The Global Warming Potential (GWP) is a widely used single-number metric used to compare the climate change effects of various greenhouse gases. Although GWP has an established role in international climate agreements, it is unphysical, unintuitive, arbitrary, ignores the time dependence of emission sources, and is in some cases misleading. The same doubts have been expressed by the convening lead author of the relevant chapter in the First Assessment Report of the Intergovernmental Panel on Climate Change, in which GWP was introduced. GWP and the related CO2-equivalent methodology have no place in describing the effects of climate change mitigation strategies beyond a 20 year horizon. An important element of sound policy making is the quantitative analysis of policy interventions. This work argues for the broader use of temperature change trajectories in educating policymakers and the public about greenhouse gas control. Modeling tools include general circulation models, related reduced complexity models, and simpler models of global mean temperature change. Examples are presented illustrating the misleading nature of GWP and the CO2-equivalent methodology. These include the greenhouse gas impacts of (1) single year and multiyear emissions of methane, (2) natural gas and coal use in the electric power sector, (3) pipeline and LNG transport of natural gas, (4) natural gas flaring, and (5) livestock herd reduction. Responding to climate change is likely to require global investments measured in trillions of dollars. Clear and accurate communication among and between scientists, policy makers. and the general public is essential. GWP is a crude, inaccurate tool that and the general public is essential. GWP is a crude, inaccurate tool that played a constructive role in the formulation of international agreements. Using better modeling tools can help make climate policy discussions more scientifically rigorous while demystifying the criteria upon which policy choices are made.

Pore connectivity, a topological characteristic of pore structure, is oftentimes more important than the geometrical aspects in controlling fluid flow and mass transport in porous natural rocks as well as their associated utilities in energy and environmental stewardship. A different extent of pore connectivity can be reflected in the proportion of isolated pore space not connected to the surface of natural rocks. This work presents the multi-approach and multi-scale laboratory studies to investigating the proportion of isolated pore space of, and its resultant anomalous fluid flow and radionuclide movement in, generic geological barrier materials (clay sediment, crystalline rock, salt rock, shale, tuff). The samples include clay sediments of Wakkanai formation at Horonobe underground research center in Hokkaido of Japan, Opalinus clay of Mt. Terri Underground Research Laboratory as well as granodiorite from the Grimsel Test Site in Switzerland, salt rock from Waste Isolation Pilot Plant in New Mexico, various shales (Barnett, Eagle Ford and Wolfcamp from Texas), and welded tuff in Yucca Mountain in Nevada. Working with sample sizes from <75 μm to several centimeters, the experimental approaches include the independent quantification of both (1) surface-accessible pore space with various probing fluids (e.g., helium in expansion, water in vacuum saturation and nuclear magnetic resonance, mercury in intrusion porosimetry, nitrogen in gas physisorption, and Wood’s metal in high-pressure impregnation and micron-scale tracer mapping using laser ablation-ICP-MS); and (2) total (both connected and isolated) porosity by small angle X-ray scattering. In summary, our evolving complementary approaches provide a rich toolbox for tackling the pore structure characteristics in geological barrier materials, and associated fluid flow & radionuclide transport, implicated in their long-term performance in natural and engineered systems of a nuclear waste repository.

The clear-sky and all-sky global mean energy flow system of the Earth as the solution of four radiative transfer constraint equations were presented in Zagoni (CERES STM 2020). These equations have their theoretical origin in the concept of radiative equilibrium for stratified atmospheres (Schwarzschild 1906, Eq. 11; Milne 1930, Eq. 93-95; Goody 1964, Chamberlain 1978, Eq. 1.2.29-1.2.30; Eq. 2.115; Goody and Yung 1989, Eq. 2.146 and Eq. 9.5; Houghton 2002, Eq. 2.13; Andrews 2010, Eq. 3.50-3.51; Pierrehumbert 2010, Eq. 4.44-4.45, etc.). We showed that each of the equations is justified by 19 years of CERES data within ±3 Wm-2 and the all-sky equations by the IPCC-AR5 (2013) Fig. 2.11 global energy budget estimate within ±2 Wm-2. The individual flux components, both for clear-sky and all-sky are valid within ± 1 Wm-2 at the TOA and within ± 4 Wm-2 at the surface. A fifth equation was introduced in Zagoni (EGU 2020) showing the place of a non-observable flux component (atmospheric window radiation) in the theoretical system; and a sixth equation allowed to extend the arithmetic structure to total solar irradiance. The set of these equations has a solution for LWCRE = 1 as unit flux, and the whole system of the global mean atmospheric energy flows can be described by small integers, in their own units, separately for the clear-sky, the cloudy sky and (as their weighted sum) for the all-sky case. OLR(all) = 9, OLR(clear) = 10, ULW = 15, G(all) = 6, G(clear) = 5 units = 133.40 Wm-2 with TSI = 51 units = 1360.68 Wm-2. Here we introduce the cloudy versions of the examined classic radiative transfer constraint equations and present the all-sky global mean energy budget as the weighted sum of the clear-sky and cloudy-sky energy flow system. “Clouds” are regarded as a single IR-opaque layer, represented by an effective cloud area fraction. Essential characteristics of the climate (like the clear-cloudy energy exchange; the surface, TOA, in-atmosphere and net CREs; and the greenhouse effect) are explained as the cooperation of the clear-sky and cloudy-sky geometric arrangements expressed in the transfer equations. This way, the theoretical description of the Earth’s global mean energy budget is complete.

There are growing evidences that the warming marginal seas impact the torrential rainfall events in many parts of the world. The sea surface temperature (SST) in the East Asian marginal seas (EAMS) exhibits rapid rise during the last decades compared to the global mean, but its impact is still a matter of debate. Here we assess the impact of the recent warming trend of the EAMSs on the torrential rainfall event that caused devastating flooding and landslides in Kyushu Island located in the western part of Japan in July 2017, using a high-resolution cloud permitting model. The warming trend of EAMS with atmospheric warming since 1980s increases the simulated 12-hr precipitation to 6.8%, corresponding to approximately 10% increase per 1 K of SST rise, consistent with the previous data analysis study. Slight increase in heat and moisture supplies due to the warming EAMS has impacted a conditionally unstable condition of air masses flowing into an area of the precipitation, leading to more vigorous convective systems. Moisture budget analysis indicates that the changes in the amount of precipitation is not responsible for the availability of precipitable water but the intensification of the convective system. Since the change in precipitation amount exhibits high sensitivity to the SST trends, use of multiple SST datasets is desirable to provide a more reliable estimate and its uncertainty.

While Artistic techniques may help scientists visualize data and communicate results to their colleagues, I believe the Arts can play a more significant role in communicating scientific information to the general public. Modes of presentation of information determine the impact of reception. Data on a page or screen is received cerebrally. Psychologists posit that concepts received emotionally can have a more lasting, deeper impact on an audience. That is what the arts (film, dance, drama, painting) can achieve. My paper will demonstrate through a particular project that concept. It will involve the presentation of a recent 56 foot long piece I’ve completed called “THE WORLD MAP SERIES” : https://www.dianeburko.com/new-page-1m which speaks to the impact of Climate Change on glaciers and coral reefs. This 10-part series represents my bearing witness to melting ice and coral bleaching, as well as exchanges with glaciologists and marine biologists over the past few years. It will also serve as an example of the artistic process.

Soil moisture is an essential measurement to manage water and improve crop production. However, agricultural research in the Yaqui Valley (in northwestern Mexico) with extensive wheat fields (Triticum sp.) have focused on other monitoring schemes (e.g. remote sensing) with less attention to soil moisture. Most of this cultivated soil contains up to ~ 50% clay, which results in changes to soil properties from wet to dry conditions and challenges in the implementation of in-situ measurements of soil moisture. For this research, we selected a 1-ha wheat field in the Yaqui Valley representative of a typical flood irrigation system. We measured meteorological variables (ClimaVUE™50), and soil moisture for the winter crop-cycle from December 2019 to Abril 2020. Volumetric water content (VWC) was recorded from 5 to 50 cm using two TDR (SoilVUE™10), one located in the bottom of the furrow under bare conditions, and the other on the top under the vegetated condition for further integration and comparison. A Cosmic Ray Neutron Sensor (CRNS) was located alongside the meteorological sensor. The universal calibration equation was used to estimate VWC based on neutron counts. The comparison from the CRNS and the integrated TDR (5 to 50 cm) resulted in an RMSE of 0.02 m3m-3 and an r2 = 0.73. While both technologies respond to water inputs, the CRNS is a more reliable measurement during the dry-down periods when the high-clay soil cracks to the extent of 40 cm where soil is exposed to air. During this driest period, recorded VWC at 50 cm was, on average, 0.25 m3 m-3, while measurements with the CRNS was on average, 0.16 m3 m-3. Interestingly, both sensors peaked at 0.56 m3 m-3 during the flood irrigation event.

In previous work (Hairston et al., GRL doi 10.1029/2018GL077381, 2018) we showed the topside F-layer (~850 km) electron temperatures measured by two DMSP spacecraft as they flew through the Moon’s shadow during the 21 August 2017 eclipse exhibited a series of non-uniform, banded decreases rather than a broad and smooth temperature decrease. We found that making a “mask” of the shadow of the Moon eclipsing the existing active regions on the sun’s surface created a pattern on the ionosphere showing where the gradient of the EUV from the active regions was greatest. The complex pattern of these areas from the mask at the F-peak altitude at 300 km corresponded to the areas in the topside F-layer where the DMSP observed the bands of cooled electrons. We have expanded this work to examine about a dozen other eclipses including the most recent 21 June 2020 eclipse. We repeatedly observed the same banded pattern in the electron temperatures in almost all the DMSP eclipse passes, thus demonstrating this is a repeatable phenomenon. Since the DMSP series of spacecraft form a constellation of four operational satellites with the same plasma instrument package making multiple measurements of the shadow at different local times, and sometimes within 10-15 minutes of each other, we can use these observations to map the shape and evolution of these cooling band patterns as the eclipse’s shadow passes over the Earth’s ionosphere. Here we will present our first detailed analysis of the two eclipses that occurred on 20-21 May 2012 and 2 July 2019. Both these eclipses have passes through the duskside by two spacecraft within a few minutes of each other, thus allowing us to examine the evolution of the pattern. We are using these events to determine the empirical patterns seen in the electron temperature decreases during eclipses and to explore the mechanism causing the cooling of the plasma and how it is transported from the F-peak region to the topside ionosphere.

The drivers of tree growth are one critical question in forest ecology and conservation. However, the measurement of tree growth is a difficult task that requires novel methods to improve accuracy and broaden the understanding of the effect of climate on tree metabolism and carbon accumulation. In this context, isotopes variation along woody tissues is a strong tool that provides new information about tree metabolism, growth rate, and the effect of climatic variation on these processes at high temporal resolution. Here, we obtained woody samples of two tree species two individuals per species (n = 4) from the Biogeographic Choco; Region in Colombia, one of the most humid regions of the planet without dry periods (mean annual temperature 25.9C and rainfall over 7200 mm). We measured 18O and 13C on these samples across some rings in each one to obtain intra-annual variation. Using these data, we assessed if isotopes variation in wood is correlated with climatic variation, explicitly precipitation regimen indicators employing Pearson correlation and linear mixed effect models. We found that both isotopes are correlated negatively with ring width. We also found that 18O is high negative correlated with precipitation indicators, rather than 13C. Our results suggest that isotopes variation are surrogates of tree growth in humid and non-seasonal forests. Besides, the 18O accumulation, which is strongly related to rainfall during the less rainy month (February: 370 mm on average), could be a better indicator of the effect of precipitation on the woody tissue rate change. However, 13C is more related to tissue formation processes. In conclusion, we found evidence of intra-annual variation in isotopes and tree growth in one hyper-humid forest challenging the effect of the dry season of tree growth and potentially suggesting the water excess as an additional limiting factor controlling growth rhythms in tropical trees.

Reliable, high-resolution sea ice forecasts may help contribute to safety of Indigenous marine mammal hunting and community travel in the Arctic. At the same time, sea ice forecasts could also be useful predictors of seasonal harvest success, including potential harvest shortfalls with impacts at the community level. However, large scale measures of sea ice concentration and ice extent are not sufficient indicators for predicting marine mammal harvest success in Bering Strait communities. Weekly sea ice and weather forecasts for Alaskan communities in the Bering Strait were analyzed from the Sea Ice for Walrus Outlook (SIWO) to identify sea ice and weather thresholds that greatly affected Indigenous marine mammal hunting activity and access to marine mammals during the spring harvest. The forecast of the timing for ice-free waters around a coastal community generally aligned with local observations. However some hunters continued to hunt by traveling longer distances from shore to reach marine mammals. This emphasizes the importance of maintaining coastal and marine forecasts even when coastal areas around communities appear ice-free. It was also apparent that while wind forecasts generally predicted the local wind conditions that were observed, the forecasts sometimes omitted important changes in wind direction, speed or ice movement, that occasionally resulted in ocean and ice conditions that required local search and rescue efforts or left hunters “stuck in the ice” overnight. The use of seasonal sea ice forecasts from models have not yet been explored with community partners as a potential tool to plan for upcoming subsistence hunting seasons, although the current use of SIWO is recognized as a tool to record hunter observations in “our words and descriptions” for current events and for future use and analysis. An evaluation of the Sea Ice for Walrus Outlook is being conducted, and the results of this new study will be useful to support future development of forecast information, and avenues for sharing of timely community observations.

This study explored whether the global temperature had any role in the spread and vulnerability to COVID-19 and how that knowledge can be used to arrest the fast spreading disease. It highlighted that for transmitting the virus, global temperature played an important role and a moderately cool environment was the most favourable state. Whereas, the risk from the virus was reduced significantly for warm places and countries. Based on the temperature of March and April, various degree of vulnerability was identified and countries were specified. The maximum reported case, as well as death, was noted when the temperature was in the range of around 275°K(2°C) to 290°K(17°C). Countries like the USA, UK, Italy and Spain belonged to this category. The vulnerability was moderate when the temperature was less than around 275°K(2°C) e.g., Russia, parts of Canada and a few Scandinavian countries. For temperature 300°K(27°C) and above, a significantly lesser degree of vulnerability was noted. Countries from South Asian Association for Regional Cooperation, South East Asia, the African continent and Australia fell in that category. This work discussed that based on the variability of temperature, countries can switch from one vulnerability state to another. That influence of temperature on the virus and results of previous clinical trials with similar viruses provided a useful insight that regulating the level of temperature can offer remarkable results to arrest and stop the outbreak. Based on that knowledge, some urgent and simple solutions are proposed, which are practically without side effects and very cost-effective too.

Gold mining has played a significant role in Ghana’s economy for centuries. Regulation of this industry has varied over time and while large-scale mining is prevalent in the country, prevalence of artisanal mining, or Galamsey has escalated throughout Ghana in recent years. These mines are not only harmful to human health due to the use of Mercury in the amalgamation process, but also leave a significant footprint on terrestrial ecosystems, degrading and destroying forested ecosystems in the region. This study used machine learning and Google Earth Engine to quantify the footprint of artisanal gold mines in Ghana and understand how conversion of forested regions to mining has changed from 2002-2019. We used Landsat imagery and a random forest classification to classify areas of anomalous NDVI loss during this time period and used WorldView image collections to assess the accuracy of the model. We then used a 3-year moving average to calculate the year of maximum derivative NDVI values. We used this calculation to identify the year of conversion to mining. Within the study area of Southwestern Ghana, our analysis showed that approximately 35,000 ha of vegetation were converted to mining. The majority of this mining occurred between 2014 and 2017. Additionally, around 700 ha ha of mining occurred within protected areas defined by the World Database on Protected Areas. Often, artisanal mining appears to be co-located with rivers such as the Orin and Ankobra Rivers, demonstrating the potential of these mines to affect access to clean drinking water. Through the process of gold extraction, these mines leave a distinct footprint with a series of ponds following these major rivers. However, while the footprints of these ponds are spatially distinct, our model does not distinguish between active and inactive ponds if no remediation actions are taken following inactivity. Future research should work towards distinguishing between active and inactive mining sites to better understand current levels of mining activity in Ghana.

Current machine learning based shear wave velocity (Vs) inversion using surface wave dispersion measurements utilizes synthetic dispersion curves calculated from existing 3-D velocity models as training datasets. It is shown in the previous studies that the performances of the resulting networks are dependent on the diversity of the training data. We present an improved semi-supervised deep learning algorithm-based method that incorporates both observed and synthetic surface wave dispersion curves in the network training process. The algorithm is termed Wasserstein cycle-consistent generative adversarial networks (Wcycle-GAN), which combines the architecture of cycle-consistent GAN with Wasserstein loss metrics in optimization. Different from conventional supervised deep learning approaches, the GAN architecture also extracts structural information from the observed surface wave dispersion data in the training process that may improve generalization of the resulting network. The cycle-consistent loss addresses soft constraints on the trained neural networks to be reversible and thus reduces the variance of the trained networks. The Wasserstein metric provides weaker topology for convergence and improves spatial continuity of the predicted shear velocity (Vs) models. We demonstrate these improvements by applying the Wcycle-GAN to 4066 fundamental mode Rayleigh wave phase and group dispersion curves obtained in Southern California (SC). In general, the 3-D Vs model predicted by the best training Wcycle-GAN is consistent with previous surface wave tomography studies of SC in the overlapping area, but with smaller data misfit, yields better spatial smoothing, and provides improved images of structures near faults and in the top 5 km. Our results indicate that the proposed Wcycle-GAN algorithm has strong training stability and generalization abilities.

This paper presents some pre-earthquake and coseismic water-level and stream-flow changes observed in Japan and Taiwan. The results suggest that: (1) Hydrological precursors do occur; (2) they can be observed at a relatively few sensitive sites; (3) these “sensitive” sites consistently show coseismic changes; (4) the mechanisms of these precursors can be understood, if crustal heterogeneity and pre-earthquake slow-slip events are included in their mechanism consideration. In Japan, the monitored well was sensitive, because it tapped a permeable aquifer connected to a nearby fault, which was under a hydraulic –pressure gradient caused by pumping activity in an underground gallery on the other side of the fault. Also, the fault was in a near-critical condition, such that leakage could be caused by a small crustal disturbance, such as seismic shaking, in the case of coseismic changes, or a stress increment, in the case of precursory changes. In Taiwan, both the sensitive well and the stream gauge were located on the hanging wall of the seismogenic fault of the magnitude-7.6 Chi-Chi earthquake in 1999. The hanging wall probably bulged before the earthquake, causing opening up of fractures along some secondary faults, and allowing stored groundwater to flow down to the monitored stream and caused the observed pre-earthquake stream-flow increase. The continued fracture-opening process toward greater depth then caused down-flow of water into greater depth of the crust and triggered the occurrence of slow-slip events, which propagated down-dip to where these faults met the seismogenic fault and caused slow-slip events to propagate up-dip the seismogenic fault toward the hypocenter, triggering the earthquake and the observed water-level precursor at a well located near the tip of the wall.

Light detection and ranging (LiDAR) technologies are changing the ways in which scientists research the Arctic. Unmanned aerial vehicle (UAV)-based LiDAR collects detailed structural landscape data by returning high density point clouds. LiDAR systems are improving the quality and accuracy of data collection compared to field surveys and help to remove some of the logistical barriers of research in remote and complicated terrain. Our study mapped thermokarst depressions in a 3 km2 watershed on the Seward Peninsula near Nome, Alaska in 2017 and 2018. The watershed is characterized as tussock permafrost landscape consisting of grasses and mosses interspersed with patches of dense shrubs. By configuring the UAV with a 32 laser swath and flying slowly at low altitude, we collected high density point clouds of about 4,000 points m2, including high density terrain surface points underneath dense shrubby vegetation. We then modeled the sub-vegetation terrain surface at very fine detail to detect thermokarst depressions. Combining these high resolution data with vegetation surveys and topographic properties, we tested the relationship between permafrost subsidence, thermokarst depressions and vegetation type, specifically the relationships in shrub-associated thermokarst features. By coupling our LiDAR data and analysis with hydrologic models, climate variables (e.g., snow depth, soil moisture), and vegetation surveys, we can infer geospatial relationships between thermokarst development, vegetation, and landscape position throughout the watershed. The technologies used in our study have implications for predicting the development of future thermokarst features and permafrost thaw sites across the Arctic.

The NASA Mars InSight lander carries two color cameras: The Instrument Context Camera (ICC), a wide-angle camera mounted to the lander, and the Instrument Deployment Camera (IDC), mounted to the lander robotic arm. The cameras provide both valuable information for lander and instrument operation and essential data for a range of scientific studies. In this study, we examine ICC images to investigate whether there is any shift that might be associated with lander movement. Detection of lander movement may lead to potential applications, including a possibility of inferring the background magnetic field. We focused on the data intervals where there were strong winds, many ICC images taken during the Martian day, or during seismometer deployment. Because any potential shift in ICC images is expected to be minuscule, we developed a computer program to search for the shift between images which minimizes the sum of squared differences in brightness. The preliminary results indicate that the lander, ICC, and the mount are very robust. Our image analysis method is suitable for identifying object movement in color images from both InSight cameras.

The rapid acceleration of Greenland Ice Sheet mass loss over, particularly the last two decades, is well documented.However, limits in early remote sensing restricted the details with which we could examine local changes on an ice-sheet-wide scale, particularly in areas of slow motion, along shear margins and complex coastal terrain. We explore the localcharacter of rapid contemporary change marine-terminating glaciers using satellite-derived ice sheet surface velocities,glacier terminus advance/retreat history, and surface elevation-change data from the 1980s to the present. Widespread glacierterminus retreat is a strong and more consistent climate response indicator than velocity change, but local changes in velocityare critical indicators of rapid ice sheet reconfiguration. Ice thickness changes related to changing ice dynamics often providethe first evidence of processes that initiate outlet glacier retreats and mass loss, such as the development of sub-ice shelfcavities and subglacial hydrology changes. Reconfiguration is observed locally as narrowing zones of fast-flow, ice flowrerouting, shear margin migration, and likely glacier outlet abandonment. These patterns are apparent in all ice sheet sectorsand observable from space-borne instruments. The rapid reconfiguration now well underway in Greenland has wide-rangingimplications, including expected changes in subglacial hydrology, ice discharge, freshwater flux to the ocean, and transport ofnutrients and sediment. Lacking detailed observations of earlier deglaciations and current limits on ice-sheet modelcapabilities, the expanding details of these combined observational records may provide a valuable analog for studying pastice sheet dynamics and projecting future ice loss.

Large Igneous Provinces (LIPs) are among the greatest magmatic events in Earth history withvolumes in excess of ∼500,000 km3 of predominantly basaltic lavas covering hugecontinental and ocean regions (>100,000 km2). Field observations suggest that lava flowfields in LIPs are made largely of sheet pāhoehoe lava lobes and the 10-100 m thick flows areformed by inflation. Understanding the emplacement history of these lava lobes can help usinfer the magnitude and temporal dynamics of past events.We use a phase-field model to describe solidification and re-melting of sequentially emplacedlava flows. We calibrate model parameters using field measurements at Makaopuhi lava lakeand perform extensive numerical simulations by varying the thickness of individual flow and thetime intervals between eruptions. These results help quantify the complex interplay betweenthermal evolution, flow thickness and emplacement frequency. If flows are thick enough andthe interval between emplacement short enough, reheating and re-melting may remove thetextural record of flow contacts – making flows appear thicker than they actually were. Guidedby field observations in Columbia River Basalt and Deccan Traps, we illustrate how the finalmorphology of sequentially emplaced lava is controlled by both the time scale of emplacementintervals and the time scale of cooling. We summarize our results to provide theoreticalconstraints on the thickness and emplacement intervals of individual LIP lava flows.

The Cameroon Volcanic Line (CVL) is a linear feature of volcanism that begins off the western coast of Africa with several islands and continues on shore through Cameroon further into the African continent. Equatorial Guinea’s Bioko Island is the largest and last of the CVL volcanic islands. It is home to three shield volcanoes: Pico de Basile, Pico Biao, and Gran Caldera de Luba. Eruptive history is only known for Pico de Basile which erupted within the past 100 years, and steam vents were observed as recently as 2012. There is no permanent seismic monitoring; the closest seismic stations are in Cameroon and have not reported data since 2015. The CVL is of scientific interest and has been studied by several groups. Most geophysical studies focus on the area around Mt. Cameroon, the most active volcano in the system. A network of seismic stations was installed across the entire country from 2005-2007. There has been no successful geophysical surveys of the island portion of the line. In Nov-2017 Drexel University, supported by the Bioko Biodiversity Protection Program (BBPP) and the Universidad Nacional de Guinea Ecuatorial (UNGE), installed 4 broadband seismometers on Bioko. Two stations were installed in March of 2019.Preliminary earthquake detection and location was completed with an automated STA/LTA algorithm. Initial locations use the global IASP91 model and events were relocated with a local model. Events cluster in two areas: those near Bioko Island and those near Cameroon. Between 12-Dec-2017 and 17-Feb-2018, 77 events were recorded. Local magnitudes range between 0.16and 2.61. Of these events, 49 are located near Cameroon and 28 are near Bioko. Most of the depths are upper to mid-crust. Analysis of the entire data set yields 458 events with 367 near Bioko Island and 91 near Cameroon. The range in local magnitude is -0.28 – 3.86. Our preliminary results show seismicity associated with Bioko Island as well as Cameroon. Locations match well with events recorded by the regional network previously installed in Cameroon. In addition, the rate of seismicity recorded from2017-2019 is comparable to what was observed from the Cameroon network when distance is taken into account. Data has been retrieved in Feb-2018, Nov-2018, and Mar-2019. The next service was scheduled Mar-2020 but the trip was canceled due to travel restrictions.