiometers with direct calibration traceability to the WRR, and it uses these reference instruments to calibrate pyrheliometers and pyranometers using the International Organization for Standardization (ISO) 17025-accredited Broadband Outdoor Radiometer Calibration (BORCAL) process (Reda et al. 2008). To fill the gap between each IPC, NREL pyrheliometer comparisons (NPCs) are held annually at the Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Open to all ACR owners and operators, each NPC provides an opportunity to determine the unique WRR transfer factor (WRR-TF) for each participating pyrheliometer. By adjusting all subsequent pyrheliometer measurements by the appropriate WRR-TF, the solar irradiance data are traceable to the WRR.
The purpose of this report is to identify fundamental issues for coupled data assimilation (CDA), such as gaps in science and limitations in forecasting systems, in order to provide guidance to the World Meteorological Organization (WMO) on how to facilitate more rapid progress internationally. Coupled Earth system modeling provides the opportunity to extend skillful atmospheric forecasts beyond the traditional two-week barrier by extracting skill from low-frequency state components such as the land, ocean, and sea ice. More generally, coupled models are needed to support seamless prediction systems that span timescales from weather, subseasonal to seasonal (S2S), multiyear, and decadal. Therefore, initialization methods are needed for coupled Earth system models, either applied to each individual component (called Weakly Coupled Data Assimilation - WCDA) or applied the coupled Earth system model as a whole (called Strongly Coupled Data Assimilation - SCDA). Using CDA, in which model forecasts and potentially the state estimation are performed jointly, each model domain benefits from observations in other domains either directly using error covariance information known at the time of the analysis (SCDA), or indirectly through flux interactions at the model boundaries (WCDA). Because the non-atmospheric domains are generally under-observed compared to the atmosphere, CDA provides a significant advantage over single-domain analyses. Next, we provide a synopsis of goals, challenges, and recommendations to advance CDA: Goals: (a) Extend predictive skill beyond the current capability of NWP (e.g. as demonstrated by improving forecast skill scores), (b) produce physically consistent initial conditions for coupled numerical prediction systems and reanalyses (including consistent fluxes at the domain interfaces), (c) make best use of existing observations by allowing observations from each domain to influence and improve the full earth system analysis, (d) develop a robust observation-based identification and understanding of mechanisms that determine the variability of weather and climate, (e) identify critical weaknesses in coupled models and the earth observing system, (f) generate full-field estimates of unobserved or sparsely observed variables, (g) improve the estimation of the external forcings causing changes to climate, (h) transition successes from idealized CDA experiments to real-world applications. Challenges: (a) Modeling at the interfaces between interacting components of coupled Earth system models may be inadequate for estimating uncertainty or error covariances between domains, (b) current data assimilation methods may be insufficient to simultaneously analyze domains containing multiple spatiotemporal scales of interest, (c) there is no standardization of observation data or their delivery systems across domains, (d) the size and complexity of many large-scale coupled Earth system models makes it is difficult to accurately represent uncertainty due to model parameters and coupling parameters, (e) model errors lead to local biases that can transfer between the different Earth system components and lead to coupled model biases and long-term model drift, (e) information propagation across model components with different spatiotemporal scales is extremely complicated, and must be improved in current coupled modeling frameworks, (h) there is insufficient knowledge on how to represent evolving errors in non-atmospheric model components (e.g. as sea ice, land and ocean) on the timescales of NWP.
The intent of this white paper is to inform WMO projects and working groups, together with the broader weather research and general meteorology and oceanography communities, regarding the use of Observing System Simulation Experiments (OSSEs). This paper is not intended to be either a critical or cursory review of past OSSE efforts. Instead, it describes some fundamental, but often neglected, aspects of OSSEs and prescribes important caveats regarding their design, validation, and application. Well designed, properly validated, and carefully conducted OSSEs can be invaluable for examining, understanding, and estimating impacts of proposed observing systems and new data assimilation techniques. Although significant imperfections and limitations should be expected, OSSEs either profoundly complement or uniquely provide both qualitative and quantitative characterizations of potential analysis of components of the earth system.
The use of neural operators in a digital twin model of an offshore floating structure holds the potential for a significant shift in the prediction of structural responses and health monitoring, offering valuable real-time control insights. In this work, we investigate the effectiveness of three neural operators, namely the deep operator network (DeepONet), the Fourier neural operator (FNO), and the Wavelet neural operator (WNO), to accurately capture the responses of a floating structure under six different sea state codes (3 − 8) based on the wave characteristics described by the World Meteorological Organization (WMO). To further enhance the accuracy of the vanilla architecture of the neural operators, novel extensions, such as wavelet-DeepONet and self-adaptive WNO, are proposed in this paper. The results demonstrate that these high-precision neural operators can deliver structural responses more efficiently, up to two orders of magnitude faster than a dynamic analysis using conventional numerical solvers. Additionally, compared to gated recurrent units (GRUs), a commonly used recurrent neural network for time-series estimation, neural operators are both more accurate and efficient, especially in situations with limited data availability. Taken together, our study shows that FNO outperforms all other operators for approximating the mapping of one input functional space to the output space as well as for responses that have small bandwidth of the frequency spectrum. Conversely, DeepONet, with historical states, proves most accurate in learning the mapping of multiple input functions to the output space and capturing responses within a broad frequency spectrum.
Accurate measurements of direct normal (beam) solar irradiance from pyrheliometers are important for developing and deploying solar energy conversion systems, improving our understanding of the Earth's energy budget for climate change studies, and for other science and technology applications involving solar flux. Providing these measurements places many demands on the quality system used by the operator of commercially available radiometers. Maintaining accurate radiometer calibrations that are traceable to an international standard is the first step in producing research-quality solar irradiance measurements. In 1977, the World Meteorological Organization (WMO) established the World Radiometric Reference (WRR) as the international standard for the measurement of direct normal solar irradiance (Frohlich 1991). The WRR is an internationally recognized, detector-based measurement standard determined by the collective performance of six electrically self-calibrated absolute cavity radiometers comprising the World Standard Group (WSG). Various countries, including the United States, have contributed these specialized radiometers to the Physikalisch-Meteorologisches Observatorium Davos - World Radiation Center (PMOD/WRC) to establish the WSG.
Site A1 netCDF L3 data files have level 3 (L3) data that have gone through the calculation service and contain all the data from the algorithms, including mixing layer height values and quality index data. L3 default files contain L3 data that use the default preset for a live plot. File naming schema: L3_DEFAULT_ _YYYYMMDDHHMM_ _ .nc Name Description L3 Identification of the data level DEFAULT Identification of the L3 file type CUSTOM OFFLINE STATION_NUMBER WMO station number, if defined YYYYMMDDHHMM UTC time ParameterKey Identification of the advanced algorithm settings. See the table below for an explanation. FREE_FORMAT File suffix, if defined
Site A1 netCDF L3 data files have level 3 (L3) data that have gone through the calculation service and contain all the data from the algorithms, including mixing layer height values and quality index data. L3 default files contain L3 data that use the default preset for a live plot. File naming schema: L3_DEFAULT_ _YYYYMMDDHHMM_ _ .nc Name Description L3 Identification of the data level DEFAULT Identification of the L3 file type CUSTOM OFFLINE STATION_NUMBER WMO station number, if defined YYYYMMDDHHMM UTC time ParameterKey Identification of the advanced algorithm settings. See the table below for an explanation. FREE_FORMAT File suffix, if defined