Causation of Late Quaternary Rapid-increase Radiocarbon Anomalies

Brief (less than 100 years) rapid-increase anomalies in the Earth's atmospheric radiocarbon production have previously been attributed to either gamma photon radiation from supernovae or to cosmic ray particle radiation from exceptionally large solar flares. Analysis of distances and ages of nearby supernovae remnants, the probable gamma emissions, the predicted Earth incident radiation, and the terrestrial radiocarbon record indicates that supernova causation may be the case. Supernovae include Type Ia white dwarf explosions, Type Ib, c, and II core collapse events, and some types of gamma burst objects. All generate significant pulses of atmospheric radiocarbon depending on distances. Surveys of supernova remnants offer a nearly complete accounting for the past 50,000 years. There are 18 events less than or at 1.4 kilo-parsec distance, and brief radiocarbon anomalies with appropriate sizes occurred for each of the closest events. In calendar years before 1950, these are: Vela, 22 per mil del 14C at 12,760; S165, 20 per mil at 7431; Vela Junior, 13 per mil at 2765; HB9, 9 per mil at 5372; Boomerang, 11 per mil at 10,255; and Cygnus Loop (per mil change not calculated) at 14,722. Although uncertainties remain large, the agreements of prediction to observation support a possible causal connection

A Mars Pathfinder landing on a recently drained ephemeral sea: Cerberus Plains, 6 deg N, 188 deg W

Along a 500 km-wide belt extending between 202 deg and 180 deg W and lying astride the martian equator, moderately low-albedo, uncratered smooth plains exhibit low thermal inertia and potentially favorable conditions for the preservation of near-surface ice. The Cerberus Plains occupy a topographic trough as much as 2 km below the planetary datum, and the denser atmosphere at these altitudes would also favor long residence times for near-surface ice once emplaced. The plains have previously been interpreted as the result of young (late Amazonian) low viscosity lava flows or similarly youthful fluvial deposition. However, the plains are also included in maps of possibly extensive martian paleoseas or paleolakes. Ice emplaced as such seas dissipated could still be preserved under thin (a few tens of centimeters) sedimentary cover. In any case, and if a sea once existed, aqueous-born interstitial cementation, probably including hydrated iron oxides and sulfate minerals, would have been favored and is now susceptible to investigation by the Pathfinder alpha proton x-ray spectrometer and multispectral imager

Monitoring water discharge and floodplain connectivity for the northern Andes utilizing satellite data: A tool for river planning and science-based decision-making

River discharge data and magnitudes of floods are often not readily available for decision makers of many developing nations, including Colombia. And this while flooding for these regions is often devastating, causing many fatalities and insurmountable damage to the most vulnerable communities. During the we season, in strong La Nina years, infrastructural damages of over $US 7.2 billion have occurred. Mitigation of such natural disasters lacks data-supported scientific approaches for evaluating river response to extreme climate events. Here, we propose a satellite-based technique to measure river discharge at selected sites for the main northern Andean River, the Magdalena. This method has the advantage of back calculating daily river discharges over a period of two decades, and thus making it possible to calculate return intervals of significant flood events. The study shows that satellite based river discharges well capture a) the inter-annual variability of river discharge; b) the natural seasonality of water discharge along the floodplains; and c) peak discharges that were observed during La Nina conditions between 2008 and 2011. The last is likely more accurate compared to ground-based gauging stations, as ground-based stations tend to overflow during large flood events and as such are hampered to accurately monitor peak discharges. Furthermore, we show that these derived discharges can form the base to study river-floodplain connectivity, providing environmental decision makers with a technique that makes it possible to better monitor river and ecosystem processes

Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: Influence of local factors

One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real time ground observations are not available. These include several international river locations in Africa: Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (Random Forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measurement sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1km; a large floodplain area and in flooded forest; with a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; Leaf Area Index > 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. The work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.JRC.H.7-Climate Risk Managemen

Floodwater Depth Estimation Tool - Coastal Version (FwDET-C)

No abstract availabl

River gauging at global scale using optical and passive microwave remote sensing

Recent discharge observations are lacking for most rivers globally. Discharge can be estimated from remotely sensed floodplain and channel inundation area, but there is currently no method that can be automatically extended to many rivers. We examined whether automated monitoring is feasible by statistically relating inundation estimates from moderate to coarse (>0.05°) resolution remote sensing to monthly station discharge records. Inundation extents were derived from optical MODIS data and passive microwave sensors, and compared to monthly discharge records from over 8000 gauging stations and satellite altimetry observations for 442 reaches of large rivers. An automated statistical method selected grid cells to construct “satellite gauging reaches” (SGRs). MODIS SGRs were generally more accurate than passive microwave SGRs, but there were complementary strengths. The rivers widely varied in size, regime, and morphology. As expected performance was low (R  0.6. The best results (R > 0.9) were obtained for large unregulated lowland rivers, particularly in tropical and boreal regions. Relatively poor results were obtained in arid regions, where flow pulses are few and recede rapidly, and in temperate regions, where many rivers are modified and contained. Provided discharge variations produce clear changes in inundated area and gauge records are available for part of the satellite record, SGRs can retrieve monthly river discharge values back to around 1998 and up to present

On the use of global flood forecasts and satellite-derived inundation maps for flood monitoring in data-sparse regions

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response decisions. Global-scale flood forecasting and satellite-based flood detection systems are currently operating, however their reliability for decision making applications needs to be assessed. In this study, we performed comparative evaluations of several operational global flood forecasting and flood detection systems, using 10 major flood events recorded over 2012-2014. Specifically, we evaluated the spatial extent and temporal characteristics of flood detections from the Global Flood Detection System (GFDS) and the Global Flood Awareness System (GloFAS). Furthermore, we compared the GFDS flood maps with those from NASA’s two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results reveal that: 1) general agreement was found between the GFDS and MODIS flood detection systems, 2) large differences exist in the spatio-temporal characteristics of the GFDS detections and GloFAS forecasts, and 3) the quantitative validation of global flood disasters in data-sparse regions is highly challenging. Overall, the satellite remote sensing provides useful near real-time flood information that can be useful for risk management. We highlight the known limitations of global flood detection and forecasting systems, and propose ways forward to improve the reliability of large scale flood monitoring tools.JRC.H.7-Climate Risk Managemen

Earth observations into action: the systemic integration of earth observation applications into national risk reduction decision structures

Purpose - As stated in the United Nations Global Assessment Report 2022 Concept Note, decision-makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible and easy to use. The purpose of this paper is to demonstrate scalable and replicable methods to advance and integrate the use of earth observation (EO), specifically ongoing efforts within the Group on Earth Observations (GEO) Work Programme and the Committee on Earth Observation Satellites (CEOS) Work Plan, to support risk-informed decision-making, based on documented national and subnational needs and requirements. Design/methodology/approach - Promotion of open data sharing and geospatial technology solutions at national and subnational scales encourages the accelerated implementation of successful EO applications. These solutions may also be linked to specific Sendai Framework for Disaster Risk Reduction (DRR) 2015–2030 Global Targets that provide trusted answers to risk-oriented decision frameworks, as well as critical synergies between the Sendai Framework and the 2030 Agenda for Sustainable Development. This paper provides examples of these efforts in the form of platforms and knowledge hubs that leverage latest developments in analysis ready data and support evidence-based DRR measures. Findings - The climate crisis is forcing countries to face unprecedented frequency and severity of disasters. At the same time, there are growing demands to respond to policy at the national and international level. EOs offer insights and intelligence for evidence-based policy development and decision-making to support key aspects of the Sendai Framework. The GEO DRR Working Group and CEOS Working Group Disasters are ideally placed to help national government agencies, particularly national Sendai focal points to learn more about EOs and understand their role in supporting DRR. Originality/value - The unique perspective of EOs provide unrealized value to decision-makers addressing DRR. This paper highlights tangible methods and practices that leverage free and open source EO insights that can benefit all DRR practitioners

A global network for operational flood risk reduction

Every year riverine flooding affects millions of people in developing countries, due to the large population exposure in the floodplains and the lack of adequate flood protection measures. Preparedness and monitoring are effective ways to reduce flood risk. State-of-the-art technologies relying on satellite remote sensing as well as numerical hydrological and weather predictions can detect and monitor severe flood events at a global scale. This paper describes the emerging role of the Global Flood Partnership (GFP), a global network of scientists, users, private and public organizations active in global flood risk management. Currently, a number of GFP member institutes regularly share results from their experimental products, developed to predict and monitor where and when flooding is taking place in near real-time. GFP flood products have already been used on several occasions by national environmental agencies and humanitarian organizations to support emergency operations and to reduce the overall socio-economic impacts of disasters. This paper describes a range of global flood products developed by GFP partners, and how these provide complementary information to support and improve current global flood risk management for large scale catastrophes. We also discuss existing challenges and ways forward to turn current experimental products into an integrated flood risk management platform to improve rapid access to flood information and increase resilience to flood events at global scale