There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Data Mining - Concepts and Techniques.

Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

A new bulk microphysical parameterization (BMP) has been developed for use with the Weather Research and Forecasting (WRF) Model or other mesoscale models. As compared with earlier single-moment BMPs, the new scheme incorporates a large number of improvements to both physical processes and computer coding, and it employs many techniques found in far more sophisticated spectral/bin schemes using lookup tables. Unlike any other BMP, the assumed snow size distribution depends on both ice water content and temperature and is represented as a sum of exponential and gamma distributions. Furthermore, snow assumes a nonspherical shape with a bulk density that varies inversely with diameter as found in observations and in contrast to nearly all other BMPs that assume spherical snow with constant density. The new scheme’s snow category was readily modified to match previous research in sensitivity experiments designed to test the sphericity and distribution shape characteristics. From analysis of four idea...

/pdf/explicit-forecasts-of-winter-precipitation-using-an-improved-200vx38jzm.pdf

Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization

The National Severe Storms Laboratory (NOAA-NSSL) and the Advanced Radar Research Center at the University of Oklahoma (OU-ARRC) are presently involved in the design, development and construction of a cylindrical polarimetric phased array radar (CPPAR) to demonstrate polarimetric capabilities for weather sensing within the Multi-function Phased Array Radar (MPAR) project. The bias in radar meteorological polarimetric variables is dependent on a number of parameters like cross-to-copolar gain ratio, integrated cross-polarization level, cross-to-copolar phase, copolar beam-width mismatch and beam pointing angle mismatch [1–2]. In the first part we present a preliminary system design for CPPAR, in the second part we present a procedure for polarimetric calibration using a target of opportunity, namely rain. Polarimetric calibration such as this one is extremely important for polarimetric phased arrays, since calibration needs be done on a beam by beam basis.

Polarimetric phased array weather radar: Concepts for polarimetric calibration

Remote measurements of cloud liquid water content (LWC) and characteristic droplet size (e.g., radar estimated size: RES) are required for quantifying potential aircraft icing hazard (Politovich, 1989; Politovich and Bernstein, 2002; Vivekanandan et al., 2001). During the 2004 Winter Icing and Storm Project (WISP04), research radars and radiometers were deployed at NCAR’s Marshall experimental site near Boulder, Colorado to evaluate remote sensing techniques for characterizing cloud icing conditions. The dataset included radar and radiometer measurements. The best case for single wavelength radar and twochannel radiometer-based retrievals was on March 1011, when a shallow, fairly uniform stratus cloud in the temperature range of ~ -5 to -15C was observed. High liquid water content and little ice was found in the cloud. This cloud began with some patches of relatively high reflectivity (~10-20 dBZ) and snow showers at the ground. It then evolved to low (<-10 dBZ) reflectivity with lots of liquid, as evidenced by numerous pilot reports of icing in the Denver area. Strong ground clutter at S-band limits the usefulness of the data for a dual-wavelength application. Nevertheless, Ka-band radar reflectivity and radiometer measurements were available for retrieving cloud characteristics. In this paper, we present retrievals for cloud LWC and RES from single frequency radar reflectivity and dual-channel radiometer measurements. Retrieval methods are reviewed in Section 2. The retrieval results and comparisons are presented in Section 3. A summary and discussion are given in Section 4.

Radar/radiometer combination to retrieve cloud characteristics for icing detection

[1] Radial wind is routinely measured by Doppler method, whereas winds transverse to the radar beam are measured using an interferometric technique in which three or more spaced antennas are used (i.e., the Spaced Antenna (SA) technique). In this paper, an interferometric technique is examined whereby a single antenna is used to measure both radial and transverse winds. Angular Interferometry (AI) determines transverse wind, and Range Interferometry (RI) determines radial wind. The cross-correlation of signals, received from different angles and from different ranges by a single antenna, is derived based on wave scattering from random fluctuations of refractive index. The radial and transverse wind components are estimated from the cross-correlation of signals received from different ranges and different directions. The theoretical standard deviation of the estimated wind is derived, and its dependence on spatial resolution, observation time, and turbulence is presented. The theory shows that AI requires small beam size to measure transverse wind accurately, contrary to the SA technique, whereas RI requires fine range resolution to perform well.

https://opensky.ucar.edu:/islandora/object/articles%3A8913/datastream/PDF/view

Angular and range interferometry to measure wind

It is cost-effective to use a polarimetric phased array radar (PPAR) network for multi-missions of weather and aviation surveillance as well as target detection. Considering the deficiency of a planar PPAR (PPPAR) in making polarimetric weather measurements, a concept of cylindrical polarimetric phased array radar is introduced to realize the dual mission capability. The Cylindrical Polarimetric Phased Array Radar (CPPAR) has many advantages, including azimuthal scan invariant beam characteristics and orthogonal polarization basis for all beam directions. A path to realize the CPPAR for multi-missions is planned.

A cylindrical polarimetric phased array radar concept — A path to multi-mission capability

This paper describes the design of a mobile Cylindrical Polarimetric Phased Array Radar (CPPAR) developed at the Advanced Radar Research Center (ARRC) The primary purpose of the radar is to prove the concept of a CPPAR and demonstrate its inherent polarimetric advantages Since these advantages become most apparent in the context of the polarimetric weather radar mission, the ability to make meaningful weather measurements with the system is desired With limited resources, a novel system has been designed which both can demonstrate the CPPAR concept and serve as a platform for general phased array research in the future

Guifu Zhang

Papers

Polarimetric phased array weather radar: Concepts for polarimetric calibration

Radar/radiometer combination to retrieve cloud characteristics for icing detection

Angular and range interferometry to measure wind

A cylindrical polarimetric phased array radar concept — A path to multi-mission capability

Cylindrical polarimetric phased array radar: Hardware design and mobile demonstrator