This page collects the Research Reports produced as results of the SCIRoCCo-funded Grants. You may download them from the link at the bottom of the page.

 


 

Title: Examining the validity of ERA-Interim for tropical hurricanes over the course of time

Author: Tim Bijsterbosch (KNMI, 2016)

Abstract:

Validity of ERA-Interim for tropical hurricanes over the course of time is examined. ERA-Interim is a reanalysis which uses one of the leading weather prediction models to reforecast the state of the atmosphere several times per day. This means that the only thing that changes the way ERA-Interim calculates these reforecasts are the input measurements used as initial state, which improve in quantity and quality with time. To examine if the validity of ERA-Interim for tropical hurricanes also improves with time the 10 m height wind product modelled by ERA-Interim will be compared to 10 m height wind product derived from satellite observations over a period of time. The satellite observations which are used are from the ERS-2 (1996 – 2001) and ASCAT ( 2007 – 2014) scatterometers.


 

Title: Neural-network discrimination sea/ice discrimination using ERS
scatterometer data.

Author: Khaoula Hmamouche (RMA, August 2015)

Abstract:  The primary objective of the scatterometer is to determine the wind fields over oceans using empirical Geophysical Model Functions (GMF). These models are only valid over open sea, they are not valid over land and sea-ice. Land is easily discarded using land masks. Over sea-ice it is more difficult to discriminate open water and the ice due to the dynamic extent of the sea-ice which result from the freezing and melting through the seasons. So as to remove spurious wind vectors we have to discriminate the sea and the ice at real time.
A neural-network has been developed, to compute the sea/ice probability P(H1|mc) at each
node of the grid. (where: H1 is the hypothesis the measurement corresponds to ice, given the measurement vector mc =(Cc; n), n is the node number in which the measurement Cc was made).
Some criteria can be used such as: derivative of sigma, backscatter isotropy, distance to the wind model and distance to ice model. This work is an attempt to enhance the sea-ice detection algorithm by adding other criteria while the stateless strategy will be the same.


 

Title: Comparison of ERS-2 ESCAT sea backscattering coefficients with electromagnetic models of sea surface scattering and other empirical models under challenging geophysical conditions

Author:  Federica Aveta (SERCO/KNMI, 2016)

Abstract:   Rain effect can distort the signal and cause errors in the wind retrieval. In fact, rain modifies the measured radar cross section in several ways and the most important rain effects are the splash effects and the atmospheric effects. Rain modifies the ocean surface by impinging on it with an increasing of the surface roughness due to the generation of the ring waves and with an induced wave damping due to the generation of an upper turbulence layer. Meanwhile rain modifies the scatterometer signal when it passes through the atmosphere by attenuating it and by increasing the signal due to volume scattering.
The electromagnetic model Small Slope Approximation up to the second order (SSA2), that simulates the ocean surface backscattering coefficient, has been modified by including these rain effects. The splash effects, i.e. generation of ring waves and rain-induced wave damping [6], that modify the ocean surface roughness, have been considered by modifying the Elfouhaily sea wind wave spectrum in the region of the capillary waves.

 


 

Attachments:
Download this file (Aveta_Master_Thesis_2016.pdf)Aveta_Master_Thesis_2016.pdf[Master Thesis - Rain effects ]2422 kB
Download this file (Report-Sea-ice-detection-2015-f.pdf)Hmamouche 2015[Scirocco Grant Report]1527 kB
Download this file (Report_Tim_knmi-3.pdf)Bijsterbosch 2016[Scirocco Research Report]6230 kB
Download this file (SCI-REP-16-0001_F_Aveta.pdf)Aveta 2016[Scirocco Research Report]1640 kB