In this study, we try to explore the feasibility on whether or not the magnetospheric processes under northward Interplanetary Magnetic Field (IMF) conditions can be diagnosed using two different auroral phenomena; transpolar arc (TPA) and omega-band aurora. Both TPA and omega-band aurora can occur during the northward IMF intervals, and their appearances are closely related with the nightside magnetospheric processes. TPA can be formed and grown by the field-aligned currents induced by the plasma flow shear or the plasma vortex structures between the fast plasma flows generated by magnetotail magnetic reconnection and slower background magnetospheric flows, and the convection of the reconnection-formed closed magnetic fluxes, which cause in the nightside plasma sheet. On the other hand, the omega-band aurora can be attributed to the Kelvin-Helmholtz instabilities triggered by the flow shear between the plasma flows of the nightside magnetospheric boundary layer such as low-latitude boundary layer (LLBL) and background magnetospheric (plasma sheet) flows. If both auroral phenomena can simultaneously be observed, we might remotely investigate (diagnose) how the plasma and its energy are transported in the nightside magnetosphere and at the magnetospheric boundary region under northward IMF conditions. We will discuss the feasibility of this magnetospheric diagnosis, giving the observational example(s) of simultaneous observations of two different auroral phenomena, that is, TPA and omega-band aurora, and in-situ magnetospheric observation(s). Keyword: 1. Transpolar arc and omega band aurora 2. Solar wind-magnetotail-ionosphere coupling 3. Magnetospheric diagnosis 4. Magnetospheric dynamics under northward IMF conditions

Japan Agency for Marine-Earth Science and Technology (JAMSTEC) has been disseminated information of data and samples obtained by JAMSTEC’s research vessels and submersibles via some databases. The core database is the Data and Sample Research System for Whole Cruise Information (DARWIN, http://www.godac.jamstec.go.jp/darwin/e). DARWIN provides information of more than 2000 cruises and 6500 dives, and its related observation data and geological sample. Each cruise or dive information page of DARWIN has links to related contents such as biological sample, deep-sea image, cruise report and data book provided by another databases. In this poster, we will introduce some examples of efforts to improve the reusability of data and sample described above. - Assignment of Digital Object Identifier (DOI): DOIs have been assigned to more than 2000 research cruises information from the early 1980s onward to promote data citation. A granularity of DOI is a research cruise information page defined as a cruise ID at this time. - Specification of Data Policy: DARWIN has been treated data and samples based on only JAMSTEC data policy until FY2018’s research cruises. Currently, the applicable policy is dependent on type of cruise because the cooperative research cruises have been started since FY2019. DARWIN has been updated to display of an applicable policy on each information page clearly. The function is also available to add to another policy in the future. - Data Rescue: A cruise report is a prompt report that includes the purpose of the cruise, information about what kind of observation was done, how it was done and the results. Cruise reports for past research cruises have been found when moving laboratory and submitted to the Data Management Group. The reports have been scanned and saved as individual PDF to store for long-term and prepare for publication. A part of them with Principle Investigators’ consent have been disseminated step by step.

Batan Bay and Tinago Lake are shallow embayments connected to each other, located on the north of Panay Island, central Philippines (11.53° – 11.67°N, 122.38° – 122.52°E). Although they had been originally surrounded by dense mangrove forest till the middle of the last century, mangroves have been mostly cleared and converted into fish and shrimp ponds. Recently, shelves and rafts for cultivating oysters and green mussels have become widespread in the shallow areas of the embayments (see Figure as an example). Replantation of mangroves is also ongoing in limited areas of Batan Bay. We are conducting researches there focusing on ecosystem services of mangroves and seagrass meadows, especially in relation to carbon sequestration and aquaculture production. In this presentation, we report preliminary survey results on environmental conditions that may influence growth and survival of cultivated bivalves, such as freshwater inputs and potential food resources. The survey was conducted in both dry season (February 2019) and rainy season (November 2019). Although the salinity gradient across the bay due to freshwater input was evident in both seasons, the oxygen isotope ratio of seawater indicated that evaporation overwhelmed in inner bay sites in the dry season. Concentrations of chlorophyll and suspended particulate organic matter (POM), i.e. potential food source for bivalves, were high in the inner bay area. Carbon stable isotope ratio (δ13C) of dissolved organic carbon (DIC) and POM showed spatial gradient from the bay mouth (high) to inner sites (low), indicating the influence of riverine DIC and POM inputs. However, the δ13C of oysters (adductor muscle) was consistently higher than POM and showed no clear spatial gradient. The δ13C of oysters was relatively higher for individuals collected from inside or edge of seagrass meadows than those collected in open areas. These results suggest that oysters assimilate only a specific fraction of POM relatively enriched in 13C (i.e. marine-origin POM) and that seagrass meadows support growth of oysters by providing additional food source (e.g. attached microalgae that are abundant on seagrass blades).

Subduction zones showcase the multiplicity of earthquakes—interplate, intraplate and intraslab—with shallow, intermediate, or deep focus, associated with different energy release patterns and frequency contents. An understanding of the duration and frequencies associated with various pulses of energy is useful for damage assessment. Empirical Mode Decomposition (EMD) of strong-motion records and the application of Hilbert transform have been suggested to overcome the limitations of the Fourier spectral analysis in dealing with highly non-linear strong-motion records (Huang et al., 1998, Zhang et al., 2003). Following the same approach, we have been trying various methods of analysis using the KiK-net strong-motion records to explore the efficacy of these techniques in representing the source of the rupture, in terms of energy release and frequency distribution. Our previous studies used EMD and time-frequency analysis tools such as spectrogram, scalogram, and Hilbert spectrum, using Intrinsic Mode Functions (IMFs) of the original signals as inputs. Nishant (2019) made random picks of IMFs to represent sources by correlating the sum of the selected IMFs with the original signal but found that the results were station dependent. We selected IMFs based on their frequency content (0.1 to 3 Hz) and used their linear combinations to develop the Energy Release Functions (ERF) for individual earthquakes (Mache et al., 2019). They reported that the ability to capture the signature of the original signal using the IMFs varied between earthquakes and stations. Next, we selected stations based on the direction of rupture inferred from teleseismic waveform models. The use of appropriate combinations of individual IMFs, chosen based on the direction of slip, resulted in ERFs whose shapes compared better with the Moment Rate Functions (MRFs) obtained from the teleseismic models. To further explore the station dependence on the resolution of ERFs viz-a-viz the MRFs, we used the instrumental seismic intensity distribution maps (JMA 1996, Shabestari and Yamazaki 2001) to select the stations. We analyzed five earthquakes; two interplate (Mw 7.2 2005 Miyagi, and Mw 6.9 2008/07/19), two intraplate (Mw 7.0 2003 Sendai, and Mw 7.2 2012 Kamaishi) and one intraslab (Mw 7.1 2011 Miyagi), following the above methodologies. This abstract presents the initial results of our study, which to our knowledge, is the first of its kind and holds significant potential in understanding the spatial and temporal patterns of energy release and their associated frequencies. [cont.]

Infrasound waves can be defined as the sound waves with frequency range from 0.003 to 20 Hz. Kochi University of Technology (KUT) Infrasound Sensor Network contains 30 infrasound sensors which are distributed all over Japan, a large number of sensors are located in Shikoku Island, all infrasound stations installed with accelerometers to measure the peak ground acceleration (PGA) which can be a good detector for infrasound sources occur on or under the ground like earthquakes. Many earthquakes detected by our network after establishing of the network since 2016. In this study we will focus on all the possibilities for infrasound detection from earthquakes using KUT sensor network and International Monitoring system (IMS) stations for the earthquakes which were detected in southern of Japan during 2019. The selected events for this study are recorded in different international databases; Reviewed Event Bulletin (REB) database of International Data Center (IDC) , Japan Meteorological Agency (JMA) and United States Geological Survey (USGS). There are different scenarios for infrasound coupling from earthquakes one of these scenarios is the conversion of seismic waves to acoustic from the generated T-phases of oceanic earthquakes. On 09 of May 2019, at 23:48:00 UTC an earthquake with magnitude 6.0 mb happened in west of Kyushu Island and infrasound sensors recorded a clear P-waves, However station K53 and I30JP recorded infrasound waves at distances ranges between 850 to 870 km, In addition to T-phases well-recorded from the earthquake in H11N station near Wake island at 3750 km from the event. Progressive multi-channel cross correlation method applied on both infrasound and hydroacoustic data to identify the arrival phases and the back-azimuth of the waves from station to the source. Moreover, infrasound propagation simulation applied to the event to confirm the infrasound arrivals. Ground to Space Model (AVO-G2S) used with HWM-14 and NRL-MSISE to construct the atmospheric profile for higher altitudes up to 180 km over the event area, furthermore the 3d ray tracing process and the calculation of the transmission loss equation by normal modes and parabolic equation methods applied. In conclusion this study shows the earthquake detectability from infrasound waves using local infrasound sensors for the largest earthquakes occurred in southern of Japan during 2019. Many parameters control the generation of infrasound from earthquakes; magnitude, depth, mechanism and the topographic features. In addition to the T-phases generation through the SOFAR layer can be an evidence of seismic conversion to sound for the oceanic earthquakes as occurred on the earthquake of 09 May 2019, after applying the propagation simulation with (AVO-G2S) model on this earthquake the tropospheric arrivals confirmed and the calculated celerities well-correlated with the real detected data .

In the last few years, ALOS/PALSAR (L-band) (HH, HV, VH and VV) images have been widely used due toits ability to penetrate the surface in certain conditions for example of low moisture or dry friable sandysoil. Images from ALOS-1 sensor have been applied to delineate subsurface structures. Optical imagessuch as Landsat-7 ETM+ data are used to discriminate between scatterings from earth surface andsubsurface materials. Thus, Farafra desert is an optimal environment for L-band microwave penetration.Therefore, this research involves mapping and interpretation of lineaments, surface and subsurfacestructures. The interested four spots at Farafara sand sheets display many structures that not have beentraced in the Egyptian official geological maps. Speckle noise is found in radar images due to many reasons, for example, when an object stronglyreflected between itself and the spacecraft causing noise. Refined LEE Filter (RLF) is applied for specklenoise reduction; speckle noise near strong edges is not strongly filtered, leaving the center of the pixelunfiltered, so, this procedure is an essential step in processing of polarimetric data to improve theaccuracy of the data and enhance resolution. ALOS/PALSAR data are processed into circular polarizationfor providing the best viewing of morphological and subsurface lineaments. The ellipse shape governed bytwo axes; semi-major axis ‘a’ and semi-minor axis ‘b’. Orientation angle(ψ) is measured frompositive horizontal axis X counter clockwise direction, orientation angle range from 0° to 180°. Ellipticity(χ) is a shape parameter defined by the degree of oval shape, defined by χ=arctanb/a and can takevalues between -45° to +45°. As, the circular polarization yielded best outputs of subsurface structure indifferent trends, full polarimetric ALOS/PALSAR images (PLR) are transformed into circular polarization, bychanging both angles into orientation angle ψ=0° and elliptical angle χ=45°. Full polarimetric images arerepresented in Pauli RGB. Landsat-7 ETM+ data are freely uploaded with the same date and location ofALOS/PALSAR images. Bands 1, 2, 3, 4, 5 and 7 are merged together, then bands (R:2, G:4, B:7) arechanged to obtain best spatial resolution. Landsat-7 images have some gap areas, which is essentially befilled with Landsat-7 data acquired at the same time of the year by histogram matching technique to fillthe missed pixels of the interested target scenes according to Landsat 7. The obtained rose diagramshows two trends of dominant and secondary; the most dominant direction is North West (NW 330°),while the secondary trend is North (North 10°). This result is confirmed by the field survey. The dominantdirection of lineaments extracted from ALOS/PALSAR images is well fitted with the secondary direction ofthe geological structure in the study area. This work represents a stage of achievement in detecting buried lineaments covered by sand sheets byusing ALOS/PALSAR and Landsat-7 ETM+. Surface and subsurface

Quantifying the spatiotemporal variability of precipitation is the principal component for the assessment of the impact of climate change on the hydrological cycle. A better understanding of the quantification of variability and its trend is vital for water resources planning and management. Therefore, a multitude of studies has been dedicated to quantify the precipitation variability over the years. Despite their importance for modeling precipitation variability, the studies mainly focused on the amount of precipitation and its spatial patterns. The studies investigating the spatial and temporal variability of precipitation across the Indian subcontinent, in general, and at multiscale, in particular, are limited. In this study, we introduce a novel measure, Standardized Variability Index (SVI), based on information entropy to investigate the spatiotemporal variability of precipitation. The proposed measure is independent of the temporal scale, the length of the data and can compare the precipitation variability at multiple timescales. Distinct spatial patterns were observed for information entropies at the monthly and seasonal scale. Stations with statistically significant trends were observed and vary from monthly to seasonal scale. There is an increase in the variability of precipitation amount across Central India. Trend analysis revealed there is changing behaviour in the precipitation amount as well as rainy days, showing an increase in the probability of occurrence of extreme events in the near future. In addition, coupling the mean annual rainfall with SVI enables a relative assessment of the water resources availability.

In coastal regions, more precaution for urban expansion should be considered regarding hidden geological hazard from the existence of expansive clay soil and shallow groundwater level. These conditions cause huge damage to engineering constructions that leads to losses of human lives and financial property. However, very little studies were focused on hazard assessment of swelling clay potentiality using GIS approach, because its natures as occur slowly by time. The purpose of the present work is the analysis of geological–geotechnical factors to present a geo-hazard risk assessment model for the identification of high risk-prone regions in the coastal zone using an integrated GIS statistical system and Electrical Resistivity Tomography (ERT) mapping. Suez city (the case study area) is located in the northwest of the Gulf of Suez that has a vital and attractive global location for trading and investment. The geo-hazard model was created in a GIS environment by integrating thematic maps of possible controlling factors from ALOS-DEM image and available geological and geotechnical boreholes. These factors showed a varied ranges: slope (0-35°), elevation (0-50 m), superficial soil (Conglomerate to silty clay), clay thickness (0-25 m), depth to groundwater (0-20 m), TDS (1000-35000 ppm), Cl-1 (500-17000 ppm), So4 (250-9000 ppm) and pH (6.8-8.7) and in conjunction with swelling potentiality (Liquid Limit (LL) (35-88 %), Plastic Index (PI) (12-62 %) and free Swelling (Sf) (35-150 %)). Assessment these factors causes kind of uncertainty during the evaluation procedure, thus all thematic maps were scored and weighted according to specified criteria to produce severity distributions maps. The crucial relationships between surface and subsurface factors were identified by employing geospatial qualitative and Pearson’ correlation analysis. In the considered case, the clay soil is an inorganic cohesive type of high to a very high swelling degree. Among tested factors, the existence of clay soil and its thickness seem to play an important role to increase groundwater level that approach surface in several sites of Suez city, hence rising the risks of Total Dissolved Salts (TDS), Chloride (Cl-1), and augmenting swelling potential. Accordingly, the designed suitable relative weights were determined and all thematic maps were combined to produce a geo-hazard map using Simple Weighting Overlay (SWO) method. This approach illustrates the significant factors and the arithmetic weights assigned to each level of severity, and therefore they should be considered in similar studies. Geo-hazard map was produced with four degrees of severity for urban development: low, marginal, severe and very severe comprising 36.38, 40.28, 22.13 and 1.2 %, respectively, of the study area. The very severe area was observed mainly around El Kapanon district. An extensive field survey was performed, noted significantly high saline groundwater move into the sewage system. Seven 2D- ERT pro

Predication of temporal trends of aerosol optical depth (AOD) within the numerical climate models with enabled chemistry module is very challenging and computationally expensive. In this work, new predication model is introduced based on artificial neural networks (ANN) in order to estimate average AOD over Egypt. Long short-term memory (LSTM) algorithm which is artificial recurrent neural network (RNN) architecture, is selected to construct the predication model. Seven input datasets for LSTM algorithm are from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis within period (1980-2017). The seven variables are pressure (PR), temperature (T), wind speed (W), dust surface particulate matter (PM2.5), surface (SO2) and (SO4) concentrations and (CO) concentration. AOD is the output of the trained and validated model. Effects of changing the number of both hidden layers and number of neurons per layers were evaluated. The results of increasing the number of neurons per one hidden layer revealed that increasing the number of neurons leads to three main finding (a) leads to faster convergence of loss function. (b) Produces more realistic AOD estimation (c) RMSE is reduced by increasing number of neurons. It was also found that, the model with one hidden layer and 50 neurons is the best model setup with RMSE (0.06). However, our studies showed also that increasing the number of hidden layers has no dominant effect on model RNN performance. The proposed LSTM model showed a very high level of accuracy with percentage 99.94 %. Future work can include more variables that has direct effect on AOD calculations. Both ensemble algorithms and different datasets can have more positive impact on the current proposed model.

Previous studies have shown that the Indian Ocean Dipole (IOD) has a significant impact on land temperatures over southern Europe. However, whether IOD influences rainfall over this region and how this impact compares to that of El Nino Southern Oscillation (ENSO) have not been established. Here using the E-OBS gridded rainfall datasets for the period 1958 to 2012, we have analyzed the influence of IOD and ENSO on European rainfall. We find that IOD impacts are predominantly felt over southwestern Europe in a region covering Spain and Portugal during the peak phase of the event. Correlations exceeding 0.4 are observed over the central regions of Spain. We find that ENSO impacts on European rainfall are substantially weaker compared to that of IOD, but occur with a pattern similar to the latter. Partial correlation analysis suggests that the marginal ENSO correlations are a statistical areifact arising from the co-occurrence of a fraction of the El Nino events with positive IOD events. Possible dynamical mechanisms by which IOD impacts rainfall over southwestern Europe will be discussed.

Since we discovered the newly morphological transpolar arc (TPA), whose nightside end got distorted toward pre- or post-midnight, identified as “nightside distorted TPAs”, their fundamental characteristics have been revealed based on investigations of the space-borne auroral imager data and corresponding solar wind conditions. Nightside distorted TPAs had two types; “J”- and “L”-shaped TPAs, and their locations of appearance (dawn or duskside of the polar cap) were governed by the polarity of the By component of the Interplanetary Magnetic Field (IMF). Furthermore, we found that the nightside distorted TPAs have antisymmetric morphologies in the Northern and Southern hemispheres, also depending on the IMF-By orientation. In this presentation, we show that that the electric currents flowing aligned to the magnetic field lines which connect between the magnetotail and the ionosphere, that is, Field-aligned currents (FACs) play an essential role in the formations of the “J”- and “L”-shaped TPAs. They are induced by significant plasma flow velocity difference (plasma flow shear) between the fast plasma flows associated with nightside magnetic reconnection and slower background plasma flows in the magnetotail. The current vortex structures with the counterclockwise rotation are also clearly seen in the ionospheric current vectors derived from fluctuations of the geomagnetic field measured at the ground observatories beneath and in close proximity of the growth regions of the nightside distorted TPA. This result suggests that the FACs were flowing out of the ionosphere toward the magnetotail (upward FACs) near the TPA. Furthermore, based on the geomagnetic field variations and the SuperDARN HF radar data, we obtained evidence in which the locations of magnetotail magnetic reconnection, which persisted even during northward IMF-Bz intervals, that is, the TPA durations, retreated further down tail as the TPA grew to the dayside. Taking into account these observational results, we finally show a model to illustrate the nightside distorted TPA (particularly, “L”-shaped TPA) formation.

A theory postulates that a huge ice lake named “Lake Agassiz” existed near the border between Canada and the United States during the last glacial age. It was thought that this lake collapsed, sometime between 13,000 to 8,200 years ago, causing global environmental changes such as cooling in the Younger Dryas period and the sea level rise. However, the truth about Lake Agassiz and its collapse remained unclear. To verify the actuality of the collapse, a simulation software was created for the geomorphological analysis and water volume calculation. The result of the present analysis indicated that the amount of water in Lake Agassiz was much smaller than presumed in the previous theory. Considering the surrounding topography, we deduced that Lake Agassiz was not the type of lake whose collapse would have caused a large-scale flood. Additionally, from a slope map created for the North American continent, we discovered a topography that appears to be a trace of erosion caused by a large-scale flood near Lake Agassiz. These findings reveal that the flooding of Lake Agassiz was likely caused by the collapse of an even larger ice-sheet lake. This study considers the scale and mechanism of the floods from a giant ice-sheet lake that existed in the Laurentide Ice Sheet.

When the COVID-19 pandemic forced institutions to close their physical spaces, many researchers and professors were required to work from home. Media outlets and individuals wondered if women specifically would be shouldering the childcare and/or homeschooling responsibilities, decreasing the time they had for professional activities. Preliminary analyses show mixed results: some have seen decreased submissions from women (Vincent-Lamarre et al., 2020; Del Boca et al., 2020), with at least one other showing an increase in submissions from women (Dolan & Lawless, 2020); and another suggests the rate of male-athored submissions to preprint archives are growing faster than those from women (Frederickson 2020). AGU has been monitoring our monthly submission data to understand how the pandemic and stay-at home orders are affecting our submissions from specific demographics—based on author gender, age, and country. Our analysis finds that the pandemic so far has not resulted in a decrease in submissions to AGU journals; nor has there so far been a decrease in the participation of women as submitting authors. Instead, we have seen an increase in submissions from most author groups compared to year-to-date numbers in previous years.

Turbulent kinetic energy dissipation rates in the Indonesian throughflow (ITF) exit passages to the Indian Ocean, the Lesser Sunda waters, are inferred from archived CTD measurements and recent high-resolution time series data sets. Dissipation rates from archived data sets are inferred using an improved Thorpe scale method validated against microstructure measurements. Elevated dissipation rates ~[10-6-10-7] m2s-3 were observed in the straits, where internal tides are generated. Tidal variations seemingly influence the dissipation rates and diffusivities as has been suggested from the yoyo profiling data sets. The spatial pattern of dissipation rates inferred from the high-resolution 3D hydrodynamics model output of Nagai et al (2015) shows a general agreement with the observations in the location of the mixing hot spots and suggests that the M2 internal tide is the dominant factor driving the turbulent kinetic dissipation rates in this region. The bias in the model is possible due to the lack of representation of the ITF and mesoscale circulation in the model.

The aim of this study is to determine the hydrochemical properties of water resources in the Seyfe Basin and to understand processes involving water chemistry using statistical techniques such as principal component analysis (PCA) and cluster analysis. Seyfe Lake closed basin is located west of Kirsehir (Turkey) in the Central Anatolia. Considering the importance of the Seyfe Lake Basin for its water resources potential and due to its fragile ecosystem, a detailed hydrogeological characterization of the basin has been undertaken. In order to characterize hydrogeological system accurately, water samples were collected from springs, wells, drainage channels during September and December 2019 field campaigns from the Seyfe basin. The temperature, pH, total dissolved solids (TDS) and specific electrical conductance (EC25°C) were measured at the field and spatio-temporal changes of major ions are evaluated. The waters have neutral to slightly alkaline character, and most of the water samples are saturated with calcite, dolomite and aragonite minerals. According to the results obtained from Gibbs, Piper plot, and PCA, the water-rock interaction takes place without any remarkable ion exchange reactions. Water facies identified with the Piper diagram; supports this view. Water types are determined as Ca-HCO3 for springs; Na-HCO3 for wells; Na-SO4 for drainage channel in the dry season and Na-Cl in the rainy season. In Ihe study area; ionic compositions of the springs are not affected by seasonal changes. The high sulfate concentration is probably related to the weathering of evaporitic rocks in the basin. The waters are grouped according to the results, and the difference observed within the groups are related to the lithology of aquifers and flow path of the waters. KEYWORDS: Hydrochemistry, Major ions, Kırsehir, Central Anatolia, Seyfe Closed Basin, Spatio-temporal Changes.

JAMSTEC publicly distributes samples and data obtained by JAMSTEC-AORI-JURCAOS Cooperative Research Cruises [1], as well as those by JAMSTEC private/open-call cruises, through online database (DB) websites, for additional uses with research/educational purposes. These online DBs are, from a long-term perspective, under a process of reorganization and integration: Public-level information systems for rock and sediment core samples were integrated into DARWIN DB [1] in FY2017. As for marine biological samples, whose information has been mainly distributed through “Marine Biological Sample DB [3], a part of information is already shared with DARWIN to utilize its search/map functions. DB integration is in progress for not only public-level but also management-level information system, which are operated by sample holders responsible for storage of physical samples. In FY2018, JSDB (JAMSTEC Sample Management Database) is installed for the management of JAMSTEC rock, sediment core and biological samples, and actual data was transferred into this new system in FY2019. For rock and sediment core samples, information forwarding from management-level system (JSDB) to public-level system (DARWIN) is planned to be established in the near future. JSDB consists of data tables for sample matadata information for onboard sampling activities, sample archive information for status and storage of physical samples, associate data information for various data obtained for samples, literature information for published documents, sample distribution information for service logs for sample requests. User authorization includes group setting, enabling individual sample holders outside Data Management Office to read, create and modify the information in an appropriate manner, although the DB is only accessible from inside JAMSTEC because of security reasons. Associate data information is supposed to include various data types, such as photos/images, text-based descriptions, spread-sheets and URLs etc., and open/close status control and group-setting are available for individual entries. Information for research proposals/projects or other data management issues, which should be associated with multiple samples, can also be managed as associated data information. For the future possibility of involvement with IGSN, sample metadata entries and their vocabulary are reorganized to follow the IGSN Descriptive Metadata [4], as much as possible. Peoples involved in sample and data management tend to spend much effort for dealing with unusual conditions/situations which are not originally expected. Robustness is important for design/operation of information systems, because lack of flexibility and too much complexity of information systems are frequent causes of such kind of problems. [1] https://www.aori.u-tokyo.ac.jp/coop/ [2] http://www.godac.jamstec.go.jp/darwin/ [3] http://www.godac.jamstec.go.jp/bio-sample/ [4] https://www.geosamples.org/metadata

The ocean plays important roles not only in the global climate system but also in the global material cycling through biogeochemical processes, and has close relationships with the daily lives of people through fisheries, marine energy and resources, ocean transportation, marine sports, ocean relaxation activities, and others. The Ocean Literacy movement began in the U.S. in the early 2000s, and has recently become international as shown by the Ocean Literacy Portal website operated by IOC/UNESCO. In Japan, the present national standard course of study at elementary school has not given any room for ocean education while the Oceanographic Society of Japan (JOS) and 34 other academic societies/committees gave a proposal entitled, “On the Setting up of a class named, ‘the role of Ocean’ in the national standard course of study for the 4th grade students in the elementary science education” to the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in April 2016. In the U.S., aiming to serve as a community-based measurement tool that allows the comparison of levels of ocean knowledge across time and location, the International Ocean Literacy Survey (IOLS) project has been started since 2015. Fauville et al. (2018, https://doi.org/10.1080/13504622.2018.1440381) published the results from IOLS Version 2, and the English version IOLS Version 4 was finalized after reviewing the English IOLS Version 3 by IOLS Advisory Board consisting of international marine researchers, communicators, teachers, and psychometricians. The English version of the IOLS Version 4 was translated into 14 languages (Catalan, Chilean, Dutch, Greek, Italian, Japanese, Korean, Polish, Portuguese, Simplified Chinese, Spanish, Tagalog, Thai, and Traditional Chinese) and its field testing was conducted during February and March 2019 with nominal 6945 participants worldwide including nominal 567 participants from Japan. In collaboration with IOLS Version 4 field testing, JOS and the Marine Learning Center took part in correcting the original Japanese draft of IOLS Version 4, sponsored IOLS Version 4 field testing, and made a wide campaign to high-school teachers through sending recommendation letters to academic societies and other ocean-related organizations.

Nowadays, it is so important in saving our economic activity and evading the disasters caused by terrestrial electromagnetic effects to predict both temporal and spatial scales of the geomagnetic disturbances based on in-situ solar wind observations. Recently, Neural Network (NN) is one of the notable techniques for the predictions of the magnetospheric activities. However, NN has a problem referred to as ‘black box’, which is difficult to extract which solar wind parameters are the most important for prediction. In this study, we examine a significant relationship between Kp index, which represents the magnetospheric activity, and the solar wind conditions based on an interpretable neural network: ‘Potential Learning (PL)’. A feature of the PL is to make a network that can understand the input variables by learning the “input potentialities”, which are indices calculated using the variances of the solar wind parameters as input variables. In this study, we investigate the magnetospheric activity profile when the Interplanetary Magnetic Field (IMF) oriented southward (Bz < 0). As the input solar wind data, we utilize the two components of the magnetic field (Bx, By) in GSE, and solar wind flow speed, and number density during 20 years between 1999 and 2018. Furthermore, we divide the associated values of Kp into two groups (targets): ‘Kp = 6- to 9 (positive target)’ and ‘Kp = 0 to 1+ (negative target)’. Because the data number of positive target was smaller than that of negative target, the negative target samples are randomly selected so that the data numbers of both targets become equal. Based on the PL neural network, we obtain two important results; 1) the solar wind plasma flow speed might have the most influential in the increase of the Kp index, and 2) as the secondary influential parameter for the Kp increase, the solar wind proton density is considered. In the presentation, we will discuss feasibility of the application to the prediction of the magnetospheric activity based on the solar wind parameters.