Hydrometeorological and vegetation indices for the drought monitoring system in Tuscany Region, Italy

We present here the first experiments for an integrated system that is under development for drought monitoring and water resources assessment in Tuscany Region in central Italy. The system is based on the cross-evaluation of the Standardized Precipitation Index (SPI), Vegetation Indices from remote sensing (from MODIS and SEVIRI-MSG), and outputs from the distributed hydrological model MOBIDIC, that is used in real-time for water balance evaluation and hydrological forecast in the major basins of Tuscany. <br><br> Furthermore, a telemetric network of aquifer levels is near completion in the region, and data from nearly 50 stations are already available in real-time. <br><br> Preliminary estimates of drought indices over Tuscany in the first eight months of 2007 are shown, and pathway for further studies on the correlation between patterns of crop water stress, precipitation deficit and groundwater conditions is discussed

Land-atmosphere interactions in an high resolution atmospheric simulation coupled with a surface data assimilation scheme

A valid tool for the retrieving of the turbulent fluxes that characterize the surface energy budget is constituted by the remote sensing of land surface states. In this study sequences of satellite-derived observations (from SEVIRI sensors aboard the Meteosat Second Generation) of Land Surface Temperature have been used as input in a data assimilation scheme in order to retrieve parameters that describe energy balance at the ground surface in the Tuscany region, in central Italy, during summer 2005. A parsimonious 1-D multiscale variational assimilation procedure has been followed, that requires also near surface meteorological observations. A simplified model of the surface energy balance that includes such assimilation scheme has been coupled with the limited area atmospheric model RAMS, in order to improve in the latter the accuracy of the energy budget at the surface. The coupling has been realized replacing the assimilation scheme products, in terms of surface turbulent fluxes and temperature and humidity states during the meteorological simulation. Comparisons between meteorological model results with and without coupling with the assimilation scheme are discussed, both in terms of reconstruction of surface variables and of vertical characterization of the lower atmosphere. In particular, the effects of the coupling on the moisture feedback between surface and atmosphere are considered and estimates of the precipitation recycling ratio are provided. The results of the coupling experiment showed improvements in the reconstruction of the surface states by the atmospheric model and considerable influence on the atmospheric dynamics

Sea state monitoring using coastal GNSS-R

We report on a coastal experiment to study GPS L1 reflections. The campaign was carried out at the Barcelona Port breaker and dedicated to the development of sea-state retrieval algorithms. An experimental system built for this purpose collected and processed GPS data to automatically generate a times series of the interferometric complex field (ICF). The ICF was analyzed off line and compared to a simple developed model that relates ICF coherence time to the ratio of significant wave height (SWH) and mean wave period (MWP). The analysis using this model showed good consistency between the ICF coherence time and nearby oceanographic buoy data. Based on this result, preliminary conclusions are drawn on the potential of coastal GNSS-R for sea state monitoring using semi-empirical modeling to relate GNSS-R ICF coherence time to SWH.Comment: All Starlab authors have contributed significantly; the Starlab author list has been ordered randomly. Submitted to GR

The Eddy Experiment: accurate GNSS-R ocean altimetry from low altitude aircraft

During the Eddy Experiment, two synchronous GPS receivers were flown at 1 km altitude to collect L1 signals and their reflections from the sea surface for assessment of altimetric precision and accuracy. Wind speed (U10) was around 10 m/s, and SWH up to 2 m. A geophysical parametric waveform model was used for retracking and estimation of the lapse between the direct and reflected signals with a 1-second precision of 3 m. The lapse was used to estimate the SSH along the track using a differential model. The RMS error of the 20 km averaged GNSS-R absolute altimetric solution with respect to Jason-1 SSH and a GPS buoy measurement was of 10 cm, with a 2 cm mean difference. Multipath and retracking parameter sensitivity due to the low altitude are suspected to have degraded accuracy. This result provides an important milestone on the road to a GNSS-R mesoscale altimetry space mission.Comment: All Starlab authors have contributed significantly; the Starlab Author list has been ordered randoml

The GNSS-R Eddy Experiment II: L-band and Optical Speculometry for Directional Sea-Roughness Retrieval from Low Altitude Aircraft

We report on the retrieval of directional sea-roughness (the full directional mean square slope, including MSS, direction and isotropy) through inversion of Global Navigation Satellite System Reflections (GNSS-R) and SOlar REflectance Speculometry (SORES)data collected during an experimental flight at 1000 m. The emphasis is on the utilization of the entire Delay-Doppler Map (for GNSS-R) or Tilt Azimuth Map (for SORES) in order to infer these directional parameters. Obtained estimations are analyzed and compared to Jason-1 measurements and the ECMWF numerical weather model.Comment: Proceedings from the 2003 Workshop on Oceanography with GNSS Reflections, Barcelona, Spain, 200

Validazione di una innovativa rete di rilevamento pluviometrica basata sulla misura opportunistica di segnali televisivi diffusi da satellite

Nonostante la varietà di metodi e strumenti esistenti per la misura di precipitazioni, non esiste un metodo che funzioni meglio di tutti gli altri in tutte le condizioni operative. I pluviometri sono gli strumenti tradizionalmente utilizzati per ottenere misure puntuali con elevata precisione del quantitativo d’acqua che precipita in un determinato intervallo di tempo. I sistemi radar meteorologici consentono invece di stimare la distribuzione spaziale della precipitazione e di monitorarne la dinamica, pur se con precisioni minori. Infine i satelliti consentono in maniera indiretta di stimare la precipitazione su scale molto più ampie, ma al prezzo di un aumento dell’incertezza e di una minor risoluzione spazio temporale. Rispetto a questi strumenti tradizionali ve ne sono alcuni che derivano da un uso opportunistico di sistemi progettati e realizzati per altri scopi, ma che possono comunque fornire informazioni utili alla stima della precipitazione. In particolare, i sistemi di telecomunicazione che impiegano radiocollegamenti con frequenze superiori al GHz possono fornire informazioni rilevanti sulle precipitazioni, attraverso la misurazione dell'attenuazione del segnale trasmesso causata dalle gocce di pioggia nella tratta dal trasmettitore al ricevitore. NEFOCAST è un progetto di ricerca FAR-FAS finanziato dalla Regione Toscana, che sfrutta questa opportunità attraverso innovativi dispositivi satellitari bidirezionali (cioè trasmettitori/ricevitori) denominati Smart Low-Noise Block converter (SmartLNB), concepiti per l’interazione ubiquitaria via satellite ma in grado di rilevare il valore di attenuazione del segnale ricevuto e di trasmetterlo direttamente ad un centro di raccolta. L'utilizzo di SmartLNB presenta significativi vantaggi in termini di costi e facilità di installazione/configurazione e fornisce la possibilità di applicazione in qualsiasi area coperta dal segnale satellitare, offrendo al tempo stesso un'efficiente soluzione “embedded” per la trasmissione dei dati, senza necessità di ricorrere a ricevitori dedicati per la stima della pioggia. L’algoritmo di stima della precipitazione di NEFOCAST è stato studiato basandosi su modelli fisici e su modelli empirico-statistici. Per tale scopo sono state effettuate delle campagne di misura utilizzando uno SmartLNB, un radar meteorologico (puntato nella stessa direzione del satellite) ed un disdrometro co-locati presso la sede del CNR-ISAC di Roma. L’algoritmo di stima dei campi di precipitazione è stato implementato attraverso un filtro di Kalman che utilizza come dati di input le misure degli SmartLNB e dati ausiliari da osservazioni satellitari. Durante il progetto NEFOCAST è stata infine condotta una campagna di test e validazione dell’algoritmo messo a punto per la stima della precipitazione a partire da misure di attenuazione effettuate con gli SmartLNB. Durante tale campagna di misura, della durata di un anno circa, sono stati dislocati sul territorio della Regione Toscana un numero significativo di SmartLNB. Le stime di precipitazione ottenute dalla rete di SmartLNB, opportunamente densa di terminali nell’area di Firenze, sono state analizzate attraverso i confronti con una rete di pluviometri co-locata e un radar polarimetrico X-band Doppler installato per gli obiettivi di calibrazione/validazione

Tsunami detection using the PARIS concept

Abstract On 26 December 2004 a tsunami generated by an earthquake with its epicentre in the Indian Ocean West of Indonesia caused a real human and material catastrophe in the region. After the event some proposals to establish a network of sensors for tsunami detection were put forward. This paper presents an alternative concept that can be applied from satellite, aircraft or from the coast, and which can complement such a network of sensors for fast tsunami detection. The concept makes use of GNSS signals reflected from the ocean's surface to perform mesoscale ocean altimetry. The technique, designated PARIS (Passive Reflectometry and Interferometry System), aims at capturing fast topographic events happening on the ocean surface such as eddies and fronts. The paper includes details of some aircraft experiments whereby a PARIS altimeter was used to map a topographic signature with amplitude and wavelength similar to a tsunami in open ocean

Estimating land cover effects on evapotraspiration with remote sensing: a case study in Ethiopian Rift Valley

A methodology for the analysis of land surface control on evapotranspiration and heat fluxes is presented, based on the assimilation of remotely sensed data. The method is suitable for application in areas with limited data availability since only standard micro-meteorological measurements and land surface temperature maps are required, while no a priori information about land cover is required. The land cover effect on the heat exchange is inferred from the assimilation in terms of heat transfer coef-ficients. The methodology has been applied in the Ethiopian Rift Valley where desertification processes are progressing at a high rate in association with remarkable temperatures recorded in the last decades. Measurements of radiation, temperature and wind profiles were taken in a field campaign. The land surface temperature maps were obtained from NOAA-AVHRR. The results show reasonable estimates of the retrieved surface fluxes and spatial patterns of heat transfer coefficients consistent with those of land cover and vegetation