scholarly journals Non-linear flow modelling of a Martian Lobate Debris Apron

2019 ◽  
Vol 65 (254) ◽  
pp. 889-899 ◽  
Author(s):  
Louise Steffensen Schmidt ◽  
Christine Schøtt Hvidberg ◽  
Jung Rack Kim ◽  
Nanna Bjørnholt Karlsson
Keyword(s):  
High Resolution ◽  
Inverse Method ◽  
Radar Data ◽  
Creep Parameter ◽  
Accumulation Rates ◽  
Linear Flow ◽  
Water Ice ◽  
Small Water ◽  
Flow Modelling ◽  
Flow Features

AbstractThe Martian mid-latitudes contain numerous small water-ice deposits, collectively termed viscous flow features (VFFs). The shape and topography of the deposits contain information on their past flow history and formation process. In order to access this information, it is imperative to get information on their deformational properties. Here we use a high-resolution digital topography map and ice-penetrating radar data in combination with an inverse method to constrain the deformational properties of a lobate debris apron, a class of VFF, in the southern hemisphere of Mars. We find that while the creep parameter and accumulation rates are not well constrained in absolute values, their ratio is robust. We also find that the creep exponent is most likely n ≤ 3.

An Efficient Dual-Resolution Approach for Ensemble Data Assimilation and Tests with Simulated Doppler Radar Data

2008 ◽  
Vol 136 (3) ◽  
pp. 945-963 ◽  
Author(s):  
Jidong Gao ◽  
Ming Xue
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Radial Velocity ◽  
Computational Cost ◽  
Radar Data ◽  
Horizontal Resolution ◽  
Velocity Data ◽  
Background Error ◽  
Cross Covariance ◽  
Radial Velocity Data

Abstract A new efficient dual-resolution (DR) data assimilation algorithm is developed based on the ensemble Kalman filter (EnKF) method and tested using simulated radar radial velocity data for a supercell storm. Radar observations are assimilated on both high-resolution and lower-resolution grids using the EnKF algorithm with flow-dependent background error covariances estimated from the lower-resolution ensemble. It is shown that the flow-dependent and dynamically evolved background error covariances thus estimated are effective in producing quality analyses on the high-resolution grid. The DR method has the advantage of being able to significantly reduce the computational cost of the EnKF analysis. In the system, the lower-resolution ensemble provides the flow-dependent background error covariance, while the single-high-resolution forecast and analysis provides the benefit of higher resolution, which is important for resolving the internal structures of thunderstorms. The relative smoothness of the covariance obtained from the lower 4-km-resolution ensemble does not appear to significantly degrade the quality of analysis. This is because the cross covariance among different variables is of first-order importance for “retrieving” unobserved variables from the radar radial velocity data. For the DR analysis, an ensemble size of 40 appears to be a reasonable choice with the use of a 4-km horizontal resolution in the ensemble and a 1-km resolution in the high-resolution analysis. Several sensitivity tests show that the DR EnKF system is quite robust to different observation errors. A 4-km thinned data resolution is a compromise that is acceptable under the constraint of real-time applications. A data density of 8 km leads to a significant degradation in the analysis.

scholarly journals A Microphysical Bulk Formulation Based on Scaling Normalization of the Particle Size Distribution. Part I: Description

2005 ◽  
Vol 62 (12) ◽  
pp. 4206-4221 ◽  
Author(s):  
Wanda Szyrmer ◽  
Stéphane Laroche ◽  
Isztar Zawadzki
Keyword(s):  
Particle Size ◽  
High Resolution ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Numerical Models ◽  
Radar Data ◽  
Retrieval Algorithm ◽  
Microphysical Processes ◽  
The Moment ◽  
Microphysical Parameterization

Abstract The authors address the problem of optimization of the microphysical information extracted from a simulation system composed of high-resolution numerical models and multiparameter radar data or other available measurements. As a tool in the exploration of this question, a bulk microphysical scheme based on the general approach of scaling normalization of particle size distribution (PSD) is proposed. This approach does not rely on a particular functional form imposed on the PSD and naturally leads to power-law relationships between the PSD moments providing an accurate and compact PSD representation. To take into account the possible evolution of the shape/curvature of the distribution, ignored within standard one- and two-moment microphysical schemes, a new three-moment scheme based on the two-moment scaling normalization is proposed. The methodology of the moment retrieval included in the three-moment scheme can also be useful as a retrieval algorithm combining different remote sensing observations. The developed bulk microphysical scheme presents a unified formulation for microphysical parameterization using one, two, or three independent moments, suitable in the context of data assimilation. The effectiveness of the scheme with different combinations of independent moments is evaluated by comparison with a very high resolution spectral model within a 1D framework on representative microphysical processes: rain sedimentation and evaporation.

scholarly journals Investigating Hector Convective Development and Microphysical Structure Using High-Resolution Model Simulations, Ground-Based Radar Data, and TRMM Satellite Data

2014 ◽  
Vol 71 (4) ◽  
pp. 1353-1370 ◽  
Author(s):  
Sabrina Gentile ◽  
Rossella Ferretti ◽  
Frank Silvio Marzano
Keyword(s):  
High Resolution ◽  
Conceptual Model ◽  
Vertical Structure ◽  
Mesoscale Model ◽  
Tropical Rainfall Measuring Mission ◽  
Sea Breeze ◽  
Radar Data ◽  
Full Life Cycle ◽  
Resolution Model ◽  
High Resolution Model

Abstract One event of a tropical thunderstorm typically observed in northern Australia, known as Hector, is investigated using high-resolution model output from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) observations from a ground-based weather radar located in Berrimah (Australia) and data from the Tropical Rainfall Measuring Mission (TRMM) satellite. The analysis is carried out by tracking the full life cycle of Hector from prestorm stage to the decaying stage. In both the prestorm stage, characterized by nonprecipitating cells, and the triggering stage, when the Hector storm is effectively initiated, an analysis is performed with the aid of high-spatial-and-temporal-resolution MM5 output and the Berrimah ground-based radar imagery. During the mature (“old”) stage of Hector, considering the conceptual model for tropical convection suggested by R. Houze, TRMM Microwave Imager satellite-based data were added to ground-based radar data to analyze the storm vertical structure (dynamics, thermodynamics, and hydrometeor contents). Model evaluation with respect to observations (radar reflectivity and TRMM data) suggests that MM5 performed fairly well in reproducing the dynamics of Hector, providing support to the assertion that the strength of convection, in terms of vertical velocity, largely contributes to the vertical distribution of hydrometeors. Moreover, the stages of the storm and its vertical structure display good agreement with Houze’s aforementioned conceptual model. Finally, it was found that the most important triggering mechanisms for this Hector event are topography, the sea breeze, and a gust front produced by previous convection.

Synergy of very high resolution optical and radar data for object-based olive grove mapping

2011 ◽  
Vol 25 (6) ◽  
pp. 971-989 ◽  
Author(s):  
Jan Peters ◽  
Frieke Van Coillie ◽  
Toon Westra ◽  
Robert De Wulf
Keyword(s):  
High Resolution ◽  
Radar Data ◽  
Olive Grove ◽  
Object Based ◽  
Very High

scholarly journals Spatial-Temporal Rainfall Models Based On Poisson Cluster Processes

2021 ◽  
Author(s):  
Nanda R Aryal ◽  
Owen D Jones
Keyword(s):  
High Resolution ◽  
Method Of Moments ◽  
Approximate Bayesian Computation ◽  
Radar Data ◽  
Bayesian Computation ◽  
Central Importance ◽  
Temporal Models ◽  
Simulated Method Of Moments ◽  
Approximate Bayesian ◽  
Poisson Cluster

Abstract We fit stochastic spatial-temporal models to high-resolution rainfall radar data using Approximate Bayesian Computation (ABC). As a baseline we fit a model of Cox, Isham and Northrop, which we then generalise in a variety of ways. Of central importance is the use of ABC, as it is not possible to fit models of this complexity using previous approaches. We also introduce the use of Simulated Method of Moments (SMM) to initialise the ABC fit.

scholarly journals A high-resolution synthetic bed elevation grid of the Antarctic continent

2016 ◽  
Author(s):  
Felicity S. Graham ◽  
Jason L. Roberts ◽  
Ben K. Galton-Fenzi ◽  
Duncan Young ◽  
Donald Blankenship ◽  
...  
Keyword(s):  
High Resolution ◽  
Ice Sheet ◽  
Radar Data ◽  
Detailed Knowledge ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Bed Elevation ◽  
Antarctic Continent ◽  
Ice Sheet Dynamics ◽  
The Antarctic

Abstract. Digital elevation models of Antarctic bed topography are heavily smoothed and interpolated onto low-resolution (> 1 km) grids as our current observed topography data are generally sparsely and unevenly sampled. This issue has potential implications for numerical simulations of ice-sheet dynamics, especially in regions prone to instability where detailed knowledge of the topography, including fine-scale roughness, is required. Here, we present a high-resolution (100 m) synthetic bed elevation terrain for the whole Antarctic continent. The synthetic bed surface preserves topographic roughness characteristics of airborne and ground-based ice-penetrating radar data from the Bedmap1 compilation and the ICECAP consortium. Broad-scale features of the Antarctic landscape are incorporated using a low-pass filter of the Bedmap2 bed-elevation data. Although not intended as a substitute for Bedmap2, the simulated bed elevation terrain has applicability in high-resolution ice-sheet modelling studies, including investigations of the interaction between topography, ice-sheet dynamics, and hydrology, where processes are highly sensitive to bed elevations. The data are available for download at the Australian Antarctic Data Centre (doi:10.4225/15/57464ADE22F50).

scholarly journals A Comparison Between Global Satellite Mapping of Precipitation Data and High-Resolution Radar Data – A Case Study of Localized Torrential Rainfall over Japan

2021 ◽  
Vol 16 (4) ◽  
pp. 786-793
Author(s):  
Yoshiaki Hayashi ◽  
Taichi Tebakari ◽  
Akihiro Hashimoto ◽  
◽  
Keyword(s):  
High Resolution ◽  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Radar Data ◽  
Rain Gauge ◽  
Hourly Rainfall ◽  
The Difference ◽  
Microwave Imager ◽  
Satellite Mapping

This paper presents a case study comparing the latest algorithm version of Global Satellite Mapping of Precipitation (GSMaP) data with C-band and X-band Multi-Parameter (MP) radar as high-resolution rainfall data in terms of localized heavy rainfall events. The study also obliged us to clarify the spatial and temporal resolution of GSMaP data using high-accuracy ground-based radar, and evaluate the performance and reporting frequency of GSMaP satellites. The GSMaP_Gauge_RNL data with less than 70 mm/day of daily rainfall was similar to the data of both radars, but the GSMaP_Gauge_RNL data with over 70 mm/day of daily rainfall was not, and the calibration by rain-gauge data was poor. Furthermore, both direct/indirect observations by the Global Precipitation Measurement/Microwave Imager (GPM/GMI) and the frequency thereof (once or twice) significantly affected the difference between GPM/GMI data and C-band radar data when the daily rainfall was less than 70 mm/day and the hourly rainfall was less than 20 mm/h. Therefore, it is difficult for GSMaP_Gauge to accurately estimate localized heavy rainfall with high-density particle precipitation.

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