scholarly journals A Digital-Simulation Model for a Full-Polarized Microwave Radiometer System and Its Calibration

2021 ◽  
Vol 13 (23) ◽  
pp. 4888
Author(s):  
Jia Ding ◽  
Zhenzhan Wang ◽  
Yongqiang Duan ◽  
Xiaolin Tong ◽  
Hao Lu
Keyword(s):  
Error Analysis ◽  
Simulation Model ◽  
Input Signal ◽  
Digital Simulation ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Stokes Parameters ◽  
Calibration Matrix ◽  
Signal Models

A digital-correlation full-polarized microwave radiometer is an important passive remote sensor, as it can obtain the amplitude and phase information of an electromagnetic wave at the same time. It is widely used in the measurement of sea surface wind speed and direction. Its configuration is complicated, so the error analysis of the instrument is often difficult. This paper presents a full-polarized radiometer system model that can be used to analyze various errors, which include input signal models and a full-polarized radiometer (receiver) model. The input signal models are generated by WGN (white Gaussian noise), and the full-polarized radiometer model consists of an RF front-end model and digital back-end model. The calibration matrix is obtained by solving the overdetermined equations, and the output voltage is converted into Stokes brightness temperature through the calibration matrix. Then, we use the four Stokes parameters to analyze the sensitivity, linearity, and calibration residuals, from which the simulation model is validated. Finally, two examples of error analysis, including gain imbalance and quantization error, are given through a simulation model. In general, the simulation model proposed in this paper has good accuracy and can play an important role in the error analysis and pre-development of the fully polarized radiometer.

scholarly journals Satellite Microwave Surface Observations in Tropical Cyclones

2010 ◽  
Vol 138 (2) ◽  
pp. 421-437 ◽  
Author(s):  
Yves Quilfen ◽  
Bertrand Chapron ◽  
Jean Tournadre
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Rain Rate ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Surface Wind Speed ◽  
Microwave Measurements ◽  
Dual Frequency

Abstract Sea surface estimates of local winds, waves, and rain-rate conditions are crucial to complement infrared/visible satellite images in estimating the strength of tropical cyclones (TCs). Satellite measurements at microwave frequencies are thus key elements of present and future observing systems. Available for more than 20 years, passive microwave measurements are very valuable but still suffer from insufficient resolution and poor wind vector retrievals in the rainy conditions encountered in and around tropical cyclones. Scatterometer and synthetic aperture radar active microwave measurements performed at the C and Ku band on board the European Remote Sensing (ERS), the Meteorological Operational (MetOp), the Quick Scatterometer (QuikSCAT), the Environmental Satellite (Envisat), and RadarSat satellites can also be used to map the surface wind field in storms. Their accuracy is limited in the case of heavy rain and possible saturation of the microwave signals is reported. Altimeter dual-frequency measurements have also been shown to provide along-track information related to surface wind speed, wave height, and vertically integrated rain rate at about 6-km resolution. Although limited for operational use by their dimensional sampling, the dual-frequency capability makes altimeters a unique satellite-borne sensor to perform measurements of key surface parameters in a consistent way. To illustrate this capability two Jason-1 altimeter passes over Hurricanes Isabel and Wilma are examined. The area of maximum TC intensity, as described by the National Hurricane Center and by the altimeter, is compared for these two cases. Altimeter surface wind speed and rainfall-rate observations are further compared with measurements performed by other remote sensors, namely, the Tropical Rainfall Measuring Mission instruments and the airborne Stepped Frequency Microwave Radiometer.

A Coupled-Pixel Model (CPM) Atmospheric Retrieval Algorithm for High-Resolution Imagers

2015 ◽  
Vol 32 (10) ◽  
pp. 1866-1879 ◽  
Author(s):  
Mary Morris ◽  
Christopher S. Ruf
Keyword(s):  
Wind Speed ◽  
Rain Rate ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Low Frequency ◽  
Surface Wind Speed ◽  
Retrieval Algorithm ◽  
Single Column ◽  
Simplifying Assumptions ◽  
Cross Track

AbstractLow-frequency passive microwave observations allow for oceanic remote sensing of surface wind speed and rain rate from spaceborne and airborne platforms. For most instruments, the modeling of contributions of rain absorption and reemission in a particular field of view is simplified by the observing geometry. However, the simplifying assumptions that can be applied in most applications are not always valid for the scenes that the airborne Hurricane Imaging Radiometer (HIRAD) regularly observes. Collocated Stepped Frequency Microwave Radiometer (SFMR) and HIRAD observations of Hurricane Earl (2010) indicate that retrieval algorithms based on the usual simplified model, referred to here as the decoupled-pixel model (DPM), are not able to resolve two neighboring rainbands at the edge of HIRAD’s swath. The DPM does not allow for the possibility that a single column of atmosphere can affect the observations at multiple cross-track positions. This motivates the development of a coupled-pixel model (CPM) that is developed and tested in this paper. Simulated observations as well as HIRAD’s observations of Hurricane Earl (2010) are used to test the CPM algorithm. Key to the performance of the CPM algorithm is its ability to deconvolve the cross-track scene, as well as unscramble the signatures of surface wind speed and rain rate in HIRAD’s observations. While the CPM approach was developed specifically for HIRAD, other sensors could employ this method in similar complicated observing scenarios.

scholarly journals A Comparative Assessment of Surface Wind Speed and Sea Surface Temperature over the Indian Ocean by TMI, MSMR, and ERA-40

2007 ◽  
Vol 24 (6) ◽  
pp. 1131-1142 ◽  
Author(s):  
Anant Parekh ◽  
Rashmi Sharma ◽  
Abhijit Sarkar
Keyword(s):  
Wind Speed ◽  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Wind Speeds ◽  
Low Wind Speeds

A 2-yr (June 1999–June 2001) observation of ocean surface wind speed (SWS) and sea surface temperature (SST) derived from microwave radiometer measurements made by a multifrequency scanning microwave radiometer (MSMR) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is compared with direct measurements by Indian Ocean buoys. Also, for the first time SWS and SST values of the same period obtained from 40-yr ECMWF Re-Analysis (ERA-40) have been evaluated with these buoy observations. The SWS and SST are shown to have standard deviations of 1.77 m s−1 and 0.60 K for TMI, 2.30 m s−1 and 2.0 K for MSMR, and 2.59 m s−1 and 0.68 K for ERA-40, respectively. Despite the fact that MSMR has a lower-frequency channel, larger values of bias and standard deviation (STD) are found compared to those of TMI. The performance of SST retrieval during the daytime is found to be better than that at nighttime. The analysis carried out for different seasons has raised an important question as to why one spaceborne instrument (TMI) yields retrievals with similar biases during both pre- and postmonsoon periods and the other (MSMR) yields drastically different results. The large bias at low wind speeds is believed to be due to the poorer sensitivity of microwave emissivity variations at low wind speeds. The extreme SWS case study (cyclonic condition) showed that satellite-retrieved SWS captured the trend and absolute magnitudes as reflected by in situ observations, while the model (ERA-40) failed to do so. This result has direct implications on the real-time application of satellite winds in monitoring extreme weather events.

scholarly journals Examination of Surface Wind Asymmetry in Tropical Cyclones over the Northwest Pacific Ocean Using SMAP Observations

2019 ◽  
Vol 11 (22) ◽  
pp. 2604 ◽  
Author(s):  
Ziyao Sun ◽  
Biao Zhang ◽  
Jun A. Zhang ◽  
William Perrie
Keyword(s):  
Wind Speed ◽  
Wind Shear ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Relative Strength ◽  
Northwest Pacific ◽  
Translation Speed ◽  
Northwest Pacific Ocean ◽  
Maximum Wind

Tropical cyclone (TC) surface wind asymmetry is investigated by using wind data acquired from an L-band passive microwave radiometer onboard the NASA Soil Moisture Active Passive (SMAP) satellite between 2015 and 2017 over the Northwest Pacific (NWP) Ocean. The azimuthal asymmetry degree is defined as the factor by which the maximum surface wind speed is greater than the mean wind speed at the radius of the maximum wind (RMW). We examined storm motion and environmental wind shear effects on the degree of TC surface wind asymmetry under different intensity conditions. Results show that the surface wind asymmetry degree significantly decreases with increasing TC intensity, but increases with increasing TC translation speed, for tropical storm and super typhoon strength TCs; whereas no such relationship is found for typhoon and severe typhoon strength TCs. However, the degree of surface wind asymmetry increases with increasing wind shear magnitude for all TC intensity categories. The relative strength between the storm translation speed and the wind shear magnitude has the potential to affect the location of the maximum wind speed. Moreover, the maximum degree of wind asymmetry is found when the direction of the TC motion is nearly equal to the direction of the wind shear.

Error Analysis for Metering Current Transformer with DC Bias

2013 ◽  
Vol 773 ◽  
pp. 58-61
Author(s):  
Shi Hai Yang ◽  
Ke Qi Zhang ◽  
Zhong Zhuang ◽  
Min Rui Xu ◽  
Min Jian Cao ◽  
...  
Keyword(s):  
Error Analysis ◽  
Power System ◽  
Simulation Model ◽  
Digital Simulation ◽  
Current Transformer ◽  
Angle Error ◽  
Ratio Error ◽  
Dc Bias ◽  
Simulation Results ◽  
Different Levels

DC bias widely exists in power system. In order to analyze its influence on metering current transformer (MCT), a new digital simulation model based on Preisach theory is constructed firstly. Using this digital model, the ratio error and angle error of a running MCT are calculated under different levels of DC bias. Simulation results show that the current DC bias in power system has only little influence on the error of MCT.

scholarly journals Observational Undersampling in Tropical Cyclones and Implications for Estimated Intensity

2012 ◽  
Vol 140 (3) ◽  
pp. 825-840 ◽  
Author(s):  
Eric W. Uhlhorn ◽  
David S. Nolan
Keyword(s):  
Wind Speed ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Maximum Wind ◽  
Storm Intensity ◽  
Stepped Frequency ◽  
Hurricane Isabel ◽  
Observing System Simulation Experiment ◽  
Averaged Model

Abstract The maximum surface wind speed is an important parameter for tropical cyclone operational analysis and forecasting, since it defines the intensity of a cyclone. Operational forecast centers typically refer the wind speed to a maximum 1- or 10-min averaged value. Aircraft reconnaissance provides measurements of surface winds; however, because of the large variation of winds in the eyewall, it remains unclear to what extent observing the maximum wind is limited by the sampling pattern. Estimating storm intensity as simply the maximum of the observed winds is generally assumed by forecasters to underestimate the true storm intensity. The work presented herein attempts to quantify this difference by applying a methodology borrowed from the observing system simulation experiment concept, in which simulated “observations” are drawn from a numerical model. These “observations” may then be compared to the actual peak wind speed of the simulation. By sampling a high-resolution numerical simulation of Hurricane Isabel (2003) with a virtual aircraft equipped with a stepped-frequency microwave radiometer flying a standard “figure-four” pattern, the authors find that the highest wind observed over a flight typically underestimates the 1-min averaged model wind speed by 8.5% ± 1.5%. In contrast, due to its corresponding larger spatial scale, the 10-min averaged maximum wind speed is far less underestimated (1.5% ± 1.7%) using the same sampling method. These results support the National Hurricane Center’s practice, which typically assumes that the peak 1-min wind is somewhat greater than the highest observed wind speed over a single reconnaissance aircraft mission.

scholarly journals Stepped Frequency Microwave Radiometer Wind-Speed Retrieval Improvements

2019 ◽  
Vol 11 (3) ◽  
pp. 214 ◽  
Author(s):  
Joseph Sapp ◽  
Suleiman Alsweiss ◽  
Zorana Jelenak ◽  
Paul Chang ◽  
James Carswell
Keyword(s):  
Wind Speed ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Ground Truth ◽  
Surface Wind Speed ◽  
Critical Parameters ◽  
Analysis Model ◽  
Operational Model ◽  
Research Aircraft ◽  
Ocean Surface Wind

With the operational deployment of the *SFMR, hurricane reconnaissance and research aircraft provide near real-time observations of the 10 m ocean-surface wind-speed both within and around tropical cyclones. Hurricane specialists use these data to assist in determining wind radii and maximum sustained winds—critical parameters for determining and issuing watches and warnings. These observations are also used for post-storm analysis, model validation, and ground truth for aircraft- and satellite-based wind sensors. We present observations on the current operational wind-speed and rain-rate *SFMR retrieval procedures in the tropical cyclone environment and propose suggestions to improve them based on observed wind-speed biases. Using these new models in the *SFMR retrieval process, we correct an approximate 10% low bias in the wind-speed retrievals from 15 m / s –45 m / s with respect to *GPS dropwindsondes. In doing so, we eliminate the rain-contaminated wind-speed retrievals below 45/ h at tropical storm- and hurricane-force speeds present in the current operational model. We also update the *SFMR *RTM to include recent updates to smooth-ocean emissivity and atmospheric opacity models. All corrections were designed such that no changes to the current *SFMR calibration procedures are required.

A preliminary assessment of the sea surface wind speed production of HY-2 scanning microwave radiometer

2013 ◽  
Vol 33 (1) ◽  
pp. 114-119 ◽  
Author(s):  
Xiaoqi Huang ◽  
Jianhua Zhu ◽  
Mingsen Lin ◽  
Yili Zhao ◽  
He Wang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Preliminary Assessment ◽  
Sea Surface Wind Speed ◽  
Sea Surface Wind

Validation of year-round Stepped Frequency Microwave Radiometer (SFMR) measurement of sea surface wind speed around the Korean Peninsula during 2018-2019

2020 ◽  
Author(s):  
Ji-Hyoung Kim ◽  
Chulkyu Lee ◽  
Hyojin Yang ◽  
Suengpil Jung ◽  
Heejong Ko ◽  
...  
Keyword(s):  
Wind Speed ◽  
Korean Peninsula ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Sea Surface Wind Speed ◽  
Sea Surface Wind ◽  
Research Aircraft ◽  
Stepped Frequency

<p>Korea Meteorological Administration/National Institute of Meteorological Sciences (KMA/NIMS) has adopted KMA/NIMS Atmospheric Research Aircraft (NARA) since the beginning of 2018. NARA has performed year-round airborne measurement of Sea surface Wind Speed (SWS) using Stepped Frequency Microwave Radiometer (SFMR) during 2018-2019. Total 84 flights of SFMR SWS measurements during this period were analyzed by comparing to concurrent measurements of KMA marine buoy. SFMR SWS around the Korean peninsula during the same period was 6.34±4.95 m s<sup>-1</sup>. SFMR SWS was appeared to be 12.3% larger than those of KMA marine buoy and mean Bias Difference (BD) was 0.69 m s<sup>-1</sup>. However, SFMR SWS and KMA marine buoy were correlated well to each other (R<sup>2</sup>~0.80). The BD was decreased with increasing SWS, this agreed well with results of previous studies (Klotz et al., 2014), however, SFMR SWS measurement showed still reliable even in low SWS environment (< 15 m s<sup>-1</sup>). For more accurate measurement of SFMR SWS, parameters such as the flight altitude (swath area) and pre-input values (sea surface temperature, salinity) should also be considered. Also, this result can be a comparison reference for those of satellite-borne sensors, as well.</p>

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