Water supply reliability in the Truckee River basin stands to substantially benefit from forecast-informed reservoir operations(FIRO), especially given expected increases in rain: snow ratios and a transition to earlier runoff under warming climate that current infrastructure and operational rules were not designed for. However, in its position on the lee side of the Sierra Nevada mountains (CA/NV, USA), several unique forecast uncertainties exist that must be considered to mitigate against increased flood risk potential. Both water supply and floods are strongly linked to wintertime atmospheric rivers (AR) but despite improvements in forecasting these events at long lead times, the timing and amount of spillover precipitation onto the lee side remains a key uncertainty. In addition, storm runoff volumes in this basin are highly sensitive to rain-snow elevation, which is also difficult to forecast. Finally, antecedent snowpack and soil conditions have the potential to modulate runoff volumes but factors controlling the strength of these modulations are incompletely understood and monitored. In this study, we assess streamflow forecast skill in the Truckee River to provide a preliminary understanding of potential forecast-related challenges and opportunities for FIRO. To accomplish this, we used an archive of readily available short-range Hydrologic Ensemble Forecast System winter (Oct-Apr) streamflow forecasts for water years 2015-2020 and compared these to observed3-day flows at lead times of 0 to 15 days. We subset the data into AR days, non-AR days and top 10% flow days examined the variance explained between the ensemble median and observed 3-day flows as a function of lead time. We also examined how the observed 3-day flows rank in relation to the ensemble members for each day. We found that forecast accuracy improves considerably starting at a 7-day lead time but tends to be lower for high-flow and AR events relative to non-ARs. We also found the ensembles to have a slight bias toward underprediction and tendency toward under-dispersion (i.e. observed flows were sometimes outside the ensemble range) with this being the case for AR and high flow days for some but not all sites.

Understanding the effect of different landscapes on local temperature is important for understanding land-atmospheric interactions, and is a critical step toward an informed urban design under a changing climate. This presentation considers Lake Memphremagog, a transboundary water body between Quebec and Vermont, along with one of its adjacent wetlands as a test bed to study the impact of different water bodies on regulating the local temperature. We use the data from two identical climate stations to study hourly temperature, absolute and relative humidity as well as incoming and outgoing radiation components along with vapour pressure deficit at the lake and wetland. We benchmark the temperature measurements in these two sites with the data gauged in an Environment and Climate Change Canada’s weather station located between the two sites. Using a systematic analysis, we account for the cooling and heating impacts of the lake and the wetland and demonstrate their underlying causes. We show that during the growing season and at the daily scale, the cooling impacts of the wetland can cancel out the heating impacts of the lake. This is not the case during day times, in which the lake acts as a sink of heat, while the wetland is the source. We show that the cooling and heating effects of the considered lake-wetland duo can be described by the daily temperature statistics (i.e. average, minimum, maximum and range) at the benchmark weather station. This provides an opportunity to create stochastic models for retrospective and prospective projections of cooling and heating impacts of this lake-wetland duo under current and future climate.

Traditional watershed modeling often overlooks the role of vegetation dynamics. While past studies indicate possible improved hydrologic predictions by increasing the physical realism of vegetation dynamics in process-based models, there has been little quantitative evidence to support similar improvements in water quality predictions. To fill this knowledge-gap, we recently applied a modified Soil and Water Assessment Tool (SWAT) to quantify the extent of improvements that the assimilation of remotely sensed Leaf Area Index (LAI) would convey to streamflow, soil moisture, and nitrate load simulations across a 16,860 km2 agricultural watershed in the midwestern United States. We modified the SWAT source code to directly insert spatially distributed and temporally continuous LAI estimates from Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to a “basic” traditional model with limited spatial information, our LAI assimilation model (i) significantly improved daily streamflow simulations during medium-to-low flow conditions, (ii) provided realistic spatial distributions of growing season soil moisture, and (iii) substantially reproduced the long-term observed variability of daily nitrate loads. Further analysis revealed that assimilation of MODIS LAI data corrected the model’s LAI overestimation tendency, which led to a proportionally increased rootzone soil moisture and decreased plant nitrogen uptake. With these new findings, our study confirms that assimilation of MODIS LAI data in watershed models can effectively improve both hydrology and water quality predictions.

Abnormally heavy precipitation events can lead to numerous hazards, including flooding, landslides, and avalanches. Their developments require a sufficient supply of moisture and some physical mechanism to produce condensation. Atmospheric rivers (ARs) defined as long and narrow corridors of strong horizontal moisture transport can provide such necessary conditions. The presence and strength of ARs are often described using the integrated water vapor (IWV) and the integrated vapor transport (IVT). However, the associated precipitation is not directly correlated with these two variables. It is the net convergence of moisture that determines the intensity of precipitation. The purpose of this study is to illustrate, in the context of AR analysis, how the converged vapor should be distributed between condensation and air moistening. A simple algorithm is proposed for estimating the heavy precipitation attributable to the IVT convergence. Bearing a strong resemblance to the Kuo-Anthes parameterization scheme for cumulus convection, the proposed algorithm calculates the large-scale primary condensation rate (PCR) as a proportion of the IVT convergence, with a reduction to account for the general moistening in the atmosphere. The amount of reduction is determined by the column relative humidity (CRH), which is defined as the ratio of IWV to its saturation counterpart. It is found that the PCR in an air column with CRH < 0.60 is negligibly small. Based on a one-year dataset from the Canadian global numerical weather prediction (NWP) model, the best cut-off value of CRH for the algorithm is 0.66. It is demonstrated that this diagnosable PCR compares well to the forecast precipitation rate given by the NWP model. Case studies are conducted to illustrate the usefulness of CRH and PCR as two complements to standard AR analysis and impact-based storm classification.

According to the 2020 FEMA Fact Sheet (FEMA, 2020), Puerto Rico and Virgin Islands are located in a high risk region for earthquake damage. In the last year (05-jul-2019 to 05-jul 2020) the Puerto Rico Seismic Network (PRSN) recorded 136 earthquakes with magnitudes greater than 4.0 and two events had magnitudes greater than or equal to 6.0. The last update of the seismic hazard maps for Puerto Rico and the US Virgin Islands was performed in 2003. According to Mueller et al. (2010), the Bunce fault, the Muertos Trough and related fault structures were not included in the hazard map. The Great Southern Puerto Rico fault, was considered largely quiescent, but Piety et al. (2008) through paleoseismic studies, evidenced activity in this one. Otherwise, offshore faults in southern Puerto Rico were not considered, because their rates of activity were poorly known and assumed to be most likely small. However, starting in December 2019 the Southwestern Puerto Rico (SWPR) Seismic Sequence has been active and continues to be active in these southern offshore faults. According to the StEER technical report (Miranda et al., 2020), the events that occurred between December 2019 and January 2020 caused damage to approximately 10,000 structures and more than 8,000 people were displaced. Based on these facts, and considering that previously unknown tectonic fault structures have been revealed by the SWPR Seismic Sequence (Lopez et al., 2020b), a reevaluation of the seismic threat to Puerto Rico is required. This should include the seismic activity that, according to the PRSN catalog, consists of more than 50,000 events since 2002 to date. This new seismic hazard evaluation will include multiple earthquakes with magnitudes greater than M 5 which were not part of the catalog in 2001. The purpose of this study is generating a new Ground Motion Prediction Equation (GMPE) that incorporates the current seismicity for the region, which unlike the local model used in Mueller et al. (2010) the data will be used directly to obtain the ground motion relationships (Motazedian et al., 2005). This new data now permits to obtain a GMPE from a regression analysis. In the first stage of the research, the aim is generating a preliminary GMPE based on crustal seismicity (events less than 25 km deep) which represents more than 60% of the total registered earthquakes in the PRSN catalog.

The research data repository of the Environmental Data Initiative (EDI) is a signatory of the FAIR Data Principles. Building on over 30 years of data curation research and experience in the NSF-funded US Long-Term Ecological Research program (LTER), it provides mature functionalities, well established workflows, and support for ‘long-tail’ environmental data publication. High quality scientific metadata are enforced through automatic checks against community developed rules and the Ecological Metadata Language (EML) standard. Although the EDI repository is far along the continuum of making its data FAIR, representatives from EDI and the LTER Information Management community have recently been developing best practices for the edge cases in environmental data publishing. Here we discuss and seek feedback on how to best handle the publication of these ‘long-tail’ data when extensive additional data are available along with e.g., genomics data, physical specimens, or flux tower data. While these latter data are better handled in other discipline-specific repositories such as NCBI, iDigBio, and AmeriFlux, they are frequently associated with other data collected at the same time and location, or even from the same samples. This is particularly relevant across the LTER Network, where sites represent integrative research projects. Questions we address (and seek community input from) include: How to archive documents and images when they are data, e.g., field notebooks, or time-lapse photographs of plant phenology? How to deal with data from Unmanned Vehicle (e.g., drones and underwater gliders), acoustic data, or model outputs, which may be several terabytes in size? How should processing scripts or modeling code be associated with data? Overall, these best practices address issues of Findability and Accessibility of data as well as greater transparency of the research process.

Underwater bedforms in a flow have been shown to cast free-surface signatures that carry important information about these bedforms thus allowing for a novel non-intrusive methodology for bedform inference through measurement of these signatures (Gakhar et al. 2020, J. Fluid Mech. vol.900, A41). We present a method (Polarimetric Height Sensing or PHS) for spatiotemporally reconstructing the two-dimensional height field of a (water) free surface, thereby allowing for characterization of the free-surface signatures of submerged bedforms. The instrumentation for PHS comprises a small, easily portable polarimetric camera. PHS, which incorporates more than just the intensity of the light as in a regular digital image, works as follows. When light is reflected from the water surface, it acquires a polarization that depends on the polarization state of the incident beam, the indices of refraction of the surface and air, and most importantly the angle and plane of incidence. Given that we already know the refractive indices and the incident light’s polarization, using measurements of the polarization of the reflected light, we can quantify the geometric properties of the water surface. We illustrate the technique via laboratory experiments using imaging of the water in an open-channel recirculating water flume.

Emergency Action Plan for Flash Flood Due to Dambreak - Case study: Shahrchai Dam, Urmia (Iran) Seyed M. Heidaria, Seyed Jalal Heidarib a Department of Civil Engineering, Sharif University of Technology, Tehran, Iran. ([email protected]) b Department of Civil Engineering, Betasaze Corporation, Mashhad, Iran. ([email protected]) Abstract: A large number of dams have been built on the upstream of residential regions. Flash flood from these dams’ failure is a constant threat to the thousands of lives and million-dollar municipal facilities in downstream. Therefore, it is crucial to identify potentially flooded areas and develop an early warning system for downstream cities to mitigate the loss of life and financial damages. We prepared an emergency action plan (EAP) for flash floods in Iran for the first time in this work. Shahrchai Dam was selected as the case study since it is a large dam with a 220 million m2 capacity reservoir and is located close to a large city, Urmia, with 667,000 population and more than 197,000 households. We used HEC-RAS to model dambreak for two scenarios, piping and overtopping. ArcGIS was employed to identify flooded regions in downstream. The escape time was estimated based on the time that first waves reach residential zones. Time was 170 and 140 minutes for the piping and overtopping scenario, respectively. Water depth and water velocity were mapped for each scenario for flooded areas in downstream to identify secure shelters. EAP was developed for residential, commercial, and municipal buildings located in the flooded areas. Nine hospitals, four hotels, six mosques, more than ten municipal buildings, 54 public, and private schools, and five universities are determined within the flooded regions and considered in the EAP. We divided these regions into five categories, with three to five subcategories based on population and building types. For each subcategory, we identified an evacuation plan with detailed guidelines for residents and involved municipal organizations to avoid chaotic behaviors, which usually happens during flash floods. Results from this study are useful for educating people to be prepared for disasters like flash floods. Municipal policymakers can also use the findings to legislate required rules to protect urban areas from future floods and reduce associated fatality and financial costs. Acknowledgment: Authors would like to appreciate Sharif University of Technology and Dr. Fardin Jafarzadeh for their supports.

Gas transport in dominantly microporous rocks such as coal, shale is significantly controlled by Klinkenberg or slippage effect at low reservoir pressures. Pore size fractions of the concerned reservoir rock control the degree of Klingenberg effect. This study tries to assess the differences in Klinkenberg effect in dissimilar coals owing to their difference in pore-size distributions. We report apparent permeabilities of three Gondowana coal samples from the Bokaro, Jharia, and Bansgara coalfields at room temperature and constant isostatic stress (6.2 MPa). The linear plots of apparent permeability versus inverse pore pressure were modelled using the Klinkenberg equation, and non-linear plots by the Ashrafi equation to determine the slippage coefficient and intrinsic permeabilities. Ashrafi model reports lower values of slippage corrected permeability compared to the Klinkenberg model. The slippage coefficient and intrinsic permeability obtained from N2 and CO2 is different for the Bansgara sample. The trends between transport parameters and pore-size parameters were examined. The slippage coefficient decreased with interconnected porosity and total specific pore volume. Intrinsic permeabilities showed an opposite trend to that of the slippage coefficient. The Bansgara sample having larger volumetric proportion of micropores in the pore volume gamut with open ended interconnected pore network resulted in the lowest slippage coefficient and highest intrinsic permeabiliity. Reporting the slippage coefficients and intrinsic permeabilities with corresponding pore size distributions of coal samples from different global basins will lead to statistically significant empirical relationships between pore size parameters and slippage coefficients.

Geologic carbon storage (GCS) is part of a process known as carbon capture, utilization, and storage (CCUS); being adopted to mollify extreme weather events (global warming) as a result of CO2 emissions and improve energy production. Previous studies have shown promising potentials of permanent CO2 storage in depleted shale reservoirs. In this study, we experimentally and analytically investigate the impact of microbially-altered mechanical properties on carbon storage in the Niobrara shale reservoir, using a cultured solution and shale samples from Niobrara formation. Firstly, we obtained the properties of the untreated samples. Secondly, we treated and cultivated the samples with the cultured solution at specific conditions. Further, we obtained the new properties of the treated shale rocks. Lastly, we show the impact of the altered properties on CO2 storage integrity in unconventional shale reservoirs. Our results suggest that in shale reservoirs, biogeomechanical alterations can enhance the long-term integrity of geological sequestration of atmospheric CO2, by mitigating any deep subsurface potential leakage to the atmosphere.

Traditional crop irrigation relies on farmers’ knowledge on plant, soil, and weather. Irrigation system is one of the key facilities in Nebraska to supply sufficient water resource to farming activities. However, in large scale farming, it is not rare to see plant get over irrigated while the marginal economic benefit of irrigation decreases significantly. The WaterSmart system combines various data sources to provide irrigation guidance to help farmers making better irrigation decision. To support the WaterSmart system, a semantic irrigation ontology is developed to understand these Agro-Geoinformatics data with local planting knowledge such as water usage during different crop stages. Local knowledge on crop irrigation has already been studied and published by Institute of Agriculture and Natural Resources, Nebraska Extension at the University of Nebraska-Lincoln. The ontology is built using Webprotégé with using HermiT as the reasoner. The ontology focuses on two main crops in Nebraska: corn and soybean. Final product is released on GitHub repository and registered with w3id thru persistent uniform resource locator (PURL). All software and tools were used to develop the ontology are open source. The ontology is used to represent irrigation knowledge and host concepts in the irrigation decision making portal.

Purpose:Flooding following heavy rains precipitated by hurricanes/tropical storms has previously been shown to increase fecal-oral diseases, vector-borne disease transmission and pregnancy complications during or following inundation. Remote sensing can be used to spatio-temporally resolve inundation extents for subsequent analysis of risks associated with flooding at a finer scale. Here we combined earth observations of the flooding caused by Hurricane Harvey in 2017 with Emergency Department (ED) visit data to evaluate health outcomes associated with flooding.Methods:Our study area included 1073 flooded and 1809 non-flooded census tracts in Texas which were categorized using the inundation maps from Dartmouth Flood Observatory. These maps were created using Sentinel and MODIS satellite imagery captured between 28th Aug - 4th Sep 2017 following the landfall of the hurricane. ED visits in the study area were obtained from Texas Department of State Health Services. A controlled interrupted time series design was employed using ED visits from non-flooded tracts as the control series and ED visits before a week of the landfall and through 2018 as control period. Poisson regression using generalized estimating equation with census tracts as the group variable was used to estimate the relative risk of the health outcomes associated with flooding during and following the flooded days, adjusting for the age, ethnicity, race, sex of the patient, day of week, month and year trends. Results:Flooding was associated with a 35% (95% CI: 22%-48%) increase in risk for insect stings and 24% (17%-31%) increase in risk of pregnancy complications during the flood period. Similarly, relative risks were also elevated (>1) for drowning, hypothermia, and intestinal infectious diseases in the flooded tracts. Also, in the months following the flood period, the relative risk was still elevated (>1) for pregnancy complications and insect stings while asthma and acute respiratory infections showed decreased risks. Conclusion: Earth observations have helped in understanding the health risks that are related to flooding. These earth observations can in turn be used to identify specific communities with increased health risks during and following flooding events.

The rivers in the Peruvian Amazon basin are the veins that feed the largest rainforest on the planet. They connect habitats and ecosystems and are considered a source of high biodiversity. Since before the conquest, many indigenous peoples have settled along riverbanks to be supplied with water, food, and many other ecosystem services. Furthermore, the Amazonian rivers have been the basis for the sociability of those population groups. For many years, the indigenous riverine people, such as the Kukama and the Shipibo-Conibo, have developed an empirical knowledge about the rivers from their coexistence and lifestyle. Therefore, indigenous communities have learned how to be adapted under the physical dynamics by shaping their culture. It evidenced the great understanding of rivers that communities developed over the years, endowed with affective and spiritual links, which has allowed them to be preserved for many years. As part of a scientific study of the hydrogeomorphological characteristics of the main Peruvian Amazonian rivers, it was considered important to involve indigenous perceptions and knowledge. Recognizing these views is necessary for a holistic understanding of rivers; however, these have been absent from the plans and projects developed by government institutions. “River Stories” (https://www.historiasdelrio.com) is a digital storytelling platform that supports the dissemination of indigenous cosmovision in terms of experiences, in which the knowledge, memory and spirituality are displayed. It hosts more than 100 stories from indigenous people (including children and teenagers), students, local authorities, and scientists that reveal the importance of rivers in their daily life. In this way, different perspectives of the rivers from science, civil society, and the indigenous worldview are exchanged. Integrating this knowledge is essential to highlight the vital role that rivers play at the social, cultural and environmental areas. This, especially in the current context, where multiple threats, such as infrastructure and energy projects, put Amazonian rivers at risk.

High-resolution viscous-plastic (VP) sea ice models reproduce the narrow deformations lines observed in the Arctic sea ice, called the Linear Kinematic Features (LKFs). Recent studies showed that standard VP models overestimate the intersection angles between the LKFs when compared to observations. We investigate fracture angles in a uniaxial compression test and two different VP rheology. The first one uses an elliptical yield curve and a normal flow rule. In contrast, the second rheology uses a different elliptical plastic potential that creates a non-normal flow rule. Results show that the non-normality of the flow rule changes the angles of fracture. This new rheology can create fracture angles as low as 22º when the rheology with normal flow rule is limited to angles above 30º. A newly adapted theory – based on one developed from granular material observations – predicts the modeled fracture angles accurately. Using a non-normal flow rule takes longer to solve numerically, but allow reductions of the fracture angle to values within the range of satellite observations and decouples the angle of fracture from the shape of the yield curve.

Bedrock weathering and soil production set the rate that hillslope colluvium is produced, while material properties determine whether sediment can fail under a given set of conditions. Together these factors generally control both the frequency and magnitude of landslides. In 2017, Puerto Rico (USA) experienced widespread landsliding across a range of lithologies due to Hurricane Maria, making it an ideal setting to explore the role of sediment generation in landslide response to storms. Based on an inventory of >70,000 landslides island-wide and detailed field mapping from a subset of source areas, we estimate that 0.01-0.1 km3 of material was evacuated from the hillslopes (approximately 1-10 mm of lowering). Focusing on the high-density landslide area of Utuado, we estimate an average lowering of 5-50 mm. From past inventories and records of storm events, a watershed is impacted by a hurricane every ~25 years with enough rain for widespread landslides every ~5 years. Assuming a similar density, the landslide contribution to hillslope lowering could be on the order of 1-10 mm/yr. In a humid-tropical environment, where weathering rates are likely high, can hillslopes continue to produce material at this pace? Elsewhere on the island, soil production rates are on the order of 0.1 mm/yr leading to soil residence times of approximately 10 ky. However, to keep pace with landslide events like Hurricane Maria, soil production likely needs to be at least an order of magnitude faster to maintain soil-mantled hillslopes in this study area. For our study area, we ask: has the large-magnitude rainfall from Hurricane Maria caused an abnormally high density of landsliding, resetting the clock on the material availability for areas like Utuado? Here we relate measures of material properties, bedrock weathering intensity, denudation, and land-use history to begin answering this question.

Bottomland hardwood forests are a historically dominant ecosystem in the Southeastern United States, with 5.3 million-acres remaining in the Lower Mississippi Alluvial Valley. Despite the importance of forested wetlands in the global carbon cycle, not much is known about CO2 exchanges in such periodically flooded ecosystems. To address this, CO2 fluxes were measured over a mature, predominantly oak bottomland hardwood forest canopy in Northeast Louisiana. Measurements were carried out from a 37m tower, between August 2013 to October 2018, using the eddy covariance technique. Like other deciduous broadleaf forests, the site exhibited distinct diurnal and seasonal variability and was a net carbon sink during the spring and summer months, but unlike the majority of such forests and inland wetlands, the site was a net source of carbon annually. The cumulative annual net ecosystem exchange (NEE) ranged from 95.99 g C m-2 in 2014, to 267.91 g C m-2 in 2017, with an average annual NEE of 127.75 g C m-2. To better understand the variability, the relationship between the environmental factors and the components of NEE were observed. Diurnally, GPP increased with increasing global radiation and exceeded Reco from around 830 till around 1800 hrs. Seasonally, nighttime Reco increased with temperature. GPP increased and exceeded Reco from late March to early August, with a corresponding increase in the length of daylight, temperature, and leaf area index. GPP values showed more variability than Reco on a daily scale, thereby having a more distinct effect on the NEE. Research is on-going to better understand the effects of the characteristic flooding on carbon fluxes in this unique ecosystem.

During the global COVID-19 pandemic, anthropogenic emissions of air pollutants and greenhouse gases, especially traffic emissions in urban areas, have declined significantly. Long-term measurements of trace gas concentrations in urban areas can be used to quantify the impact of emission reductions on local air quality. Open-path Fourier transform infrared (OP-FTIR) spectroscopy is a non-intrusive technique that can be used to simultaneously measure multiple atmospheric trace gases in the boundary layer. This study investigates the reduction of surface CO, CO2 , and CH4 mole fractions during the lockdown in downtown Toronto, Canada, which is the fourth largest city in North America. The mean daily CO mole fraction anomaly (ΔCO) for the period from March 14 to May 18, 2020 declined by 46 ± 16% compared to the period before lockdown from January 13 to March 13, 2020. The mean daily ΔCO during the lockdown also declined relative to the same period in previous years: by 50 ± 20% relative to 2019 and by 44 ± 25% relative to 2018. Changes in the diurnal variations of CO, CO2 and CH4 during the lockdown are also investigated and compared to 2019 and 2018. Both CO and CO2 show early morning maxima on weekdays corresponding to rush hour. The change of the amplitude of the diurnal variation in CO during the lockdown is significant, compared to the period before lockdown. The differences in the diurnal variation in CO during the same two periods in 2019 and 2018 are not significant. Ratios of CO/CO2 anomalies show seasonal variations, which are also likely due to seasonal changes of emissions from local sources. These results show that the COVID-19 lockdown in Toronto modified surface mole fractions, diurnal variations, and ratios of air pollutants monitored by OP-FTIR. In addition, measured CO mole fractions are compared with simulated CO mole fractions by WRF-STILT to assess the relationship between atmospheric measurements and urban emissions from Toronto.

The Noerdlinger Ries is regarded as one of the best studied terrestrial impact craters. Because of its accessibility and its excellent preservation this area continues to be a research target for numerous international students, geoscientists and impact researchers. Here astronauts from the Apollo 14 and 17 missions studied the identification and sampling of impact rocks to prepare for their trip to the Moon. Today it is a regular training area for ESA astronauts and project planners. As an ‘In-crater museum’, the Ries Crater Museum offers insights into the spectacular event 15 million years ago. It illuminates the significance and the larger context of the Ries event to a wider audience: our Solar System, comets, asteroids, meteorites, and the special role of impacts in the evolution of our Solar System and Earth. Permanent didactic challenges in this context are: Most of the relevant processes cannot be observed directly. The time scale considered is very large and very different from that of a human being. Large impact-events took place long ago (Millions and billions of years ago) and were/are very rare events by human standards. Also, only remains of large and relatively new impacts are preserved and visible to some extent. All this often leads to the conclusion that impact processes are part of the past without actual relevance except at the cinema. In reality objects from space hit Earth every day, every hour, every minute, every second. But since they are usually very small, their fall is rarely spectacular and usually not noticed. We are currently working on the renewal of the meteorite area in our museum. In this context we plan to draw visitors’ attention to recent fall events and to show their special importance for science and society. To demonstrate the ongoing bombardment of the earth we present online or ‘near online’ observations to make visible the usually invisible to the ‘normal’ eye. We try to overcome the restrictions of timescale and take a sharp look into the present by reducing time slots and using a ‘magnifying glass’. We present concepts and approaches. Suggestions and comments are welcome!