The Effect of Phase-Correlated Returns and Spatial Smoothing on the Accuracy of Radar Refractivity Retrievals

Nicol, John; Illingworth, Anthony J.

doi:10.1175/jtech-d-12-00077.1

Cited by 13 publications

(23 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The final component of the refractivity term (proportional to d gate Dn) may be identified as a refractivity target location error, a new term analogous to the Tx target location error. This error can also be significant for klystron systems (Nicol and Illingworth 2013). We shall later quantify the magnitude of these terms in section 5.…”

Section: Influence Of Frequency Changes On Phase Measurements In Termmentioning

confidence: 99%

“…It is apparent from (7) (8), prior to the standard refractivity retrieval processing (Nicol et al 2008):…”

Section: Influence Of Local Oscillator Frequency Changesmentioning

confidence: 99%

“…The radial extent of returns from highly reflective targets is largely determined by the filtering applied in the radar receiver and may span several range gates (Nicol and Illingworth 2013); we shall refer to these returns as spreading targets.…”

Section: Quantifying the Accuracy Of Lo Frequency Changesmentioning

confidence: 99%

“…The phase change difference from spreading targets will be close to zero for the radar considered here, as the LO frequency is set to match the transmitter frequency immediately prior to each scan through fine adjustments of the NCO, so that Df Tx ' Df LO . Because of this, Nicol and Illingworth (2013) established that spreading targets may be recognized by the phase correlation between adjacent range gates; values exceeding 0.95 when averaged over the 288 individual PPI scans for a single dry day (12 December 2007) identified 1053 range-gate pairs associated with spreading targets.…”

Section: Quantifying the Accuracy Of Lo Frequency Changesmentioning

confidence: 99%

“…In this paper, we present an expression for the measured phase change in terms of range (rather than sampling and propagation delays) when there are changes in both the transmitter and local oscillator (LO) frequencies (originally given by Nicol et al 2008). This expression makes it clear that for the mismatch term the source of phase change error is, in fact, related to target location uncertainty.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Quantifying Errors due to Frequency Changes and Target Location Uncertainty for Radar Refractivity Retrievals

Nicol

Illingworth

Darlington

et al. 2013

Journal of Atmospheric and Oceanic Technology

Self Cite

View full text Add to dashboard Cite

Radar refractivity retrievals can capture near-surface humidity changes, but noisy phase changes of the ground clutter returns limit the accuracy for both klystron-and magnetron-based systems. Observations with a C-band (5.6 cm) magnetron weather radar indicate that the correction for phase changes introduced by local oscillator frequency changes leads to refractivity errors no larger than 0.25 N units: equivalent to a relative humidity change of only 0.25% at 208C. Requested stable local oscillator (STALO) frequency changes were accurate to 0.002 ppm based on laboratory measurements. More serious are the random phase change errors introduced when targets are not at the range-gate center and there are changes in the transmitter frequency (Df Tx ) or the refractivity (DN). Observations at C band with a 2-ms pulse show an additional 668 of phase change noise for a Df Tx of 190 kHz (34 ppm); this allows the effect due to DN to be predicted. Even at S band with klystron transmitters, significant phase change noise should occur when a large DN develops relative to the reference period [e.g., ;558 when DN 5 60 for the Next Generation Weather Radar (NEXRAD) radars]. At shorter wavelengths (e.g., C and X band) and with magnetron transmitters in particular, refractivity retrievals relative to an earlier reference period are even more difficult, and operational retrievals may be restricted to changes over shorter (e.g., hourly) periods of time. Target location errors can be reduced by using a shorter pulse or identified by a new technique making alternate measurements at two closely spaced frequencies, which could even be achieved with a dual-pulse repetition frequency (PRF) operation of a magnetron transmitter.

show abstract

Section: Influence Of Frequency Changes On Phase Measurements In Termmentioning

confidence: 99%

“…It is apparent from (7) (8), prior to the standard refractivity retrieval processing (Nicol et al 2008):…”

Section: Influence Of Local Oscillator Frequency Changesmentioning

confidence: 99%

Section: Quantifying the Accuracy Of Lo Frequency Changesmentioning

confidence: 99%

Section: Quantifying the Accuracy Of Lo Frequency Changesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quantifying Errors due to Frequency Changes and Target Location Uncertainty for Radar Refractivity Retrievals

Nicol

Illingworth

Darlington

et al. 2013

Journal of Atmospheric and Oceanic Technology

Self Cite

View full text Add to dashboard Cite

show abstract

The potential of 1 h refractivity changes from an operational C‐band magnetron‐based radar for numerical weather prediction validation and data assimilation†

Nicol

Illingworth

Bartholomew

2014

Quart J Royal Meteoro Soc

Self Cite

View full text Add to dashboard Cite

Refractivity changes ( N) derived from radar ground clutter returns serve as a proxy for near-surface humidity changes (1 N unit ≡ 1% relative humidity at 20• C). Previous studies have indicated that better humidity observations should improve forecasts of convection initiation. A preliminary assessment of the potential of refractivity retrievals from an operational magnetron-based C-band radar is presented. The increased phase noise at shorter wavelengths, exacerbated by the unknown position of the target within the 300 m gate, make it difficult to obtain absolute refractivity values, so we consider the information in 1 h changes. These have been derived to a range of 30 km with a spatial resolution of ∼4 km; the consistency of the individual estimates (within each 4 km × 4 km area) indicates that N errors are about 1 N unit, in agreement with in situ observations. Measurements from an instrumented tower on summer days show that the 1 h refractivity changes up to a height of 100 m remain well correlated with near-surface values. The analysis of refractivity as represented in the operational Met Office Unified Model at 1.5, 4 and 12 km grid lengths demonstrates that, as model resolution increases, the spatial scales of the refractivity structures improve. It is shown that the magnitude of refractivity changes is progressively underestimated at larger grid lengths during summer. However, the daily time series of 1 h refractivity changes reveal that, whereas the radar-derived values are very well correlated with the in situ observations, the high-resolution model runs have little skill in getting the right values of N in the right place at the right time. This suggests that the assimilation of these radar refractivity observations could benefit forecasts of the initiation of convection.

show abstract

Comparison of real‐time refractivity measurements by radar with automatic weather stations, AROME‐WMED and WRF forecast simulations during SOP1 of the HyMeX campaign

Besson

Caumont

Goulet

et al. 2016

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

International audienceWeather radars, originally designed to detect and quantify precipitation, can be used to estimate and map the refractivity at low level, a proxy for humidity. As highlighted by previous studies, this presents a definite meteorological interest, both for numerical weather prediction and for atmospheric process studies. Recent works have given keys to perform high-accuracy measurements over operational radar without decreasing the quality of reflectivity and Doppler wind classical measurements, and the retrieval of radar refractivity is now performed in real time with the Météo-France ARAMIS (Application Radar à la Météorologie Infra-Synoptique) operational network.Taking advantage of the Hydrological cycle in Mediterranean eXperiment (HyMeX) field campaign (September-November 2012), refractivity measured by a few radars located in South-East France has been compared with in-situ measurement by Automatic Weather Stations (AWSs), and correlation between these two independent observations is quite good, in particular with a high quality of the diurnal cycle and during the pre-convection period measurement by the radar.To go further in the evaluation of the usefulness of such product, we compared refractivity derived from radar measurements and from two different kinds of models: the numerical prediction model Applications de la Recherche à l'Opérationnel à Méso-Echelle – Western MEDiterranean (AROME-WMED) using a 2.5 km resolution grid mesh over southern France and a coarser resolution simulation (54x54 km) performed with the Weather Research and Forecasting (WRF) model which both ran in a forecasting mode during the HYMEX Special Observing Period 1. These two models give access to the variability of the modeling and thus enable to quantify the uncertainty of the refractivity modeling. The result of this comparison is generally fairly good, with a pattern of refractivity field similar to observations (AWS and radar), although obviously with locally strong differences.We finally illustrate the usefulness of refractivity mapping by radar by investigating a typical meteorological situation of a convective system observed during the HyMeX campaign

show abstract

The Effect of Phase-Correlated Returns and Spatial Smoothing on the Accuracy of Radar Refractivity Retrievals

Cited by 13 publications

References 9 publications

Quantifying Errors due to Frequency Changes and Target Location Uncertainty for Radar Refractivity Retrievals

Quantifying Errors due to Frequency Changes and Target Location Uncertainty for Radar Refractivity Retrievals

The potential of 1 h refractivity changes from an operational C‐band magnetron‐based radar for numerical weather prediction validation and data assimilation†

Comparison of real‐time refractivity measurements by radar with automatic weather stations, AROME‐WMED and WRF forecast simulations during SOP1 of the HyMeX campaign

Contact Info

Product

Resources

About