scholarly journals Mitigating atmospheric noise for InSAR using a high resolution weather model

2006 ◽  
Vol 33 (16) ◽  
Author(s):  
J. Foster ◽  
B. Brooks ◽  
T. Cherubini ◽  
C. Shacat ◽  
S. Businger ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Noise ◽  
Weather Model

Non-reasonable but efficient use of schemes in current model to improve realistic explicit convection modelling

2020 ◽  
Author(s):  
christophe messager ◽  
marc honnorat
Keyword(s):  
High Resolution ◽  
Current Model ◽  
Wrf Model ◽  
Region Of Interest ◽  
Limited Area ◽  
Operational Mode ◽  
Model Framework ◽  
Large Eddy Simulation Model ◽  
Weather Model ◽  
Daily Forecast

<p>There is actually no limitation of current high-resolution weather model for producing simulation and forecast of convection at kilometer and infra-kilometer horizontal resolutions. However, the disappointing results as well as the associated huge amount of computer resources required may lead to focus on Large Eddy Simulation model instead. However, the use of LES is not trivial and required a long and non-portable adjustment over the region of interest. Also, it is difficult to use in operational mode for daily forecast since they require specific inputs.</p><p>In the other side, pushing the current regional or Limited Area Model towards very high resolution is a convenient way to reach explicit resolution of convective process for instance. However, an explicit simulation is not a guarantee of a realistic result mainly due to the fact that initial condition is crucial as well as all other descriptions of the environment (soil, vegetation, sst, etc) and use of correct parameterization schemes.</p><p>For instance, within the WRF model framework, one can identify more than 4000 set of parameterizations plus all the scheme adjustments and threshold associated to.</p><p>However, a physically based analyze of what it is necessary for a realistic and explicit convection simulation may conduct a physicist user to define its “ideal” physics with what it already exists in the model. It may conduct to so-called unrealistic model requests in term of computation requirement regarding the radiative, the turbulence and the microphysics schemes but it does works with HPC systems. This kind of parameterization will be presented here and used with a very realistic vertical circulation into convective systems with convective updraft and downdraft modelling, from few meters up to several kilometers height.</p>

Waterspout Forecasting Method Over the Eastern Adriatic Using a High-Resolution Numerical Weather Model

2018 ◽  
Vol 175 (11) ◽  
pp. 3759-3778 ◽  
Author(s):  
Tanja Renko ◽  
Sarah Ivušić ◽  
Maja Telišman Prtenjak ◽  
Vinko Šoljan ◽  
Igor Horvat
Keyword(s):  
High Resolution ◽  
Numerical Weather ◽  
Numerical Weather Model ◽  
Weather Model ◽  
Forecasting Method

scholarly journals TRU-NET: a deep learning approach to high resolution prediction of rainfall

2021 ◽  
Author(s):  
Rilwan A. Adewoyin ◽  
Peter Dueben ◽  
Peter Watson ◽  
Yulan He ◽  
Ritabrata Dutta
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Spatial Resolution ◽  
Climate Models ◽  
Heavy Precipitation ◽  
Learning Approach ◽  
Multi Scale ◽  
Weather Model ◽  
The Impact ◽  
Precipitation Events

AbstractClimate models (CM) are used to evaluate the impact of climate change on the risk of floods and heavy precipitation events. However, these numerical simulators produce outputs with low spatial resolution that exhibit difficulties representing precipitation events accurately. This is mainly due to computational limitations on the spatial resolution used when simulating multi-scale weather dynamics in the atmosphere. To improve the prediction of high resolution precipitation we apply a Deep Learning (DL) approach using input data from a reanalysis product, that is comparable to a climate model’s output, but can be directly related to precipitation observations at a given time and location. Further, our input excludes local precipitation, but includes model fields (weather variables) that are more predictable and generalizable than local precipitation. To this end, we present TRU-NET (Temporal Recurrent U-Net), an encoder-decoder model featuring a novel 2D cross attention mechanism between contiguous convolutional-recurrent layers to effectively model multi-scale spatio-temporal weather processes. We also propose a non-stochastic variant of the conditional-continuous (CC) loss function to capture the zero-skewed patterns of rainfall. Experiments show that our models, trained with our CC loss, consistently attain lower RMSE and MAE scores than a DL model prevalent in precipitation downscaling and outperform a state-of-the-art dynamical weather model. Moreover, by evaluating the performance of our model under various data formulation strategies, for the training and test sets, we show that there is enough data for our deep learning approach to output robust, high-quality results across seasons and varying regions.

A Time Series Weather Radar Simulator Based on High-Resolution Atmospheric Models

2008 ◽  
Vol 25 (2) ◽  
pp. 230-243 ◽  
Author(s):  
B. L. Cheong ◽  
R. D. Palmer ◽  
M. Xue
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Time Series Data ◽  
Three Dimensional ◽  
Weather Radar ◽  
Series Data ◽  
Atmospheric Conditions ◽  
Moment Maps ◽  
Weather Model ◽  
Radar Simulator

Abstract A three-dimensional radar simulator capable of generating simulated raw time series data for a weather radar has been designed and implemented. The characteristics of the radar signals (amplitude, phase) are derived from the atmospheric fields from a high-resolution numerical weather model, although actual measured fields could be used. A field of thousands of scatterers is populated within the field of view of the virtual radar. Reflectivity characteristics of the targets are determined from well-known parameterization schemes. Doppler characteristics are derived by forcing the discrete scatterers to move with the three-dimensional wind field. Conventional moment-generating radar simulators use atmospheric conditions and a set of weighting functions to produce theoretical moment maps, which allow for the study of radar characteristics and limitations given particular configurations. In contrast to these radar simulators, the algorithm presented here is capable of producing sample-to-sample time series data that are collected by a radar system of virtually any design. Thus, this new radar simulator allows for the test and analysis of advanced topics, such as phased array antennas, clutter mitigation schemes, waveform design studies, and spectral-based methods. Limited examples exemplifying the usefulness and flexibility of the simulator will be provided.

scholarly journals Application of a high-resolution weather model in the area of the western Gulf of Corinth for the troposhperic correction of interferometric synthetic aperture radar (InSAR) observations

2019 ◽  
Author(s):  
Νικόλαος Ρουκουνάκης
Keyword(s):  
Water Vapor ◽  
High Resolution ◽  
Synthetic Aperture Radar ◽  
Precise Point Positioning ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Gulf Of Corinth ◽  
Weather Model ◽  
Point Positioning ◽  
Aperture Radar

Το αντικείμενο της διδακτορικής διατριβής είναι η ανάπτυξη μίας καινοτόμου μεθοδολογίας για την αφαίρεση της τροποσφαιρικής επίδρασης από εφαρμογές διαστημικής γεωδαισίας (GNSS και InSAR), οι οποίες αποτελούν σημαντικά εργαλεία για την παρακολούθηση περιβαλλοντικών παραμέτρων όπου απαιτείται υψηλή ακρίβεια ανίχνευσης (της τάξεως των χιλιοστών του μέτρου), όπως για παράδειγμα η μέτρηση επιφανειακών μετατοπίσεων του φλοιού της γης εξαιτίας τεκτονικών φαινομένων. Η τροπόσφαιρα εισαγάγει μια καθυστέρηση στο ηλεκτρομαγνητικό σήμα, η οποία διορθώνεται μερικώς (μόνο για τα GNSS), με την χρήση εξειδικευμένων τροποσφαιρικών μοντέλων. Επιπροσθέτως, η ατμοσφαιρική διαστρωμάτωση και οι έντονες χωροχρονικές διακυμάνσεις των υδρατμών μέσα σε αυτήν παράγουν ένα πρόσθετο «θόρυβο» στην παραμόρφωση του εδάφους που υπολογίζεται με την μεθοδολογία της συμβολομετρίας (InSAR). Επομένως, η γνώση των τροποσφαιρικών παραμέτρων κατά μήκος του μέσου διάδοσης μπορεί να χρησιμοποιηθεί για τον υπολογισμό και την ελαχιστοποίηση της επίδραση του θορύβου αυτού, έτσι ώστε το εναπομένον σήμα να περιγράφει την παραμόρφωση, ως επί το πλείστον, λόγω τεκτονικών ή άλλων γεωφυσικών διεργασιών. Ο πρωταρχικός στόχος της παρούσας διδακτορικής διατριβής είναι η σύζευξη της κατακόρυφης συνιστώσας των μετρήσεων GNSS υψηλής ακρίβειας (Precise Point Positioning), με τα δεδομένα εξόδου ενός μετεωρολογικού μοντέλου υψηλής ανάλυσης (WRF), ώστε να εξακριβωθεί η εγκυρότητα των αποτελεσμάτων και να παραμετροποιηθεί κατάλληλα το μοντέλο. Ταυτόχρονα, η τρισδιάστατη «τομογραφία» της τροπόσφαιρας που προκύπτει, μας επιτρέπει την ανάκτηση, με μεγαλύτερη ακρίβεια, του συνολικού ποσοστού των υδρατμών στην κατακόρυφη στήλη (Integrated Water Vapor ή IWV) από τα τροποσφαιρικά δεδομένα των μετρήσεων, μετατρέποντας έτσι, δυνητικά, ένα επίγειο δίκτυο δεκτών GNSS σε μετεωρολογικό προγνωστικό εργαλείο. Επιπλέον, η μελέτη επεκτείνεται στην διόρθωση της τροποσφαιρικής επίδρασης σε συμβολογραφήματα από περιοδικές λήψεις InSAR, κατά την ίδια περίοδο, για την περιοχή του Δυτικού Κορινθιακού Κόλπου. Κατ’ αυτόν τον τρόπο, η μεθοδολογία συνδυάζει σημειακές μετεωρολογικές παρατηρήσεις (GNSS) με τρισδιάστατα χωρικά μετεωρολογικά δεδομένα (WRF), για την παραγωγή αναλυτικών χαρτών ζενιθείας τροποσφαιρικής διόρθωσης (ZTD), που χρησιμοποιούνται για την αφαίρεση του θορύβου από τις απεικονίσεις InSAR.

scholarly journals Water vapour distribution at urban scale using high-resolution numerical weather model and spaceborne SAR interferometric data

2010 ◽  
Vol 10 (1) ◽  
pp. 121-132 ◽  
Author(s):  
E. Pichelli ◽  
R. Ferretti ◽  
D. Cimini ◽  
D. Perissin ◽  
M. Montopoli ◽  
...  
Keyword(s):  
High Resolution ◽  
Water Vapour ◽  
Mesoscale Model ◽  
Meteorological Data ◽  
Radar Data ◽  
Length Variation ◽  
Water Vapour Content ◽  
Semivariogram Analysis ◽  
Weather Model ◽  
Integrated Water Vapour

Abstract. The local distribution of water vapour in the urban area of Rome has been studied using both a high resolution mesoscale model (MM5) and Earth Remote Sensing-1 (ERS-1) satellite radar data. Interferometric Synthetic Aperture Radar (InSAR) techniques, after the removal of all other geometric effects, estimate excess path length variation between two different SAR acquisitions (Atmospheric Phase Screen: APS). APS are strictly related to the variations of the water vapour content along the radar line of sight. To the aim of assessing the MM5 ability to reproduce the gross features of the Integrated Water Vapour (IWV) spatial distribution, as a first step ECMWF IWV has been used as benchmark against which the high resolution MM5 model and InSAR APS maps have been compared. As a following step, the high resolution IWV MM5 maps have been compared with both InSAR and surface meteorological data. The results show that the high resolution IWV model maps compare well with the InSAR ones. Support to this finding is obtained by semivariogram analysis that clearly shows good agreement beside from a model bias.

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