Satellite inspired hydrology in an uncertain future: a H SAF and HEPEX workshop

Soil moisture is a key parameter for environmental (e.g. flood, drought,fire) and weather prediction systems. The EUMETSAT H SAF products give information on both surface and root zone soil moisture. The ASCAT Surface Soil Moisture (SSM) products are produced globally in near real-time and represent the water content in the upper soil layer (< 2cm). The SSM products are distributed in two...

H SAF provides satellite-derived products of precipitation, soil moisture and snow. These products are continuously validated to guarantee optimal performance. Various soil moisture (SM) products are distributed in near real-time, namely, the surface SM product derived from the radar backscattering coefficients measured by the Advanced Scatterometer (ASCAT) on-board the series of Metop...

Precipitation is the most important variable in Earth hydrological budget being the major component of water cycle. For this reason, the better under¬standing of the spatial and temporal distribution of precipitation, and its quantification, is fundamental for any hydrological and climatological application. Although surface precipitation gauges are considered the standard devices for...

The H SAF concept was born on the requirements of the hydrologic community and is focused on
the development and operational delivery of satellite products that can be used in work pursued by
the National Hydrological Services and water management institutions. In H SAF program are
available two types of validation on precipitation products: quality assessment and hydrological
validation....

Reliable snow cover extent is of vital importance in order to have a comprehensive understanding for present and future climate, hydrological, and ecological dynamics. Development of methodologies to obtain reliable snow cover information by means of optical and microwave remote sensing (RS) has long been one of the most active research topics of the RS community.
Operational snow products...

H SAF provides satellite-derived products of precipitation, soil moisture and snow. These products are yearly validated to guarantee optimal performance. Under the project, different snow products are distributed in near real-time, namely, SE-E-SEVIRI (Snow detection by VIS/IR radiometry); WS-E (Snow status - dry/wet - by MW radiometry); FSC-E (Effective snow cover by VIS/IR radiometry) and...

Since 2004, HEPEX (Hydrologic Ensemble Prediction Experiment) has been fostering a community of researchers and practitioners around the world. The mission is still to establish a more integrated view of hydrological forecasting, where data assimilation, hydro-meteorological modelling chains, pre- and post-processing techniques, expert knowledge, participatory co-evolution of knowledge and...

This study investigates the capability of LDAS-Monde global offline LDAS to monitor and forecast the impact of extreme events on Land Surface Variables (LSVs). LDAS-Monde is driven by ERA-5 atmospheric forcing from ECMWF and is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model.
A global...

The main objective of this study is to investigate how innovative satellite earth observation techniques that allow for the estimation of soil moisture and the mapping of flood extents can help in reducing errors and uncertainties in conceptual hydro-meteorological modelling especially in ungauged areas where potentially no or limited runoff records are available. A spatially distributed...

Floods are the most frequent and costliest natural disasters worldwide. The potentiality of the images provided by synthetic aperture radar (SAR) systems for near real-time flood mapping was demonstrated by several past studies. Nowadays, scientific methods for daily automatically detection and identification of flood area or, more generally, areas where standing water is present from SAR data...

The measurement of precipitation across the Earth’s surface is complex due to the vagaries in the occurrence and intensity of precipitation, together with the variations in the temporal and spatial distribution of precipitation across the global. The physical nature of precipitation necessitates that the observation, sampling and reporting of precipitation is adequate for the resulting end...

The talk will review the current status of satellite and surface networks capable of providing precipitation with high space/time resolution with a view towards the future. While ground based radar networks continue to see systematic although measured progress, there will be a rapid increase in satellite capabilities both in terms of microwave sensors made possible by new Cube- and MicroSat...

The snow depth in the world’s mountains ranks among the most uncertain variables in hydrology. Estimates from the interpolation of local measurements are unrealistic where they are sparse, atmospheric models poorly estimate snowfall, and current snow remote sensing observations have inherent limitations. Yet, accurate snow depth estimates are critically needed to provide information on the...

The very scales at which data may be required and the accessibility of sampling points quickly renders certain direct measurements impractical e.g., changes in land cover, sea surface temperature, snow in mountains, etc. Satellite-derived products are a valuable source of such data and overcomes the large spatial extent limitations. The data is sometimes at a reasonable temporal resolution as...

The Mediterranean region is often impacted by heavy precipitation events, responsible for damages and sometimes casualties. Because of its peculiar geographical characteristics, ground-based observations (e.g. raingauges and radars) cannot be fully exploited for the monitoring, characterization and forecasting of severe events, in particular during their offshore development. Therefore in the...

Monitoring terrestrial snow cover on continental and global scales is complicated by large differences on regional and local conditions as well as large gaps in surface observing networks. Therefore satellite-based observations provide the best spatially and temporally extensive means for snow cover monitoring on hemispherical scale.

The objective of the ESA Snow CCI is to generate...

Modelling snow events stayed as challenge as it depends on multiple parameters. For the sake of performance and fewer requirements, temperature-index models employed. These models generally calibrate a basin-wide threshold temperature, a degree-day factor (DDF) which accepted as constant. Some hydrologic models such as Mesoscale Hydrologic Model (mHM), that employs multiscale parameter...

The observed warming of temperatures in boreal regions in the past decades has led to an increase in the frequency, intensity and size of forest fires with numerous consequences on ecosystems and water budget. Hydrological models can be used to assess the impact of these fires on the hydrological regime, but they necessitate sufficient input data to produce reliable results and ground...

Over the last decades, satellite observations have increasingly been used to study the global terrestrial Water Cycle (WC). We will present here applications to retrieve for instance soil moisture, surface waters or underground water storage. However, the use of satellite products is still limited by their uncertainties and inconsistencies like their inability to close the WC budget. We show...

The flood forecasting component of the Copernicus Emergency Management Service Early Warning System (CEMS-EWS Floods), run at the European Centre for Medium-range Weather Forecasts (ECMWF), provides medium range flood forecasts at both the European and global scales. Forecast accuracy correlates strongly with accurately representing the initial status of hydrological variables including soil...

The number of precipitation-related observations that are used in ECMWF’s operational 4D-Var data assimilation system has been steadily increasing over the past two decades, bringing a significant improvement in the quality of atmospheric analyses and subsequent forecasts. This presentation will review the status of ECMWF’s operational assimilation of all-sky satellite microwave brightness...

The UKV is the Met Office operational modelling system for the UK area. An hourly cycling 4DVAR algorithm provides atmospheric initial conditions; meanwhile the initial land state is provided by interpolating a global soil moisture analysis at a daily frequency. The forecast step uses the Unified Model for the atmosphere coupled to JULES for the land state at 1.5km.

The Met Office has...

Many global initiatives launched in recent years by the international community, such as the SDG (especially SDG-6 water and sanitation) and WMO’s WHOS, HydroSOS and others have highlighted the growing need for reliable hydrological data. However the outcomes of recent survey carried out by WMO and WB indicate that particularly in low and middle-income countries, Hydrological Services are...

The performance of numerical weather prediction (NWP) can be improved significantly by assimilating remotely sensed soil moisture in the included land surface model. In our study, we investigate the improvement of the NWP in the Austrian domain by assimilating the multi-layer fused data product SCATSAR-SWI (Soil Water Index) with the surface model SURFEX. The SURFEX assimilation employs a...

An accurate representation of snow extent and depth is of great importance in Numerical Weather Prediction (NWP) models for calculations of surface fluxes which provide the lower boundary conditions for the atmosphere. In the UK the model representation of snow is itself of great interest to forecasters, who must provide current information on and predictions of snow positioning, depths and...

Bucket-type hydrological models such as the HBV model are widely popular, because of their relatively low data and computational demands. This is the case of the snow routine in the HBV model. While this approach usually results in good simulations, improvements are possible. We explored and tested different alternatives to the design of the snow routine of HBV-light such as considering a...

Improving sharpness/reliability of hydrological forecasts is key to increase the value of a warning service. Hydrological data assimilation is one possible way to increase the accuracy (and possibly reliability). Various studies in assimilation of various ECVs (water level, discharge, soil moisture) show that accuracy can be indeed be improved. Here, we show results from the H2020 IMPREX...

Event-based hydrological modelling disregards some hydrological processes that during an event resulted neglectable. A reliable initial condition of model is fundamental for discharges prediction and, consequently, for flood risk mitigation. Satellite observations can be exploited to estimate soil moisture and these can be used to enhance the predictions of hydrological models.
The aim of...

The objective of this study is to evaluate the potential of assimilating flood extent information derived from satellite Earth observation into a flood forecasting chain for reducing predictive uncertainty. A recent promising study introduces a DA framework based on probabilistic flood maps derived from SAR images considering uncertain rainfall. In our study, we carry out an identical twin...

A consortium led by the RHEA Group, working with the Ugandan Ministry of Water and Environment and local Non-Governmental Organizations (NGOs, AgriTechTalk Uganda and Mercy Corps) has developed a Drought and Flood Mitigation Service (DFMS), funded as part of the UK Space Agency’s International Partnership Programme.

DFMS is using satellite Earth observation (EO) data alongside meteorological...

Data assimilation (DA) allows for updating state variables in a model to represent reality more accurately than the initial (open loop) simulation. In hydrology, DA is often a pre-requisite for forecasting. Neural networks (NN) can learn almost any nonlinear relationship between inputs and outputs. Here, we hypothesize that NN could learn the relationship between the simulated streamflow...

A retrieval methodology based on Neural Networks was proposed (Aires et al. 2005) to retrieve and assimilate Soil Moisture (SM) from satellite observations. It is based on the fact that no radiative transfer model was satisfactory enough for a physically-based algorithm. An innovative aspect is to train the NN using modelled SMs. The resulting retrievals are not a reproduction of the model:...

Recent studies have demonstrated the potential of assimilating probabilistic inundation maps derived from Synthetic Aperture Radar (SAR) imagery for improved flood forecasts. However, high resolution SAR acquisition can only provide partial coverage of large catchments. Consequently, information on the impacts of location, timing, and frequency of inundation extent assimilation on flood...

Analyzing and forecasting the variability of snow is essential for runoff prediction especially in mountainous regions where the optimal operation of reservoirs is important. Remote sensing information has been extensively developed over the last decay with enhanced snow data sets at high resolutions. The implementation of satellite facilities in operational runoff forecasting systems by means...

Fully coupled modelling of atmospheric and hydrological processes is of growing interest among the hydrometeorology community. Understanding multi-time scale processes within a land-atmosphere modelling system is of importance for improving forecast between medium-range and seasonal forecasts. Improving forecast capabilities between sub-seasonal to seasonal forecasting, can help shape the...

Several satellite observations are used to monitor inundation over the globe: Visible/infrared observations (e.g. MODIS/Landsat), active (e.g. SAR) or passive microwave; each one with its own advantages/drawbacks. For instance passive microwave has a low spatial resolution, and visible cannot detect water below clouds or vegetation. We will review several of the techniques currently used. The...

Satellite snow products represent a precious resource in hydrology for calibrating, validating, and improving the performances of models, through data assimilation.
Here, I will provide some examples of application of snow satellite products to hydrological problems and investigate the issue of balancing model complexity and input data requirements in snow hydrology.

Satellites are key observing systems to provide information on essential climate variables over large spatial scales. Soil water content is an important essential climate variables that regulates the exchange of energy, water, and carbon between the land surface and the atmosphere.

As part of the Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF)...

This study attempts to assess the amount of water contribution from snowmelt water equivalent into Senqu River of Lesotho. Cloud free MODIS (terra/Aqua) MOD09A1 images were downloaded for the winter snow-packing period (April-July) and the melting seasons (August – September) for the years 2013-2017. The snow cover areas were mapped using the three conditions, which are Normalised Difference...

eWaterCycle II seeks to create an online environment where users can easily work with a wide variety of hydrological models, without the hassle of installing, obtaining forcing data, and setting up these models. Ultimately, the goal is to advance the state of FAIR and open science in hydrological modelling.

A big hurdle that was identified during a dedicated workshop earlier this year is...

Precipitation is generally considered to be one of the least certain input of a hydrological model. This uncertainty stems in part from its spatial variability within a watershed, which is difficult to represent with a network of rain gauges, especially when it is not very dense. Remote sensing can provide a more complete spatial picture, but its performance as an input to modeling natural...

In the portfolio of operational precipitation products (PP) released in HSAF (Satellite Application Facility on support to Hydrology), recently was added the H18 product based on passive microwave (PMW) acquisitions from the ATMS (Advanced Technology Microwave Sounder) cross-track scanning radiometer on board the Suomi-NPP satellite. The product provides instantaneous surface precipitation...

A project is being proposed which will investigate multiple issues that arise when assimilating remotely sensed soil moisture data into a distributed hydrological model for flood forecasting. The first issue is estimating subsurface soil moisture from satellite surface measurements. Although root zone soil moisture is more important for streamflow modeling, satellites can estimate soil...

Machine learning approaches can be considered as a computationally efficient alternative to ‘classical’ deterministic hydrological models. The more commonly used types of machine learning in hydrology are artificial neural networks, support vector machines, and random forests. Regardless of the model structure, machine learning models require inputs which provide information about the...

The National Oceanic and Atmospheric Administration (NOAA) Office of Water Prediction runs the National Water Model (NWM) operationally over the continential US.The model is forced by NWP products from NOAA's National Weather Service. The NWM simulates land surface and hydrologic states and fluxes: 1km land model, 250m overland and subsurface hydrologic routing, and streams at ~1.5 km.
We...

EUMETSAT FRACTIONAL SNOW COVER PRODUCTS

Burak Simsek, Kenan Bolat, Matias Takala, Zuhal Akyurek and Ali Nadir Arslan
Finnish Meteorological Institute (FMI) Arctic Space Centre, Finland
E-mail: burak.simsek@fmi.fi

ABSTRACT

EUMETSAT snow cover products namely H12 and H35 are presented. Products H12 (SN-OBS-3) and H35 (SN-OBS-3P) are fractional snow cover (FSC) products from EUMETSAT. Both...

Snow Water Equivalent (SWE) is the only remote sensing parameter of snow that provides information on amount of snow. Snow Extent and Fractional Snow Cover obtained by using optical instruments in remote sensing can’t provide neither Snow Depth nor Snow Mass which are related to SWE. However, SWE can be estimated to a degree by using passive microwave remote sensing. The EUMETSAT H SAF product...

Reliable snow cover extent is of vital importance in order to have a comprehensive understanding for present and future climate, hydrological, and ecological dynamics. Development of methodologies to obtain reliable snow cover information by means of optical remote sensing (RS) has long been one of the most active research topics of the RS community. In this study EUMETSAT snow cover products...

The European Centre for Medium Range Weather Forecasts (ECMWF) delivers the core root-zone soil moisture (SM) products for H SAF through an advanced land data assimilation system, running independently of the NWP system. Space borne scatterometer-derived surface SM observations from the ASCAT sensors are assimilated into the root-zone (0-1 m) SM of the H-TESSEL land surface model. Two products...

In the framework of the EUMETSAT’s Satellite Application Facility on Land Surface Analysis (LSA SAF), a method has been developed in order to monitor the flux of water between the land surface and the atmosphere (evapotranspiration). More recently, in addition to evapotranspiration, the surface latent and sensible heat fluxes are also generated. To better understand the reasons for some...

Flood forecasting and flood estimation commonly rely on catchment-average rainfall estimates.
However, rainfall variability has been identified as one of the most influential factors in shaping flood magnitude. Ignoring rainfall variability can hence cause significant bias in the resulting flood estimates for some catchments.
High spatial and temporal resolution rainfall data (e.g. radar...

The interaction between land and atmosphere is governed by water in the topsoil layer since the amount of surface soil moisture determines the partitioning of outgoing energy flux into latent and sensible heat fluxes. However, despite its immense importance, our understanding of the physics of diurnal water and energy cycles on a global scale is limited. In particular, the coverage of current...

Central Europe is faced actually by a long lasting drought period starting in year 2011. The preliminary peak was reached in 2018 leading to a severe agricultural drought long lasting low water periods in all rivers of Central Europe and serious economic losses. It was becoming obvious that there is an increasing need for improving drought monitoring and seasonal meteorological and...

The operational Met Office (MO) Land Surface Data Assimilation (LSDA) system for Global and Regional (UKV) models is summarised alongside upcoming developments. The MO land and atmospheric analyses are weakly coupled. Each component is computed separately and then the joint analysis is propagated by the Unified Model coupled with the land surface model Jules.

In the global model, LSDA is...

Soil moisture (SM) represent one of the most suitable indicator to assess agricultural drought, which occur when there is not enough SM to support crop production. Many studies have promoted the use of SM data from surface/hydrological models and more recently, from active and passive microwave sensors to assess agricultural drought conditions. In particular, remote sensing SM products are...

Environment and Climate Change Canada (ECCC) is the lead federal department for a wide range of environmental issues. ECCC's programs focus on minimizing threats to Canadians, in particular through the use of weather and water forecasts, issued using coupled numerical models. Six-day streamflow forecasts are currently issued twice daily on a 1-km grid for all tributaries of two of the largest...

Abstract
This study aimed at developing rainfall estimation schemes based on the high spectral resolution of Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI).
The potential of developing machine learning techniques that use ensembles of classifications and regressions was investigated, to improve rainfall rate assignment based on spectral cloud...

State-of-the-art satellite rainfall products are often the only way for measuring precipitation in remote areas of the world. Currently, one of the major issues impacting the quality of these products is related to the estimation of light precipitation that causes an underestimation of the total amount of rainfall. With the purpose of estimating rainfall using satellite soil moisture (SM)...

H SAF MW-only precipitation products are based on the exploitation of all MW radiometers onboard LEO satellites. They provides Level 2 instantaneous precipitation rate, at a nominal resolution depending on the radiometer characteristics. MW-only gridded products, based on merged precipitation estimates available from the MW radiometer constellation, are also delivered.
Here we focus on two...

STREAM -SaTellite based Runoff Evaluation And Mapping, is an ESA project investigating the feasibility to derive runoff estimates from existing spaceborne missions. The purpose of the project is to develop and validate a solid “observational” approach alternative to existing model-based runoff estimates, that exploits space-only observations of Precipitation (P), Soil Moisture (SM) and...

Flow forecasting systems are in operational use widely. They are based today on a modelling chain where the output of numerical weather prediction models forms the input of conceptual distributed or semi-distributed hydrological models. Furthermore, statistical meteorological data pre-processing and hydrological post- processing procedures round up a modelling chain. In some systems...