This open science meeting is triggered by the recent closure of an ESA activity (funded by its General Studies Programme - GSP) called "Next advances in the synergistic use of high-resolution numerical atmosphere models with spaceborne systems" that was renamed to STEAM by the consortium led by CIMA Research Foundation. At the same time, the Agency has started the deliberations on the Earth Explorer 10 candidate missions, one of which - i.e. G-CLASS/Hydroterra - has the primary science objective that is closely linked to the work performed within STEAM.
The Open Science Meeting is therefore an opportunity to exchange ideas between various groups working on one of the main science objective of G-CLASS/Hydroterra, i.e. targeting the observation of the key processes of the daily water cycle to improve prediction capability of intense rainfall and related flooding and landslides, to improve the understanding of the diurnal water cycle and to enable the near real time prediction of ground motion.
The Open Science Meeting will cover the following topics:
The preliminary agenda and timetable for the event is shown below hereto. In case you wish to attend, please complete the registration form.
Link: How to get to ESTEC?
Information regarding hotels and transportation can be found in the attachment.
A. Parodi, CIMA Research Foundation
M. Lagasio, L. Pulvirenti, A. N. Meroni, G. Boni, N. Pierdicca, F. S. Marzano, L. Luini, G. Venuti, E. Realini, A. Gatti, G. Tagliaferro, S. Barindelli, A. Monti Guarnieri, K. Goga, O. Terzo, A. Rucci, E. Passera, and B. Rommen
The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several millions euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. NumericalWeather Prediction (NWP) models are currently able to produce forecasts at the km scale spatial resolution, but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn
11 2017 are studied: a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.
A. M. Marziani1;2, M. Biscarini1, F. Consalvi3, G. Fusco2, C. Riva4, L. Luini4, A. Parodi5,
L. Pulvirenti5, M. Lagasio5, N. Pierdicca1 and F. S. Marzano1
1 DIET, Sapienza University of Rome, Italy
2 Istituto Superiore C.T.I., Ministero dello Sviluppo Economico, Italy
3 Fondazione Ugo Bordoni, Italy
4 DEIB, Politecnico di Milano, Italy
5 CIMA Foundation, Italy
Due to the increasing demand of large bandwidths and high bit rates for mobile and fi?xed applications, microwave and millimeter-wave frequencies are more and more investigated for radiocommunication purposes. Nevertheless, these high frequencies are prone to strong propagation impairments due to atmospheric particles and turbulence in the troposphere. Clear-air effects relate are mainly due to atmospheric turbulence and induce tropospheric amplitude and phase scintillation. Path attenuation due to cloud, rain and ice particles introduce an extinction of the beacon signal, mainly depending on the hydrometeor water content and size. For a satellite-to-Earth communications the state of the channel and its link budget is deeply connected to the overall status of the atmosphere. Within the ESA-STEAM project the use of high-resolution numerical weather prediction (NWP) model outputs have been coupled with microphysically-oriented radiopropagation models of slant-path microwave and millimeter-wave links. Both GFS and IFS global-scale initializations have been used to nest WRF-LAM models at 1.5 km and WRF-LES model at 0.5 km spatial resolution with and without data assimilation capability. The overall goal has been to indirectly test high-resolution NWP models in different configurations by using AlphaSat satellite "Aldo Paraboni" payload data for two case studies over Italy, measured in Milan and Rome by two receiving stations at Ka and Q band. Nearby RAOB stations have been also used to perform some further comparisons in clear air. Results show that high-resolution modeling can be suitable to grasp the the spatial variability of turbulence and convection, even though the "double-penalty" error may affect the intercomparison between the satellite-beacon point measurements and NWP-based radiopropagation simulations.
The water cycle is fundamental to human society and to life on Earth. Despite its importance, there are still aspects which are poorly understood and for which we only have limited measurements. It is increasingly recognised that improved temporal sampling is needed for future space missions, so that processes on timescales of minutes to hours can be observed directly. From space, this could be achieved using a large constellation of satellites in conventional low orbits, or a few satellites in geosynchronous orbit (GEO). A single GEO satellite can view Europe and Africa continuously, and is the concept for the G-CLASS proposal. Of the imaging bands available, microwave imagers (radar) are particularly good for water both at the surface (radar backscatter measurements) and in the atmosphere (using radar interferometry), and can provide all-weather imaging 24 hours per day. Using synthetic aperture radar it is possible to achieve resolution as good as 20 m from GEO. To improve understanding of the diurnal water cycle and related societal concerns such as floods, landslides and water resources, we therefore propose a GEO synthetic aperture radar mission: G-CLASS.
Specific water cycle science objectives for the mission are:
As weather prediction capability improves we need commensurate high resolution observations (in space and time) to initialise and validate the predictions. A GEO radar with its continuous viewing capability can potentially provide these. Diurnal forcing of soil moisture and snow state through the day are important for hydrology, and affect water resource management and agriculture. The radar measurements also enable general ground motion to be monitored, thus enabling a third science objective at no extra cost to the mission:
The baseline mission concept uses a Vega-C launch followed by an orbit-raising phase to reach GEO. A standard small-GEO satellite (mass around 2 tonne, few kW electrical power) is suitable, with a C-band radar (300-400 W RF), compact polarimetry and a 7 m diameter deployable reflector. Beam-steering is achieved by slewing the satellite: the whole Earth disk is only 16° across so small manoeuvres are used and require no propellant. Coverage is controlled by pointing and is therefore almost independent of the orbit.
G-CLASS will be the first mission to provide continuous observations of key diurnal processes. It will simultaneously observe the land surface and overlying atmosphere, and powerfully complements existing EO missions. The temporal resolution opens up significant new opportunities – only some of which we can currently predict. G-CLASS has great potential for new science, especially of the diurnal water cycle, and enables applications with important societal impact.
N. Pierdicca, University of Roma La Sapienza
I. Maiello, E. Sansosti, , G. Venuti, S. Barindelli, R. Ferretti, A. Gatti, M. Manzo, A. Monti Guarnieri, F. Murgia, E. Realini, S. Verde
A Synthetic Aperture Radar can offer not only an accurate monitoring of the earth surface deformation, but also information on the troposphere, such as the total path delay or columnar water vapor at high horizontal resolution. This can be achieved by a proper interferometric processing and post-processing of the radar interferograms. The fine and unprecedent horizontal resolution of the troposphere products can offer otherwise unattainable information to be assimilated into Numerical Weather Prediction models, which are progressively increasing their resolving capabilities. A number of tricks on the most effective processing approaches, as well as a novel method to pass from multipass differential interferometry products to absolute tropospheric columnar quantities are discussed. The proposed products and methods are assessed using real Sentinel-1 data. The experiment aims at evaluating the accuracy of the derived information and its impact on the weather prediction skill for two meteorological events in Italy. The main prospective of the study is linked to the possibility of exploiting interferometric products from a geosynchronous platform, thus complementing the inherent high resolution of SAR sensors with the required frequent revisit needed for meteorological applications.
Pedro Mateus (1), Giovanni Nico (2), João Catalão (1) and Pedro M. A. Miranda (1)
1. Instituto Dom Luiz (IDL), Faculdade Ciências, Universidade Lisboa, Lisboa, Portugal
2. Consiglio Nazionale delle Ricerche (CNR), Istituto per le Applicazioni del Calcolo, Bari, Italy
The processing of SAR images to generate maps of Precipitable Water Vapor (PWV) is becoming a useful tool in the community of atmosphere scientist to study atmospheric physical processes. Of particular interest is the assimilation of PWV maps in high resolution Numerical Weather Prediction (NWP) models. SAR meteorology, based on InSAR PWV maps and their assimilation in NWP models can help to better model phenomena such as deep convection with an impact on the correct forecast of extreme weather events as intense rainfalls. This has a crucial importance also on Civil Protection practices as it is tightly related to the flood and other hydrogeological risks. Sentinel-1 data are particularly suitable for SAR meteorology as its images cover large areas and have a short revisiting time of a few days.
We show the results obtained by assimilating PWV maps generated by Sentinel-1 data in the Weather Research and Forecasting (WRF) model. The enhancements in WRF forecasts is assessed in different ways, e.g. by comparing the PWV estimated numerically by the NWP model with GNSS measurements or the cumulated rainfall provided by the model with in-situ gauge measurements. The assessment is conducted both at the time of assimilation, and in a time window after the assimilation, to study the persistency of information on water vapor introduced by the assimilation of SAR maps. It is shown how the the impact of InSAR PWV maps on the output of NWP models changes depending on the specific atmospheric phenomenon and the NWP initial state. Also, the “memory effect” of the assimilated PWV maps changes from a few hours up to more than six hours. Methods to predict the impact that the assimilation of InSAR PWV maps would have on the output of an NWP are discussed.
Nazzareno Pierdicca, Luca Pulvirenti, Giorgio Boni
The next generation of Synthetic Aperture Radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤ 1 km) and temporal (≤ 12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture–data assimilation experiment (SM-DA) was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products characterized by diverse spatio-temporal resolutions. The experiment was designed also to understand if GEO SAR-like SM maps could provide an added-value with respect to SM products retrieved from SAR images acquired by satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems provides a valuable contribution for hydrological applications, especially if the possibility to generate many sub-daily observations is sacrificed in favor of higher spatial resolution. In the experiment, it was found that the assimilation of two GEO SAR-like observations at day with a spatial resolution of 100 m maximized the performances of the hydrological predictions, for both streamflow and SM state forecasts. Such improvements of the model performances were found to be 45% higher than the one obtained by assimilating POLAR SAR-like SM maps.
Soil moisture estimation with SAR images is currently based on the echoes backscatter. However, there are evidences that the soil or vegetation moisture can influence the interferometric phase. In fact, these moisture effects are suspected to be a considerable nuisance when the goal is the precise estimation of ground deformation. In the last year we have been investigating moisture retrieval algorithms based on interferometric phase, both for improving deformation measurements and possibly realize new soil or vegetation moisture products. A phase-based algorithm would allow moisture estimation also with a geosynchronous SAR system which backscatter might be too noisy to be used for this purpose.
In the past we have proposed a model for relating the moisture to the InSAR phase and presented validations, showing its potential. Inversions of the model, turning phase data into moisture, have also been already presented and to some degree validated. In this presentation we will summarize past works and show the latest improvements. In particular, inversion results based on L band UAVSAR data of the CanEx10 and SMAPVEX16 campaigns and their validation with ground based measurements will be presented. Moreover, we will present preliminary results of the application of the phase method to Sentinel-1 C band images. Finally, we conclude that the possibility of integrating backscatter-based soil moisture estimation with phase data is becoming realistic and should therefore be thoroughly investigated.
The WMO is currently providing technical support and products to the countries of the West Africa and Asia with initiatives such as Climate Risks and Early warning System(CREWS) and through projects like Flash Flood Guidance System(FFGS), Volta Basin Flood and Drought Management(VFDM), and Afghanistan Early Warning System Project (USAID/OFDA) building capacities and resources of the Meteorological and Hydrological services (NMHSs) at the National and Regional level. The Meteorological models delivering forecasting and leading to early warning for the Severe Weather and Climate Change events are mostly using satellite-based data and information.
The following are WMO projects and activities in the field of hydrometeorology that are interlinked with remote sensing capacities and capabilities. The purpose of the presentation is to provide a broad overview and to address the project needs, the challenges and to seek further cooperation areas and potentials.
The Adaptation Fund Project for Integrating Flood and Drought Management and Early Warning for Climate Change Adaptation in the Volta Basin.
The Volta Basin project has the ambition to provide the first large scale and transboundary implementation of Integrated Flood and Drought Management strategies through the complete chain Of End-to-End Early Warning System for Flood and Drought Forecasting. The project will empower the National Meteorological and Hydrological Services (NMHSs) and other competent authorities of the six riparian countries with robust and innovative solutions for disaster risk reduction and climate adaptation, including capacity development for green solutions and gender sensitive participatory approaches.
Afghanistan Early Warning System Project (USAID/OFDA).
To reduce the adverse effects of hydrometeorological hazards on vulnerable communities, WMO, the U.S. Agency for International Development/Office of U.S. Foreign Disaster Assistance (USAID/OFDA) and the Turkish State Meteorological Service (TSMS) have established a partnership to enhance the capacity of the Afghanistan Meteorological Department (AMD) to provide timely and accurate severe weather forecast and warnings, including flash floods.
The Flash Flood Guidance System
To address the issues associated with flash floods, especially the lack of capacity to develop effective flash flood warnings, the Flash Flood Guidance System (FFGS) was designed and developed for interactive Use by meteorological and hydrological forecasters throughout the world. In support of the FFGS programme, a Memorandum of Understanding was signed by the WMO, the U.S. Agency for International Development/Office of U.S. Foreign Disaster Assistance (USAID), the U.S. National Oceanic and Atmospheric Administration/National Weather Service (NOAA) and the Hydrologic Research Center (HRC) to work together under a cooperative Initiative to implement FFGS worldwide. The FFGS programme is a public benefit effort on behalf of the partners.
Additionally to Meteorological based products, WMO projects will also require accurate topographic, land-use and land cover etc. information for Hydrological modelling.
Martina Lagasio, CIMA Research Foundation
A. N. Meroni, L .Pulvirenti, G. Squicciarino, A. Parodi
H. Kontoes, A. Tsouni, N. Bartsotas, National Observatory of Athens
In the framework of the e-shape “EuroGEO Showcase: Applications Powered by Europe” project, the Pilot 2 application of the Disasters Resilience Showcase concerns the disasters in urban environment. Starting from the results and methodologies analyzed in the framework of the STEAM project, the e-shape pilot exploits the new capacities for designing and delivering innovative services for extreme-scale fire/hydro-meteorological modelling chain assimilating Copernicus data and core services directly ingested through the Copernicus Open Access Hub APIS, and the DIAS platform, as well as citizen scientists data, to enable more precise predictions and decision-making support for high impact events in urban and peri urban environment. Contributing to the Disaster Resilience SBA, one of the main activities listed in the GEO Space and Security Community Activity is to get maximum benefit from the use of large and heterogeneous datasets to potentially fill in the observational and capability gaps at EU decision making level. To this end, the application proposes also the integration of the datasets and tools made available in the frame of the pilot application (weather, citizen science, hydrological and fire models included in CIMA’s Platforms Dewetra and RASOR and NOA’s BEYOND Systems FireHub and FloodHub) for the impact assessment of natural hazards over areas of interest with regard to human security issues. An example of innovative service is the ingestion of high-resolution Copernicus remote sensing products in Numerical Weather Prediction (NWP) models. The rationale is that NWP models are presently able to produce forecasts with a spatial resolution in the order of 1 km, but unreliable surface information or poor knowledge of the initial state of the atmosphere may imply an inaccurate simulation of the weather phenomena. It is expected that forecast inaccuracies could be reduced by ingesting high resolution Earth Observation products into the models. In this context, the Copernicus Sentinel satellites represent an important source of data, because they can provide a set of high-resolution observations of physical variables (e.g. soil moisture, land/sea surface temperature, wind over sea, columnar water vapor) used in NWP model runs. The possible availability of a spatially dense Personal Weather Stations network could also be exploited to allow NWP models to assimilate timely updated data such as temperature, humidity and pressure. In this work a preliminary experiment design and methodology will be presented.
The TWIGA project is funded by the European Commission in the framework of its H2020 program. Goal of TWIGA is to improve the in-situ observational network in Africa and through innovative measurements. These measurements are combined with modelling efforts and satellite data to produce actionable geo-information. A number of sensor ideas at different Technology Readiness Levels are being developed and tested. In the presentation, there will be an overview of the sensors being developed, together with a more in-depth exposition about the 2018 hardware hackathon in Kumasi, Ghana, and the use of a very simple rain sensor that counts drops and the time intervals between them.
Food security and monitoring the state of Sustainable Development Goals in Africa is a topic of interest for the European Union (EU) and the African Union Commission (AUC). Both institutions have identified the need of a knowledge platform for sustainable development at national, regional, and continental scales. This platform should provide the necessary data and analytical tools to support evidence-based decision making; document existing good practices as well as replicate and upscale them; develop monitoring and evaluation capabilities of project outcomes, accountability and transparency; and ensure capacity building, ownership and sustainability. According to that, the Horizon 2020 AfriCultuReS - Enhancing Food Security in AFRIcan AgriCULTUral Systems with the Support of REmote Sensing - project (GA no.: 774652) aims to design, implement and demonstrate an integrated agricultural monitoring and early warning system that will support decision making in the field of food security. AfriCultuReS delivers a broad range of climatic, production, biophysical and economic information for eight regions in Africa (South Africa, Mozambique, Ethiopia, Rwanda, Kenya, Tunisia, Niger, and Ghana). The project consortium applies geospatial science to sustainable agricultural development, natural resource management, biodiversity conservation, and poverty alleviation in Africa. To do so, partners have developed a comprehensive solution to enrich Decision Making on food security through a geo-enabled Food Security Decision Support System (FSDSS) using remote sensing data and tools, crop modelling, and weather forecast. In particular, we have defined a list of services and products in line with the user’s requirements collected in national workshops. Services focus on improving: climate predictions, crop condition, drought early warning and forecast, grazing and rangeland monitoring, water availability monitoring and productivity, weather forecast, soil condition assessment; and provide advice on how to avoid land degradation. In all, we have considered 57 products (i.e., geospatial datasets) and classified them either as “planned” (a delivery is foreseen) or as “candidate” (a feasibility assessment must be carried out). At the moment, 60% of the products are “planned” and 40% are “candidate”. Final products will be available through a GIS platform where users will be able to visualise and analyse these datasets.
Stefano Corradini, Istituto Nazionale di Geofisica e Vulcanologia, Rome
Simona Scollo, Istituto Nazionale di Geofisica e Vulcanologia, Catania
Explosive eruptions have great impact on society and environment. Volcanic clouds in the atmosphere can affect climate and disrupt aviation safety, tephra fallout can cause roof collapses and infrastructures, and gas emissions may strongly affect human and animal health and vegetation. The volcanic hazard is also expected to increase due to a constant growth of both population and infrastructures in the proximity of active volcanoes.
Over the last 15 years, the global understanding of eruptive mechanism and impacts has improved thanks to the technology advance on ground based and satellite remote sensing systems. As example, visible calibrated cameras are used to estimate plume column height, radar instruments to evaluate the tephra plume and mass eruption rate, lidar and UV/TIR ground-based and satellites systems to characterize volcanic ash and gases in the atmosphere.
Here an overview of the ground based and satellite remote sensing systems used from INGV for the monitoring of the Etna volcano will be described. The work will describe the ability of the remote sensing systems to entirely follow the eruptive events in near real time, offering a powerful tool to mitigate volcanic risk on both local population and airspace.