201201
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Evaluation of Radar Precipitation Estimates from the National Mosaic and Quantitative Precipitation Estimation System and the WSR-88D Precipitation Processing System over the Conterminous United States Wanru Wu, David Kitzmiller, Shaorong Wu Journal of Hydrometeorology 2011 This
study evaluated 24-hour, 6-hour, and 1-hour radar precipitation estimated
from the National Mosaic and Quantitative Precipitation Estimation System
(NMQ) and the WSR-88D Precipitation Processing System (PPS) over the
Conterminous(隣接地帯？) United States
(CONUS) for the warm season April-September, 2009 and the cool season October
2009-March 2010. Precipitation gauge observations from the Automated Surface
Observing System (ASOS) were used as the ground truth. Gridded StageIV multi-sensor precipitation estimates were applied
for supplementary verification. The comparison of the two systems consisted
of a series of analyses primarily including the linear correlation
coefficient (C.C.) and the root mean square error (RMSE) between the radar
precipitation estimates and the gauge observations, large precipitation
amount detection categorical scores, and the reliability of precipitation
amount distribution. Data stratified for the 12 CONUS River Forecast Centers
(RFCs) and for the cold rains events with bright-band effects were analyzed
additionally. Major results are 1) the linear C.C. of NMQ vs. ASOS are
generally higher than that of PPS vs. ASOS over CONUS, while the spatial
variations stratified by the RFCs may switch with seasons; 2) compared to the
precipitation distribution of ASOS, NMQ shows less deviation than PPS; 3) for
the cold rains verified against ASOS, NMQ has higher C.C. and PPS has lower
RMSE for 6 hours and higher RMSE for 1-hour cold rains; and 4) for the
precipitation detection categorical scores, either NMQ or PPS can be
superior, depending on the time interval and season. The verification against
StageIV gridded precipitation estimates showed that
NMQ consistently had higher correlations and lower biases than did PPS. Volume 0, Issue 0 ( ) pp. doi: http://dx.doi.org/10.1175/JHM-D-11-064.1 NMQ:たぶん合成レーダ PPS:単体レーダ ASOS:地上雨量 RFC:流域雨量 1)相関で見ると、合成レーダの方が単体レーダより精度が高い。ただし、流域にすると季節によって精度が逆転する場合がある。 2)地上降水の分布をみると、合成レーダの方は単体レーダより精度が低い。 3)冷たい雨を対象にすると、合成レーダは相関係数が高い。単体レーダは6時間ではRMSEが小さいが1時間では値が大きくなっている。 4)降雨探知はどちらも高い精度を示す。 格子雨量データを使った評価では合成レーダの精度が高かった。1/5’12
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Planck Weighted Transmittance and Correction of Solar Reflection for Broadband Infrared Satellite Channels Yong Chen, Fuzhong Weng, Yong Han, Quanhua Liu Journal of Atmospheric and Oceanic Technology Volume 0, Issue 0 ( ) pp. doi: http://dx.doi.org/10.1175/JTECH-D-11-00102.1 【おそらく】衛星観測において、日射が測器に入り込む影響を補正する手法について研究した。補正にはモデルを使う。輝度温度brightness
temperature、周波数【？】bandがヒット。1/6’12
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Classification of precipitation types during transitional winter weather using the RUC model and polarimetric radar retrievals Terry J. Schuur, Hyang-Suk Park, Alexander V. Ryzhkov, Heather D. Reeves JHM 2011 A new hydrometeor classification algorithm that combines thermodynamic output from the Rapid-Update-Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely solely on polarimetric radar observations by using thermodynamic information to help diagnose microphysical processes (such as melting or refreezing) that might occur aloft. This added information is especially important for transitional weather events where past studies have shown radar-only techniques to be deficient. The algorithm first uses vertical profiles of wet-bulb temperature derived from the RUC model output to provide a background precipitation classification type. According to a set of empirical rules, polarimetric radar data are then used to refine precipitation type categories when the observations are found to be consistent with the background classification.
Using data from the polarimetric KOUN WSR-88D radar, the algorithm is tested on a transitional winter storm event that produced a combination of rain, freezing rain, ice pellets, and snow as it passed over central Oklahoma on 30 November 2006 (Houser and Bluestein, 2011). Examples are presented where the presence of a radar bright band (suggesting an elevated warm layer) is observed immediately above a background classification of dry snow (suggesting the absence of an elevated warm layer in the model output). Overall, the results demonstrate the potential benefits of combining polarimetric radar data with thermodynamic information from numerical models, with model output providing widespread coverage and polarimetric radar data providing an observation-based modification of the derived precipitation type at closer ranges.
Volume 0, Issue 0 ( ) pp. doi: http://dx.doi.org/10.1175/JAMC-D-11-091.1
[Abstract] [PDF (2437 KB)] [Add to Favorites] 雨雪判別について、層状性の雲はよいが前線通過のような変化がある場合は、レーダだけでは難しいのでモデルの結果を組み合わせて判別の精度を高めた。1/4’12 まずレーダで分類し、モデルを使う。 雪の直上にブライトバンドが観測された（判別できた）。今回の結果は広域の情報を利用できるモデルと近くの詳細な情報知るレーダを組み合わせると判別に有利であることを示す。1/6’12 |
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Retrieval of Ice Cloud Optical Thickness and Effective Particle Size Using a Fast Infrared Radiative Transfer Model Chenxi Wang, Ping Yang, Bryan A. Baum, Steven Platnick, Andrew K. Heidinger, Yongxiang Hu, Robert E. Holz Journal of Applied Meteorology and Climatology Volume 50, Issue 11 (November 2011) pp. 2283-2297 doi: http://dx.doi.org/10.1175/JAMC-D-11-067.1 A computationally efficient radiative transfer model (RTM) is developed for the inference of ice cloud optical thickness and effective particle size from satellite-based infrared (IR) measurements and is aimed at potential use in operational cloud-property retrievals from multispectral satellite imagery. The RTM employs precomputed lookup tables to simulate the top-of-the-atmosphere (TOA) radiances (or brightness temperatures) at 8.5-, 11-, and 12-micro meter bands. For the clear-sky atmosphere, the optical thickness of each atmospheric layer resulting from gaseous absorption is derived from the correlated-k-distribution method. The cloud reflectance, transmittance, emissivity, and effective temperature are precomputed using the Discrete Ordinate Radiative Transfer model (DISORT). For an atmosphere containing a semitransparent ice cloud layer with a visible optical thickness τ smaller than 5, the TOA brightness temperature differences (BTDs) between the fast model and the more rigorous DISORT results are less than 0.1 K, whereas the BTDs are less than 0.01 K if τ is larger than 10. With the proposed RTM, the cloud optical and microphysical properties are retrieved from collocated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) in conjunction with the Modern Era Retrospective-Analysis for Research and Applications (MERRA) data. Comparisons between the retrieved ice cloud properties (optical thickness and effective particle size) based on the present IR fast model and those from the Aqua/MODIS operational collection-5 cloud products indicate that the IR retrievals are smaller. A comparison between the IR-retrieved ice water path (IWP) and CALIOP-retrieved IWP shows robust agreement over most of the IWP range. 1/13’12Abstract
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Monitoring of IR Clear-Sky Radiances over Oceans for SST (MICROS) Xingming Liang, Alexander Ignatov Journal of Atmospheric and Oceanic Technology Volume 28, Issue 10 (October 2011) pp. 1228-1242 doi: http://dx.doi.org/10.1175/JTECH-D-10-05023.1 リモセンの話。衛星NOAA,MetOPで晴天域を抽出。brightnessとbandでヒットした模様。1/16’12
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Polarimetric Estimates of a 1-Month Accumulation of Light Rain with a 3-cm Wavelength Radar L. Borowska, D. Zrnić, A. Ryzhkov, P. Zhang, C. Simmer Journal of Hydrometeorology Volume 12, Issue 5 (October 2011) pp. 1024-1039 doi: http://dx.doi.org/10.1175/2011JHM1339.1 The authors evaluate rainfall estimates from the new polarimetric X-band radar at Bonn, Germany, for a period between mid-November and the end of December 2009 by comparison with rain gauges. The emphasis is on slightly more than 1-month accumulations over areas minimally affected by beam blockage. The rain regime was characterized by reflectivities mainly below 45 dBZ, maximum observed rain rates of 47 mm h−1, a mean rain rate of 0.1 mm h−1, and brightband altitudes between 0.6 and 2.4 km above the ground. Both the reflectivity factor and the specific differential phase are used to obtain the rain rates. The accuracy of rain total estimates is evaluated from the statistics of the differences between radar and rain gauge measurements. Polarimetry provides improvement in the statistics of reflectivity-based measurements by reducing the bias and RMS errors from −25% to 7% and from 33% to 17%, respectively. Essential to this improvement is separation of the data into those attributed to pure rain, those from the bright band, and those due to nonmeteorological scatterers. A type-specific (rain or wet snow) relation is applied to obtain the rain rate by matching on the average the contribution by wet snow to the radar-measured rainfall below the bright band. The measurement of rain using specific differential phase is the most robust and can be applied to the very low rain rates and still produce credible accumulation estimates characterized with a standard deviation of 11% but a bias of −25%. A composite estimator is also tested and discussed. http://hydro.iis.u-tokyo.ac.jp/~koshida/review/1109.htm【最後の文は、積算雨量では標準偏差は11%と小さいが、バイアスは-25%となってしまう？】1/13’12 |
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A Novel Approach for Selective Reconstruction of Cloud-Contaminated Satellite Images Bipasha Paul Shukla, P. K. Pal, P. C. Joshi Journal of Atmospheric and Oceanic Technology Volume 28, Issue 8 (August 2011) pp. 1028-1035 doi: http://dx.doi.org/10.1175/2011JTECHA1529.1 衛星画像から雲を除去する話。brightnessとbandでヒットした模様。1/16’12
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Observations of Winter-time US West Coast Precipitating Systems with W-band Satellite Radar and Other Spaceborne Instruments Sergey Y. Matrosov Journal of Hydrometeorology Volume 0, Issue 0 ( ) pp. doi: http://dx.doi.org/10.1175/JHM-D-10-05025.1 大気の川。1109。
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Automated Lightning Flash Detection in Nighttime Visible Satellite Data Richard L. Bankert, Jeremy E. Solbrig, Thomas F. Lee, Steven D. Miller Weather and Forecasting Volume 26, Issue 3 (June 2011) pp. 399-408 doi: http://dx.doi.org/10.1175/WAF-D-10-05002.1 可視画像から雷光を観測。新しい衛星には昼モードと夜モードがあるらしい。雷光（lightning flash）のbright streak(?)がヒット。1/16’12
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Typical Patterns of Microwave Signatures and Vertical Profiles of Precipitation in the Midlatitudes from TRMM Data Munehisa K. Yamamoto, Kenji Nakamura Journal of Applied Meteorology and Climatology Volume 50, Issue 6 (June 2011) pp. 1236-1254 doi: http://dx.doi.org/10.1175/2010JAMC2539.1
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1/16’12 brightbandで再検索48件
Evolving Multisensor Precipitation Estimation Methods: Their Impacts on Flow Prediction Using a Distributed Hydrologic Model
David Kitzmiller, Suzanne Van Cooten,
Feng Ding, Kenneth Howard, Carrie Langston, Jian Zhang, Heather Moser, Yu
Zhang, Jonathan J. Gourley, Dongsoo
Kim, David Riley
Journal
of Hydrometeorology
Volume
12, Issue 6 (December 2011) pp. 1414-1431
doi: http://dx.doi.org/10.1175/JHM-D-10-05038.1途中
地上でレーダを補正した雨量と、他のセンサーによる雨量の比較。1/16’12
[Abstract] [Full Text] [PDF (3576 KB)] [Add to Favorites]
A Simulation Approach for Validation of a Brightband Correction MethodMarco
Borga, Emmanouil N. Anagnostou, Witold F. Krajewski Journal
of Applied Meteorology Volume
36, Issue 11 (November 1997) pp. 1507-1518 Brightband
effects are one of the more important causes of vertical variability of
reflectivity and severely affect the accuracy of rainfall estimates from
ground-based radar. Monte Carlo simulation experiments are performed to
investigate the efficiency of a procedure for the correction of errors
related to the vertical variability of reflectivity. The simulation model
generates three-dimensional radar reflectivity fields. Brightband effects are
simulated through a physically based model of melting-layer reflectivity
observations. Sensitivity of the correction procedure for a number of
different precipitation scenarios and radar systems is analyzed. Overall, the
identification method is found to be a robust procedure for correction of
brightband effects. Results indicate a dependence of the effectiveness of the
correction procedure on mean altitude and spatial variability of the melting
layer. doi:
http://dx.doi.org/10.1175/1520-0450(1997)036<1507:ASAFVO>2.0.CO;2 計算でBBの変動を与え、補正【レーダの鉛直分布において、BBの部分を周囲と極端に違わないように補正する】に係る効率を調べる。BBの補正効率が平均高度・空間の変動度 に依存していることを示す。 |
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Modeling of the Melting Layer. Part IV: Brightband Bulk ParameterizationCatherine
Heyraud, Wanda Szyrmer, Stéphane
Laroche, Isztar Zawadzki Journal
of the Atmospheric Sciences Volume
65, Issue 6 (June 2008) pp. 1991-2001. In
this paper a simplified UHF-band backscattering parameterization for
individual melting snowflakes is proposed. This parameterization is a
function of the density, shape, and melted fraction, and is used here in a
brightband bulk modeling study. A 1D bulk model is developed where
aggregation and breakup are neglected. Model results are in good agreement
with detailed bin-model results and simulate the radar brightband
observations well. It is shown the model can be seen as an observation operator that could be introduced
into a data assimilation scheme to extract information contained in the radar
data measurements. doi:
http://dx.doi.org/10.1175/2007JAS2448.1 1次元の簡単な鉛直分布モデルを作成して、ブライトバンドをモデル化した。パラメータは密度、形、融解率。融解をバルクでとらえることが目的。凝集・分裂は考慮しない。ビンのモデルおよび観測と比較。 モデルが観測演算子（レーダ観測から同化のために情報を引き出す変数）として活用できる。1/19’12 |
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Brightband Identification Based on Vertical Profiles of Reflectivity from the WSR-88DJian
Zhang, Carrie Langston, Kenneth Howard Journal
of Atmospheric and Oceanic Technology Volume
25, Issue 10 (October 2008) pp. 1859-1872 The
occurrence of a bright band, a layer of enhanced reflectivity due to melting
of aggregated snow, increases uncertainties in radar-based quantitative precipitation
estimation (QPE). The height of the brightband layer is an indication of 0°C
isotherm and can be useful in identifying areas of potential icing for
aviation and in the data assimilation for numerical weather prediction (NWP).
Extensive analysis of vertical profiles of reflectivity (VPRs) derived from
the Weather Surveillance Radar-1988 Doppler (WSR-88D) base level data showed
that the brightband signature could be easily identified from the VPRs. As a
result, an automated brightband identification (BBID) scheme has been
developed. The BBID algorithm can determine from a volume scan mean VPR and a
background freezing level height from a numerical weather prediction model
whether a bright band exists and the height of the brightband layer. The paper
presents a description of the BBID scheme and evaluation results from a large
dataset from WSR-88D radars in different geographical regions and seasons. WSR88Dから融解層高度（ブライトバンド高度）を推定。【手法が近いかも】1/23’12 doi:
http://dx.doi.org/10.1175/2008JTECHA1039.1 |
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Effects of Incorporating a Brightband Model in a Downward-Looking Radar Rainfall Retrieval AlgorithmM. Thurai,
H. Kumagai, T. Kozu, J.
Awaka Journal
of Atmospheric and Oceanic Technology Volume
18, Issue 1 (January 2001) pp. 20-25 A
range-profiling method proposed for nadir-looking rain radar has been
investigated using aircraft measurements of a typhoon event at 10 and 35 GHz.
In order to take into account the effects of change in the hydrometeor phase
along the radar beam, it was necessary to modify the original method. Instead
of using an analytic expression for the retrieval of radar reflectivity, a
numerical solution is described that enables one to include the melting layer
contribution. Results show a marked improvement in the estimated rainfall
rates even when a fairly simple brightband model is used, indicating the
usefulness and necessity of incorporating a brightband model in a retrieval
of rain rate with a downward-looking radar. The improvement occurs mainly in
the retrieved Ka-band results and highlights the
importance of the melting layer in retrieval algorithms, particularly for
high frequencies. 【WとKaで雲を上から観測。TRRM/PRの原型。】1/23’12 改良版ではΛ（粒径分布の傾き）を評価。2/27’12 doi:
http://dx.doi.org/10.1175/1520-0426(2001)018<0020:EOIABM>2.0.CO;2 [Abstract]
[Full
Text] [PDF (104 KB)] [Add
to Favorites] 要旨：下方を見るレーダで距離方向の降水量を評価する時、融解層がある場合にレーダの反射強度因子から回帰的に関係式を求めるのでなく、融解層のモデルを入れることで、降水量の評価の精度が格段に向上した。すなわちレーダにより降水量を評価する場合には融解層のモデル化が必要である。評価精度の改善は主にKa帯で示された。評価アルゴリズムの中で融解層の重要性は特に周波数が高い場合に顕著である。4/8’12 Intro:TRMMで使えるように、航空機で検証。降水量推定の考え方は粒径分布を求めることで降水量を得ることである。粒径分布を求めるために減衰量を推定している（表面参照法を用いて）。 １．イントロ これまで、TRMM-PRで定量観測を行うための手法をいくつか提案してきた。 ２．回帰方法 ａ．粒径分布の仮定 粒径分布において全高度でＮ0は固定、λが変化すると仮定する（粒径分布は指数分布）。この仮定の下では、減衰係数κ（dB/㎞）とZeは指数関数で近似できる κ= α（N0）Ze＾β（N0）【αとβはN0の関数】 αとβは異なる粒径分布についてミー散乱よりテーブルを用意しておく。 ⇒この後、アンテナと伝搬に関するシンポジウム（2006）でモデルの改良。融解層のトップは横山と田中で融解開始高度【ということはすなわち松尾・佐粧による融解開始高度】←P2r18行目によれば現実的に(経験的に?現象に合わせて?)3高度上で決めたらしい。 改良点はRrあるいはΛ（粒径分布の傾き）について、増加している領域【論文では領域(a)】と一定の領域【論文では領域(b)】に分割した点である。【Λの増加域は直接雪⇒雨への変化を示唆している。一方でΛの定常域は雨の領域でBBに含まれる領域←形状で見たBBと思われる。すなわち大粒子の振る舞いでZの分布が急変する領域】 BBの底はトップから現場に合わせて1000mとした。 モデルを使って、RおよびΛの鉛直分布を計算した。Rは融解層内で増加する分布（0.5㎜/h⇒2.5mm/h）を示し、Λは融解層トップで極小を示した。Λは融解層の上方では小さい粒子が多く大きな値をとるが、雪粒子が落下するにつれて成長することでΛは小さくなる。大粒子の形成は融解層トップで最も強化されると考えられる。 ４．議論 本研究の発見は、BBの底より小さい降水強度でZの極大が形成されるということである。 Zのピークは計算では、観測より上方にできる。 ５．結論 BBモデルを開発した。このモデルでは降水強度が小さい値から大きな値へと妥当に変化している。 |
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Modeling of the Melting Layer. Part II: ElectromagneticFrédéric
Fabry, Wanda Szyrmer Journal
of the Atmospheric Sciences Volume
56, Issue 20 (October 1999) pp. 3593-3600 【既読】0701 doi:
http://dx.doi.org/10.1175/1520-0469(1999)056<3593:MOTMLP>2.0.CO;2 12/25’12 |
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Long-Term Radar Observations of the Melting Layer of Precipitation and Their InterpretationFrederic
Fabry, Isztar Zawadzki Journal
of the Atmospheric Sciences Volume
52, Issue 7 (April 1995) pp. 838-851 【既読】0701検索結果のみ。0612Ralpf
et al.(1995)の引用として説明。 doi:
http://dx.doi.org/10.1175/1520-0469(1995)052<0838:LTROOT>2.0.CO;2 |
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Measurements and Simulations of Nadir-Viewing Radar Returns from the Melting Layer at X and W BandsLiang
Liao, Robert Meneghini, Lin Tian, Gerald M.
Heymsfield Journal
of Applied Meteorology and Climatology Volume
48, Issue 11 (November 2009) pp. 2215-2226 Simulated
radar signatures within the melting layer in stratiform rain—namely, the
radar bright band—are checked by means of comparisons with simultaneous
measurements of the bright band made by the ER-2 Doppler radar (EDOP; X band)
and Cloud Radar System (CRS; W band) airborne Doppler radars during the
Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida-Area
Cirrus Experiment (CRYSTAL-FACE) campaign in 2002. A stratified-sphere model,
allowing the fractional water content to vary along the radius of the
particle, is used to compute the scattering properties of individual melting
snowflakes. Using the effective dielectric constants computed by the
conjugate gradient–fast Fourier transform numerical method for X and W bands
and expressing the fractional water content of a melting particle as an
exponential function in particle radius, it is found that at X band the
simulated radar brightband profiles are in an excellent agreement with the
measured profiles. It is also found that the simulated W-band profiles
usually resemble the shapes of the measured brightband profiles even though
persistent offsets between them are present. These offsets, however, can be
explained by the attenuation caused by cloud water and water vapor at W band.
This is confirmed by comparisons of the radar profiles made in the rain
regions where the unattenuated W-band reflectivity
profiles can be estimated through the X- and W-band Doppler velocity measurements.
The brightband model described in this paper has the potential to be used
effectively for both radar and radiometer algorithms relevant to the
satellite-based Tropical Rainfall Measuring Mission and Global Precipitation
Measuring Mission 【既読】？ |
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Automated Detection of the Bright Band Using WSR-88D DataJonathan
J. Gourley, Chris M. Calvert Weather
and Forecasting Volume
18, Issue 4 (August 2003) pp. 585-599【既読】？ doi:
http://dx.doi.org/10.1175/1520-0434(2003)018<0585:ADOTBB>2.0.CO;2 |
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Airflow and Precipitation Properties within the Stratiform Region of Tropical Storm Gabrielle during LandfallDong-Kyun Kim, Kevin R. Knupp,
Christopher R. Williams Monthly
Weather Review Volume
137, Issue 6 (June 2009) pp. 1954-1971【既読】？ |
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Freezing-Level Estimation with Polarimetric RadarEdward
A. Brandes, Kyoko Ikeda Journal
of Applied Meteorology Volume
43, Issue 11 (November 2004) pp. 1541-1553 A
simple empirical procedure for determining freezing levels with polarimetric
radar measurements is described. The algorithm takes advantage of the strong
melting-layer signatures and the redundancy provided by the suite of
polarimetric radar measurements—in
particular, radar reflectivity, linear depolarization ratio, and
cross-correlation coefficient. 融解高度を判定するための、簡単な経験的手法を提案する。このアルゴリズムは、一連の偏波レーダ観測による、強い融解層の信号と複数の信号を利用する。偏波観測情報では、反射強度因子、直線偏波抑圧比、偏波間相関係数を利用する。 【すべての仰角を使っているということ。】 １．イントロ （目的）融解高度がわかると、航空機の着氷障害の予測ができる。また、0度高度は予報モデルの検証に使える。さらに、レーダの定量評価に、雪の層・雨の層を知ることは不可欠。偏波を使った粒子判別にも融解高度は重要(Vivekanandan et al 1999,IEEE)。 Mittermaile
& Illingworth(2003)やGourley&Calvert(2003)ではZを用いてブライトバンドと融解層高度の長期的な統計が行われている。反射強度因子が極大を示さないときには、ドップラ速度による落下速度の増加を見て融解層を判断している。 偏波を導入する目的としては、対流性の雲で、従来より詳細な融解高度の情報が得られるからである(p1541,r13)5/2’12 ３．偏波による融解層観測
このレンジでは、霙粒子による後方散乱の影響で大きな位相差が生じる 図：Φdpが融解層手前で大きな値を示すことの模式図 今回の事例ではΦdpの極大値と他の観測値（Zとかρhvとか）のML信号はよく一致しているが、一般にはφdpはノイズが大きく、局所的なZの影響を大きく受け（RyzhkovとZrnic1998）、融解層のΦdpの信号は大きな振動を示す（Zrnicら1993など）。Spolの観測では、融解層内に二つの極大値と一つの極小値がある行動がしばしば見られた。また、Φdpは位相差の積算なので、観測レンジの最大値は、ふつう、風雨のトップやレーダの最遠方で観測される。【ΦdpがMLの指標に向かない事を示唆?】 雨になれば、急速に落下速度が増加し、降水粒子は融解層（ブライトバンド層）から抜け落ちる。また、雨滴の分裂もZの減少に寄与する。雨の層のトップではZが28ｄBZくらい、LDRとρhvは氷の層と同じくらいの値となる。p1544r-4 ４．モデルと道具(implementation) P1546r-1
【図3aの最大Zと0℃高度からのずれについて2次元の回帰式を示している】0℃高度との差は、アンテナ仰角一定観測と、方位角一定観測に基づき求めた。両者の比【観測時間あるいはスキャン数?】は６：７である。0℃からのずれ（モデルで補正なし）は、Fabry&Zawadzki(1995)の平均と良い一致を示す。0℃より上空での凝集は、この関係を決めていないことが示される。 P1548r-1
ｈi＝ｈｔｍａｘi＋ｄi 図4や図6に書かれた数字は上から、融解高度、σｈ、ρ（相関係数）が0.7を超えるパラメータ数（Ｚｈ、ＬＤＲ、ρＨＶ）。 ５．結果 ６．まとめ doi:
http://dx.doi.org/10.1175/JAM2155.1 0804Luca Baldini
and Eugenio Gorgucci 2006で引用。 0903；2009年にファジーを組み込んだ手法について発表。 出世他2009の引用文献として説明1011 OPERA報告書での引用文献1111 [Abstract]
[Full
Text] [PDF (1141 KB)] [Add
to Favorites] 1/31’12【レーダの仕様を確認のこと】 □PPI操作を元にBB高度を抽出；誤差は100-200m；対象は層状性の雲；【手法の確立（提案）したということが重要】 図1：レーダから距離10㎞での鉛直分布、Zh、LDR、ρhv、ZDR、φdp。破線は評価した0℃高度を示す。距離方向2㎞、高度方向0.2㎞で平均（p1544l8） 図2：0℃高度を4.5㎞とした場合のプロファイルモデル。 図3：a）0℃高度とZh最大値高度の差、b）Zh最大値高度とLDRおよびρhv極値高度の差 図4：5㎞毎に0℃高度を評価。2行目の数字はσb（㎞）、3行目の数字はρ>0.7より大きいパラメータの数。 図6：10㎞毎に0℃高度を検出。4/19’12 図7：仰角6度によるZh,LDR,ρhvの観測。右下には抽出した融解高度を示す。ただし、観測は4.8，6.0、7.2，9.6度の観測を用いた。【複数仰角による判定】 図8：各観測要素による融解高度判定のヒストグラム。図4で示した降雨を対象としている。【「多数一致」のグラフは2つあればよいのか?】5/1’12 図9：今回のアルゴリズムで抽出した融解高度と冬の観測（ゾンデ、レーダから60㎞位離れている）と夏の観測（航空機）の比較 【ポイントは複数の仰角、観測要素を用いて融解層高度を算出するところ。アルゴリズムの目的が層状性の雲で融解層高度を出すことだから。】 |
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An Objective Method for Recognizing and Partially Correcting Brightband Error in Radar ImagesM.
Cheng, C. G. Collier Journal
of Applied Meteorology Volume
32, Issue 6 (June 1993) pp. 1142-1149 In
this paper, a simple objective method for recognizing and correcting the
effects of the radar bright band in weather radar images is presented. The
method is based upon the finding that area-average rainfall rate can be
estimated from a fractional area of rainfall rate using a threshold value of
2 mm and excluding radar data contaminated by bright band. The observed
area-average rainfall rate is much larger than that estimated for brightband
cases. It is shown by case studies that the method is successful for frontal
rainfall systems. A simple objective method of deriving a rainfall rate
within arm affected by bright band is also proposed. doi:
http://dx.doi.org/10.1175/1520-0450(1993)032<1142:AOMFRA>2.0.CO;2 |
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Coastal Orographic Rainfall Processes Observed by Radar during the California Land-Falling Jets Experiment0508.htm_4th.documentsAllen
B. White, Paul J. Neiman, F. Martin Ralph, David E. Kingsmill, P. Ola G. Persson Journal
of Hydrometeorology Volume
4, Issue 2 (April 2003) pp. 264-282 既読0508
2/6’12 doi:
http://dx.doi.org/10.1175/1525-7541(2003)4<264:CORPOB>2.0.CO;2 |
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Uncertainty in Vertically Integrated Liquid Water Content due to Radar Reflectivity Observation ErrorMark
N. French, Hervé Andrieu,
Witold F. Krajewski Journal
of Atmospheric and Oceanic Technology Volume
12, Issue 2 (April 1995) pp. 404-409. Radar
reflectivity is used to estimate meteorological quantities such as rainfall
rate, liquid water content, and the related quantity, vertically integrated
liquid (VIL) water content. The estimation of any of these quantities depends
on several assumptions related to the characteristics of the physical
processes controlling the occurrence and character of water in the
atmosphere. Additionally, there are many sources of error associated with
radar observations, such as those due to brightband, hail, and drop size
distribution approximations. This work addresses one error of interest, the
radar reflectivity observation error; other error sources are assumed to be
corrected or negligible. The result is a relationship between the uncertainty
in VIL water content and radar reflectivity measurement error. An example
application illustrates the estimation of VIL uncertainty from typical radar
reflectivity observations and indicates that the coefficient of variation in
VIL is much larger than the coefficient of variation in radar reflectivity. 積分雨水量（VIL）を定量的に観測する際、影響を与えるレーダ反射強度因子の誤差について調査した。レーダ反射強度因子の係数の変動によって、VILの変動ははるかに大きくなる2/6’12 doi:
http://dx.doi.org/10.1175/1520-0426(1995)012<0404:UIVILW>2.0.CO;2 |
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Comparison of Rain Rates over the Ocean Derived from TRMM Microwave Imager and Precipitation Radar.Junji Ikai, Kenji Nakamura Journal
of Atmospheric and Oceanic Technology Volume
20, Issue 12 (December 2003) pp. 1709-1726. Surface
rain rates over the ocean derived from the Tropical Rainfall Measuring
Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) are
compared and systematic differences between TMI-derived rain rates and
PR-derived rain rates are shown. Three plausible reasons for these
differences were found. One is a problem in the freezing-level assumption in
the TMI algorithm for midlatitude regions in the
winter, which results in underestimation of TMI-derived rain rates. Second is
inadequate Z–R or k–R relationships for convective and stratiform types in
the PR algorithm. Third is the incorrect interpretation of the rain layer
when the freezing level is low and the rain type is convective. The strong
brightband echo seems to be interpreted as rain and a too strong rain
attenuation correction is applied. This results in a too strong rain rate by
the PR algorithm. TRMMのマイクロ波イメージTMIとPRから推定した地上降水量を比較した。両者の誤差に以下の3つの理由が考えらえる。１）融解層高度を中緯度の冬に設定しているのでTMIからの降水量は過小となる ２）ZR関係、ｋR関係が対流性の雲、層状性の雲に対してよくない ３）融解層高度の見積誤差、あるいは対流性の降雨について。強いブライトバンドは降水量を過大評価したり、減衰補正が過補正になる原因となる。このため、PRが過大になる。2/8’12 doi:
http://dx.doi.org/10.1175/1520-0426(2003)020<1709:CORROT>2.0.CO;2
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The New French Operational Radar Rainfall Product. Part II: ValidationP.
Tabary, J. Desplats, K. Do Khac,
F. Eideliman, C. Gueguen,
J-C. Heinrich Weather
and Forecasting Volume
22, Issue 3 (June 2007) pp. 409-427 doi:
http://dx.doi.org/10.1175/WAF1005.1
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Error Statistics of VPR Corrections in Stratiform PrecipitationAldo
Bellon, Gyu Won Lee, Isztar
Zawadzki Journal
of Applied Meteorology Volume
44, Issue 7 (July 2005) pp. 998-1015 08062/8’12 doi:
http://dx.doi.org/10.1175/JAM2253.1
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Toward the Use of Integral Radar Volume Descriptors for Quantitative Areal Precipitation Estimation: Results from Pseudoradar Observations.Silke Trömel, Clemens Simmer, Jürgen Braun, Thomas Gerstner,
Michael Griebel Journal
of Atmospheric and Oceanic Technology Volume
26, Issue 9 (September 2009) pp. 1798-1813. The
central objective of this analysis is to significantly enhance the quality of
radar-derived precipitation estimates by as fully as possible exploiting the
information contained in the spatial and temporal variability of 3D radar
volume data. The results presented are based on pseudoradar
data and rain rates of a regional weather forecasting model and 12 true radiosoundings as well. Two approaches are pursued: the
first approach estimates total rainfall from an individual storm over its
lifetime, whereas the second approach assesses the areawide
instantaneous rainfall from a multiplicity of such storms by the use of
measurements of the areal coverage of the storms exceeding a threshold radar
reflectivity. The concept is extended by adding more predictors to
significantly enhance the rainfall estimates. The horizontal expected value
and the horizontal standard deviation of enclosed reflectivities at the
ground, the mean brightband fraction and its trend, the fractional area with
reflectivities exceeding a threshold τ, and an orographic rainfall amplifier
provide relative errors smaller than 10% in approximately 75% of the
considered rain events in the first approach. In the second approach, a
relative error is achieved that is below 10% in approximately 63% elements of
the test set. 降水量の定量評価について、その場での観測値を用いる方法と、体積観測の結果を複合的に用いる手法で比較した。【偽のレーダデータ（pseudoradar
data）とは、直接観測でないことを言っているのか?レーダ観測を元にしたグリッドデータ?】。レーダデータと、予報値とゾンデを使っている。考え方として、降水量を増やす要素を見つけている。地上降水から期待されるZの増大や、ブライトバンドの一部と傾向、Zが閾値を超えた面積、地形効果などを考察することにより、最初の手法は、後の手法に比べて誤差が75%から10%未満に小さくなった。後の手法は対象の63%が誤差10%未満である。2/9’12 |
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Performance of the Precipitation Occurrence Sensor System as a Precipitation Gauge.B.
E. Sheppard, P. I. Joe Journal
of Atmospheric and Oceanic Technology Volume
25, Issue 2 (February 2008) pp. 196-212. The
Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar
originally developed by the Meteorological Service of Canada for reporting
the occurrence, type, and intensity of precipitation from Automated Weather
Observing Stations. This study evaluates POSS as a gauge for measuring
amounts of both liquid and solid precipitation. Different precipitation rate
estimation algorithms are described. The effect of different solid
precipitation types on the Doppler velocity spectrum is discussed. Lacking any
accepted reference for high temporal resolution rates, the POSS precipitation
rate measurements are integrated over time periods ranging from 6 h to one
day and validated against international and Canadian reference gauges. Data
from a wide range of sites across Canada and for periods of several years are
used. The statistical performance of POSS is described in terms of the
distribution of ratios of POSS to reference gauge amounts (catch ratios). In
liquid precipitation the median of the catch ratio distribution is 82% and
the interquartile range was between −12% and 19% about the median. In solid
precipitation the median is 90% and the interquartile range is between −17%
and 24% about the median. The underestimation in both liquid and solid
precipitation is shown to be a function of precipitation rate and phase. The
effects of radome wetting, raindrop splashing,
wind, and the radar “brightband” effect on the estimation of precipitation
rates are discussed. Sheppard
は0570に3件あるがこの文献はない。interquartile; 最小の四分位数から最大の四分位数までの間 POSSを用いた雨雪判別の精度評価。4分位で評価した値が、どのような意味を持つかについては不明。検証で用いる地上観測が細かい時間分解能を持たないので、6時間と日平均で評価した。また、誤差の原因となる、レドームの濡れ、流れる雨粒（個体粒子から分離し早く落ちる雨?）、ブライトバンドの効果を示す。2/13’12 doi:
http://dx.doi.org/10.1175/2007JTECHA957.1
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Characteristics of the Mirror Image of Precipitation Observed by the TRMM Precipitation Radar.Ji Li,
Kenji Nakamura Journal
of Atmospheric and Oceanic Technology Volume
19, Issue 2 (February 2002) pp. 145-158. A
mirror image is a virtual image of precipitation from “below” the ocean
surface when an airborne or a spaceborne radar is
used to view rainfall over the ocean. It is due to a reflection of energy
from the sea surface to the precipitation and back to the radar via a second
reflection at the sea surface. The mirror image characteristics were
investigated using Tropical Rainfall Measuring Mission (TRMM) precipitation
radar data and the following was found. 1) The radar can detect the mirror
image clearly over the ocean. 2) The mirror image echo corresponds well to
the direct rain echo at nadir and near-nadir incidence angles. 3) In a weak
rain region, the mirror echo intensity is nearly proportional to the direct
echo power except near the radar noise level. 4) In the strong rain region,
rain attenuation effects clearly appear. 5) The ratio of the mirror echo
power to the direct echo power is affected by the rain attenuation, which
varies with the brightband height and the range of the target rain from
surface. Further, a simple simulation was performed in order to confirm the
above characteristics. The signal fluctuation, noise contamination, rain
attenuation, and surface cross section are taken into account in the
simulation. The results of simulation confirmed the observation results. 【どうやら主のほかにミラーの信号は強い。2/14’12 doi:
http://dx.doi.org/10.1175/1520-0426(2002)019<0145:COTMIO>2.0.CO;2
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Characteristics of Sprite-Producing Positive Cloud-to-Ground Lightning during the 19 July 2000 STEPS Meso scale Convective Systems.Walter
A. Lyons, Thomas E. Nelson, Earle R. Williams, Steven A. Cummer,
Mark A. Stanley Monthly
Weather Review Volume
131, Issue 10 (October 2003) pp. 2417-2427. During
the summer of 2000, the Severe Thunderstorm Electrification and Precipitation
Study (STEPS) program deployed a three-dimensional Lightning Mapping Array
(LMA) near Goodland, Kansas. Video confirmation of sprites triggered by
lightning within storms traversing the LMA domain were coordinated with
extremely low frequency (ELF) transient measurements in Rhode Island and
North Carolina. Two techniques of estimating changes in vertical charge
moment (Mq) yielded averages of 800 and 950 C km
for 13 sprite-parent positive polarity cloud-to-ground strokes (+CGs).
Analyses of the LMA's very high frequency (VHF) lightning emissions within
the two meso scale convective systems (MCSs) show that +CGs did not produce
sprites until the centroid of the maximum density of lightning radiation
emissions dropped from the upper part of the storm (7–11.5 km AGL) to much
lower altitudes (2–5 km AGL). The average height of charge removal (Zq) from 15 sprite-parent +CGs during the late mature
phase of one MCS was 4.1 km AGL. Thus, the total charges lowered by
sprite-parent +CGs were on the order of 200 C. The regional 0°C isotherm was
located at about 4.0 km AGL. This suggests a possible linkage between
sprite-parent CGs and melting-layer/brightband charge production mechanisms
in MCS stratiform precipitation regions. These cases are supportive of the
conceptual MCS sprite-production models previously proposed by two of the
authors (Lyons and Williams). 正の対地放電に関心がある。正の電荷を作るのに融解層が関連している2/17’12 doi:
http://dx.doi.org/10.1175/1520-0493(2003)131<2417:COSPCL>2.0.CO;2
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Modeling of the Melting Layer. Part 3: The Density Effect. I.
Zawadzki, W. Szyrmer, C. Bell, F. Fabry Journal
of the Atmospheric Sciences Volume
62, Issue 10 (October 2005) pp. 3705-3723. A
model of the melting snow and its radar reflectivity is presented here. The
main addition to previous description of the melting layer is the explicit
introduction of snow density as a variable. The model is validated with
radar observations. Differences in brightband intensity for comparable
precipitation rates are related here to the coexistence of supercooled cloud
water (SCW) with snow above the melting level leading to riming and change in
snow density. Cases where riming was suspected were selected according to the
characteristics of the vertical profile of reflectivity flux above the
melting layer and vertical Doppler velocities faster than expected from
low-density snow. For stratiform precipitation with a melting layer, high
snow-to-rain velocity ratio indicates high-density snow and consequently a
small peak-to-rain reflectivity difference is expected. This relationship was
computed from the model and confirmed with vertically pointing radar
observations. In spite of the complexity of the physical processes present in
the melting layer the model appears to capture the essential elements. 何度か参考にしているはず。2/21’12 doi:
http://dx.doi.org/10.1175/JAS3563.1
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Modeling of the Melting Layer. Part I: Dynamics and
Microphysics Wanda
Szyrmer, Isztar Zawadzki Journal
of the Atmospheric Sciences Volume
56, Issue 20 (October 1999) pp. 3573-3592 doi:
http://dx.doi.org/10.1175/1520-0469(1999)056<3573:MOTMLP>2.0.CO;2
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Vertical Structure of Hurricane Eyewalls as Seen by the TRMM
Precipitation Radar Deanna
A. Hence, Robert A. Houze Jr. Journal
of the Atmospheric Sciences Volume
68, Issue 8 (August 2011) pp. 1637-1652 doi:
http://dx.doi.org/10.1175/2011JAS3578.1
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Lidar and Triple-Wavelength Doppler Radar Measurements of the
Melting Layer: A Revised Model for Dark- and Brightband Phenomena Kenneth
Sassen, James R. Campbell, Jiang Zhu, Pavlos Kollias, Matthew Shupe, Christopher Williams Journal
of Applied Meteorology Volume
44, Issue 3 (March 2005) pp. 301-312 doi:
http://dx.doi.org/10.1175/JAM-2197.1
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Improved Accuracy of Radar WPMM Estimated Rainfall upon
Application of Objective Classification Criteria Daniel
Rosenfeld, Eyal Amitai,
David B. Wolff Journal
of Applied Meteorology Volume
34, Issue 1 (January 1995) pp. 212-223 doi:
http://dx.doi.org/10.1175/1520-0450-34.1.212
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Identification of Vertical Profiles of Radar Reflectivity for
Hydrological Applications Using an Inverse Method. Part II: Formulation Hervé Andrieu, Jean Dominique Creutin Journal
of Applied Meteorology Volume
34, Issue 1 (January 1995) pp. 240-259 doi:
http://dx.doi.org/10.1175/1520-0450(1995)034<0240:IOVPOR>2.0.CO;2
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Comparison of Ice-Phase Microphysical Parameterization Schemes
Using Numerical Simulations of Tropical Convection Michale McCumber, Wei-Kuo Tao, Joanne
Simpson, Richard Penc, Su-Tzai
Soong Journal
of Applied Meteorology Volume
30, Issue 7 (July 1991) pp. 985-1004 doi:
http://dx.doi.org/10.1175/1520-0450-30.7.985
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A Polarimetric Radar Approach to Identify Rain, Melting-Layer,
and Snow Regions for Applying Corrections to Vertical Profiles of
Reflectivity Sergey
Y. Matrosov, Kurt A. Clark, David E. Kingsmill Journal
of Applied Meteorology and Climatology Volume
46, Issue 2 (February 2007) pp. 154-166 doi:
http://dx.doi.org/10.1175/JAM2508.1
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Real-Time Comparisons of VPR-Corrected Daily Rainfall
Estimates with a Gauge Mesonet Aldo
Bellon, Gyu Won Lee, Alamelu
Kilambi, Isztar Zawadzki Journal
of Applied Meteorology and Climatology Volume
46, Issue 6 (June 2007) pp. 726-741 doi:
http://dx.doi.org/10.1175/JAM2502.1
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CloudSat Studies of
Stratiform Precipitation Systems Observed in the Vicinity of the Southern
Great Plains Atmospheric Radiation Measurement Site Sergey
Y. Matrosov Journal
of Applied Meteorology and Climatology Volume
49, Issue 8 (August 2010) pp. 1756-1765 doi:
http://dx.doi.org/10.1175/2010JAMC2444.1
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The Tropical Convective Spectrum. Part I: Archetypal Vertical
Structures Dennis
J. Boccippio, Walter A. Petersen, Daniel J. Cecil Journal
of Climate Volume
18, Issue 14 (July 2005) pp. 2744-2769 doi:
http://dx.doi.org/10.1175/JCLI3335.1
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Regional and Diurnal Variability of the Vertical Structure of
Precipitation Systems in Africa Based on Spaceborne
Radar Data Bart
Geerts, Teferi Dejene Journal
of Climate Volume
18, Issue 7 (April 2005) pp. 893-916 doi:
http://dx.doi.org/10.1175/JCLI-3316.1
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Rain versus Snow in the Sierra Nevada, California: Comparing
Doppler Profiling Radar and Surface Observations of Melting Level Jessica
D. Lundquist, Paul J. Neiman, Brooks Martner, Allen
B. White, Daniel J. Gottas, F. Martin Ralph Journal
of Hydrometeorology Volume
9, Issue 2 (April 2008) pp. 194-211 doi:
http://dx.doi.org/10.1175/2007JHM853.1
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Polarimetric Estimates of a 1-Month Accumulation of Light Rain
with a 3-cm Wavelength Radar L. Borowska, D. Zrnić, A. Ryzhkov,
P. Zhang, C. Simmer Journal
of Hydrometeorology Volume
12, Issue 5 (October 2011) pp. 1024-1039 doi:
http://dx.doi.org/10.1175/2011JHM1339.1
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Evolving Multisensor Precipitation
Estimation Methods: Their Impacts on Flow Prediction Using a Distributed
Hydrologic Model David
Kitzmiller, Suzanne Van Cooten,
Feng Ding, Kenneth Howard, Carrie Langston, Jian Zhang, Heather Moser, Yu
Zhang, Jonathan J. Gourley, Dongsoo
Kim, David Riley Journal
of Hydrometeorology Volume
12, Issue 6 (December 2011) pp. 1414-1431 doi:
http://dx.doi.org/10.1175/JHM-D-10-05038.1
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Rainfall Estimation by the WSR-88D for Heavy Rainfall Events Mary
Lynn Baeck, James A. Smith Weather
and Forecasting Volume
13, Issue 2 (June 1998) pp. 416-436 doi:
http://dx.doi.org/10.1175/1520-0434(1998)013<0416:REBTWF>2.0.CO;2
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Constructing Three-Dimensional Multiple-Radar Reflectivity
Mosaics: Examples of Convective Storms and Stratiform Rain Echoes Jian
Zhang, Kenneth Howard, J. J. Gourley Journal
of Atmospheric and Oceanic Technology Volume
22, Issue 1 (January 2005) pp. 30-42 doi:
http://dx.doi.org/10.1175/JTECH-1689.1
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Assessment of Vertically Integrated Liquid (VIL) Water Content
Radar Measurement Brice
Boudevillain, Hervé Andrieu Journal
of Atmospheric and Oceanic Technology Volume
20, Issue 6 (June 2003) pp. 807-819 doi:
http://dx.doi.org/10.1175/1520-0426(2003)020<0807:AOVILV>2.0.CO;2
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TRMM Precipitation Radar Reflectivity Profiles as Compared
with High-Resolution Airborne and Ground-Based Radar Measurements G.
M. Heymsfield, B. Geerts, L. Tian Journal
of Applied Meteorology Volume
39, Issue 12 (December 2000) pp. 2080-2102 doi:
http://dx.doi.org/10.1175/1520-0450(2001)040<2080:TPRRPA>2.0.CO;2
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Raindrop Size Distributions and Rain Characteristics in
California Coastal Rainfall for Periods with and without a Radar Bright Band Brooks
E. Martner, Sandra E. Yuter,
Allen B. White, Sergey Y. Matrosov, David E. Kingsmill, F. Martin Ralph Journal
of Hydrometeorology Volume
9, Issue 3 (June 2008) pp. 408-425 doi:
http://dx.doi.org/10.1175/2007JHM924.1
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Constraining Microwave Brightness Temperatures by Radar
Brightband Observations A. Battaglia, C. Kummerow,
Dong-Bin Shin, C. Williams Journal
of Atmospheric and Oceanic Technology Volume
20, Issue 6 (June 2003) pp. 856-871 doi:
http://dx.doi.org/10.1175/1520-0426(2003)020<0856:CMBTBR>2.0.CO;2
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Electric and Kinematic Structure of the Oklahoma Mesoscale
Convective System of 7 June 1989 Steven
M. Hunter, Terry J. Schuur, Thomas C. Mapshall, W. David Rust Monthly
Weather Review Volume
120, Issue 10 (October 1992) pp. 2226-2239 doi:
http://dx.doi.org/10.1175/1520-0493(1992)120<2226:EAKSOT>2.0.CO;2
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Wintertime Nonbrightband Rain in
California and Oregon during CALJET and PACJET: Geographic, Interannual, and Synoptic Variability Paul
J. Neiman, Gary A. Wick, F. Martin Ralph, Brooks E. Martner,
Allen B. White, David E. Kingsmill Monthly
Weather Review Volume
133, Issue 5 (May 2005) pp. 1199-1223 doi:
http://dx.doi.org/10.1175/MWR2919.1
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Systematic Variation of Observed Radar Reflectivity–Rainfall
Rate Relations in the Tropics Eyal Amitai Journal
of Applied Meteorology Volume
39, Issue 12 (December 2000) pp. 2198-2208 doi:
http://dx.doi.org/10.1175/1520-0450(2001)040<2198:SVOORR>2.0.CO;2
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A Comparison of Cloud and Rainfall Information from
Instantaneous Visible and Infrared Scanner and Precipitation Radar
Observations over a Frontal Zone in East Asia during June 1998 Toshiro
Inoue, Kazumasa Aonashi Journal
of Applied Meteorology Volume
39, Issue 12 (December 2000) pp. 2292-2301 doi:
http://dx.doi.org/10.1175/1520-0450(2001)040<2292:ACOCAR>2.0.CO;2
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The Application of Radar–Gauge Comparisons to Operational
Precipitation Profile Corrections Jürg
Joss, Robert Lee Journal
of Applied Meteorology Volume
34, Issue 12 (December 1995) pp. 2612-2630 doi:
http://dx.doi.org/10.1175/1520-0450(1995)034<2612:TAORCT>2.0.CO;2
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Classification of Rain Regimes by the Three-Dimensional
Properties of Reflectivity Fields Daniel
Rosenfeld, Eyal Amitai,
David B. Wolff Journal
of Applied Meteorology Volume
34, Issue 1 (January 1995) pp. 198-211 doi:
http://dx.doi.org/10.1175/1520-0450(1995)034<0198:CORRBT>2.0.CO;2
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'bright band' in abstractで検索；92件
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An Objective Method for Recognizing and Partially Correcting
Brightband Error in Radar Images M.
Cheng, C. G. Collier Journal
of Applied Meteorology Volume
32, Issue 6 (June 1993) pp. 1142-1149 doi:
http://dx.doi.org/10.1175/1520-0450(1993)032<1142:AOMFRA>2.0.CO;2
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A QUANTITATIVE STUDY OF THE “BRIGHT BAND” IN RADAR
PRECIPITATION ECHOES Pauline
M. Austin, Alan C. Bemis Journal
of Meteorology Volume
7, Issue 2 (April 1950) pp. 145-151 doi:
http://dx.doi.org/10.1175/1520-0469(1950)007<0145:AQSOTB>2.0.CO;2
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Raindrop Size Distributions and the Radar Bright Band A. Huggel, W. Schmid, A. Waldvogel Journal
of Applied Meteorology Volume
35, Issue 10 (October 1996) pp. 1688-1701 doi:
http://dx.doi.org/10.1175/1520-0450(1996)035<1688:RSDATR>2.0.CO;2
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Radar Echo Intensities Below Bright Band Bh V. Ramana Murty, A. K. Roy, K. R.
Biswas Journal
of the Atmospheric Sciences Volume
22, Issue 1 (January 1965) pp. 91-94 doi:
http://dx.doi.org/10.1175/1520-0469(1965)022<0091:REIBBB>2.0.CO;2
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The Reduction of Errors Caused by Bright Bands in Quantitative
Rainfall Measurements Made Using Radar Catherine
J. Smith Journal
of Atmospheric and Oceanic Technology Volume
3, Issue 1 (March 1986) pp. 129-141 doi:
http://dx.doi.org/10.1175/1520-0426(1986)003<0129:TROECB>2.0.CO;2
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Observations of the Morphology of Melting Snow Charles
A. Knight Journal
of the Atmospheric Sciences Volume
36, Issue 6 (June 1979) pp. 1123-1130
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Characteristics through the Melting Layer of Stratiform Clouds Ronald
E. Stewart, John D. Marwitz, John C. Pace, Richard
E. Carbone Journal
of the Atmospheric Sciences Volume
41, Issue 22 (November 1984) pp. 3227-3237 doi:
http://dx.doi.org/10.1175/1520-0469(1984)041<3227:CTTMLO>2.0.CO;2
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Observations of Copolar Correlation
Coefficient through a Bright Band at Vertical Incidence D.
S. Zrnić, R. Raghavan, V. Chandrasekar Journal
of Applied Meteorology Volume
33, Issue 1 (January 1994) pp. 45-52 doi:
http://dx.doi.org/10.1175/1520-0450(1994)033<0045:OOCCCT>2.0.CO;2
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Airborne Radar Observations of Eye Configuration Changes,
Bright Band Distribution, and Precipitation Tilt During the 1969 Multiple
Seeding Experiments in Hurricane Debbie PETER
G. BLACK, HARRY V. SENN, CHARLES L. COURTRIGHT Monthly
Weather Review Volume
100, Issue 3 (March 1972) pp. 208-217 doi:
http://dx.doi.org/10.1175/1520-0493(1972)100<0208:AROOEC>2.3.CO;2
[Abstract]
[PDF] [Add
to Favorites] |
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Lidar and Triple-Wavelength Doppler Radar Measurements of the
Melting Layer: A Revised Model for Dark- and Brightband Phenomena Kenneth
Sassen, James R. Campbell, Jiang Zhu, Pavlos Kollias, Matthew Shupe, Christopher Williams Journal
of Applied Meteorology Volume
44, Issue 3 (March 2005) pp. 301-312 doi:
http://dx.doi.org/10.1175/JAM-2197.1
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Synoptic and Topographic Variability of Northern California Precipitation
Characteristics in Landfalling Winter Storms
Observed during CALJET David
E. Kingsmill, Paul J. Neiman, F. Martin Ralph, Allen B. White Monthly
Weather Review Volume
134, Issue 8 (August 2006) pp. 2072-2094 doi:
http://dx.doi.org/10.1175/MWR3166.1
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Error Statistics of VPR Corrections in Stratiform
Precipitation Aldo
Bellon, Gyu Won Lee, Isztar
Zawadzki Journal
of Applied Meteorology Volume
44, Issue 7 (July 2005) pp. 998-1015 doi:
http://dx.doi.org/10.1175/JAM2253.1
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THE INVERSION “BRIGHT BAND” PATRICK
E. HUGHES, RICHARD A. WOOD Monthly
Weather Review Volume
90, Issue 3 (March 1962) pp. 97-102 doi:
http://dx.doi.org/10.1175/1520-0493(1962)090<0097:TIBB>2.0.CO;2
[Abstract]
[PDF] [Add
to Favorites] |
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Polarization Diversity Lidar Returns from Virga
and Precipitation: Anomalies and the Bright Band Analogy Kenneth
Sassen Journal
of Applied Meteorology Volume
15, Issue 3 (March 1976) pp. 292-300 doi:
http://dx.doi.org/10.1175/1520-0450(1976)015<0292:PDLRFV>2.0.CO;2
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Brightband Identification Based on Vertical Profiles of
Reflectivity from the WSR-88D Jian
Zhang, Carrie Langston, Kenneth Howard Journal
of Atmospheric and Oceanic Technology Volume
25, Issue 10 (October 2008) pp. 1859-1872 doi:
http://dx.doi.org/10.1175/2008JTECHA1039.1
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Structure of the Melting Layer in Mesoscale Convective System
Stratiform Precipitation Paul
T. Willis, Andrew J. Heymsfield Journal
of the Atmospheric Sciences Volume
46, Issue 13 (July 1989) pp. 2008-2025 doi:
http://dx.doi.org/10.1175/1520-0469(1989)046<2008:SOTMLI>2.0.CO;2
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Radar Observations and Simulation of the Melting Layer of
Precipitation Wim
Klaassen Journal
of the Atmospheric Sciences Volume
45, Issue 24 (December 1988) pp. 3741-3753 doi:
http://dx.doi.org/10.1175/1520-0469(1988)045<3741:ROASOT>2.0.CO;2
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The Kinematics of Orographic Airflow During Sierra Storms John
D. Marwitz Journal
of the Atmospheric Sciences Volume
40, Issue 5 (May 1983) pp. 1218-1227 doi:
http://dx.doi.org/10.1175/1520-0469(1983)040<1218:TKOOAD>2.0.CO;2
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Constraining Microwave Brightness Temperatures by Radar
Brightband Observations A. Battaglia, C. Kummerow,
Dong-Bin Shin, C. Williams Journal
of Atmospheric and Oceanic Technology Volume
20, Issue 6 (June 2003) pp. 856-871 doi:
http://dx.doi.org/10.1175/1520-0426(2003)020<0856:CMBTBR>2.0.CO;2
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Tropical Rainfall Associated with Convective and Stratiform
Clouds: Intercomparison of Disdrometer and Profiler
Measurements Ali
Tokay, David A. Short, Christopher R. Williams, Warner L. Ecklund,
Kenneth S. Gage Journal
of Applied Meteorology Volume
38, Issue 3 (March 1999) pp. 302-320 doi:
http://dx.doi.org/10.1175/1520-0450(1999)038<0302:TRAWCA>2.0.CO;2
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Microwave Radiative Transfer in the Mixed-Phase Regions of
Tropical Rainfall T.
T. Wilheit, P. V. Hobbs, K. Jin,
A. L. Rangno, M. E. Triesky,
J. R. Wang Journal
of Atmospheric and Oceanic Technology Volume
23, Issue 11 (November 2006) pp. 1519-1529 doi:
http://dx.doi.org/10.1175/JTECH1944.1
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Collocated Radar and Radiosonde Observations of a Double-Brightband Melting Layer in Northern CaliforniaBrooks
E. Martner, Paul J. Neiman, Allen B. White Monthly
Weather Review Volume
135, Issue 5 (May 2007) pp. 2016-2024 doi:
http://dx.doi.org/10.1175/MWR3383.1 0804 1）2本のブライトバンド;自動検出 |
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The Development of Drop Size Distributions in Light Rain..I.
Zawadzki, E. Monteiro, F. Fabry Journal
of the Atmospheric Sciences Volume
51, Issue 8 (April 1994) pp. 1100-1114. A
model of rain development based on the quasi-stochastic coalescence equation
and including the sedimentation of drops has been used to study the formation
of drop size distributions in conditions of weak updraft. Comparisons with
“box model” results indicate that sedimentation effects are crucial in
establishing the shapes of the distribution. Under realistic conditions of cloud
droplet distribution with size, the raindrop size distributions as simulated
by the model compare well with observations of orographic rain made in
Hawaii. On the other hand, Doppler radar measurements of drop size
distributions just below a bright band confirm that the Marshall-Palmer
distribution results from processes affecting particles in the solid phase
rather than from the interaction of raindrops. 融解層より下では粒径分布はMP分布に従い、途中に雨滴粒子が入ってくる影響よりも、雪の粒径分布の影響が卓越している。ボックスモデルで粒径分布をシミュレーション。1/26’12 doi:
http://dx.doi.org/10.1175/1520-0469(1994)051<1100:TDODSD>2.0.CO;2 |
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Rain Resulting from Melting Ice Particles..Louis
J. Battan Journal
of Applied Meteorology Volume
16, Issue 6 (June 1977) pp. 595-604. By
means of a zenith-pointing radar, observations were made of the
reflectivities and Doppler spectra in orthogonal planes as a dissipating
shower exhibiting a bright band passed overhead. The observations have been
used to test various procedures for estimating hydrometeor parameters from
measurements of radar reflectivitity. They involve
assumptions that the raindrop diameters were exponentially distributed,
preferably in the manner prescribed by the Marshall-Palmer distribution. It
is concluded that, in this case, such an assumption was not valid in regions
where it was expected to be valid. As a consequence, estimates of median
raindrop diameters and updraft velocities calculated from radar
reflectivities were in error. The analyses indicate that raindrop size
sorting under the influence of vertical wind shear can account for the
observed non-exponential size distributions. doi:
http://dx.doi.org/10.1175/1520-0450(1977)016<0595:RRFMIP>2.0.CO;2 |
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Polarimetric Signatures in the Stratiform Region of a
Mesoscale Convective System D.
S. Zrnic, N. Balakrishnan, C. L. Ziegler, V. N. Bringi, K. Aydin, T. Matejka Journal
of Applied Meteorology Volume
32, Issue 4 (April 1993) pp. 678-693 doi:
http://dx.doi.org/10.1175/1520-0450(1993)032<0678:PSITSR>2.0.CO;2
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Doppler Radar Wind and Reflectivity Signatures with
Overrunning and Freezing-Rain Episodes: Preliminary Results Erwin
T. Prater, Alan A. Borho Journal
of Applied Meteorology Volume
31, Issue 11 (November 1992) pp. 1350-1358 doi:
http://dx.doi.org/10.1175/1520-0450(1992)031<1350:DRWARS>2.0.CO;2
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Measurements and Simulations of Nadir-Viewing Radar Returns
from the Melting Layer at X and W Bands Liang
Liao, Robert Meneghini, Lin Tian, Gerald M.
Heymsfield Journal
of Applied Meteorology and Climatology Volume
48, Issue 11 (November 2009) pp. 2215-2226 doi:
http://dx.doi.org/10.1175/2009JAMC2033.1
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Typical Patterns of Microwave Signatures and Vertical Profiles
of Precipitation in the Midlatitudes from TRMM Data Munehisa K.
Yamamoto, Kenji Nakamura Journal
of Applied Meteorology and Climatology Volume
50, Issue 6 (June 2011) pp. 1236-1254 doi:
http://dx.doi.org/10.1175/2010JAMC2539.1
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Vertical Structure of Precipitation and Related Microphysics
Observed by NOAA Profilers and TRMM during NAME 2004 Christopher
R. Williams, Allen B. White, Kenneth S. Gage, F. Martin Ralph Journal
of Climate Volume
20, Issue 9 (May 2007) pp. 1693-1712 doi:
http://dx.doi.org/10.1175/JCLI4102.1
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Polarimetric Estimates of a 1-Month Accumulation of Light Rain
with a 3-cm Wavelength Radar L. Borowska, D. Zrnić, A. Ryzhkov,
P. Zhang, C. Simmer Journal
of Hydrometeorology Volume
12, Issue 5 (October 2011) pp. 1024-1039 doi:
http://dx.doi.org/10.1175/2011JHM1339.1
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Automated Detection of the Bright Band Using WSR-88D Data Jonathan
J. Gourley, Chris M. Calvert Weather
and Forecasting Volume
18, Issue 4 (August 2003) pp. 585-599 doi:
http://dx.doi.org/10.1175/1520-0434(2003)018<0585:ADOTBB>2.0.CO;2
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Airflow and Precipitation Properties within the Stratiform
Region of Tropical Storm Gabrielle during Landfall Dong-Kyun Kim, Kevin R. Knupp,
Christopher R. Williams Monthly
Weather Review Volume
137, Issue 6 (June 2009) pp. 1954-1971 doi:
http://dx.doi.org/10.1175/2008MWR2754.1
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Vertical Structures of Precipitation in Cyclones Crossing the
Oregon Cascades Socorro
Medina, Ellen Sukovich, Robert A. Houze Jr. Monthly
Weather Review Volume
135, Issue 10 (October 2007) pp. 3565-3586 doi:
http://dx.doi.org/10.1175/MWR3470.1
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Long-Term Radar Observations of the Melting Layer of
Precipitation and Their Interpretation Frederic
Fabry, Isztar Zawadzki Journal
of the Atmospheric Sciences Volume
52, Issue 7 (April 1995) pp. 838-851 doi:
http://dx.doi.org/10.1175/1520-0469(1995)052<0838:LTROOT>2.0.CO;2
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Inner Core Structure of Hurricane Alicia from Airborne Doppler
Radar Observations Frank
D. Marks Jr., Robert A. Houze Jr. Journal
of the Atmospheric Sciences Volume
44, Issue 9 (May 1987) pp. 1296-1317 doi:
http://dx.doi.org/10.1175/1520-0469(1987)044<1296:ICSOHA>2.0.CO;2
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A Study on the Relation between Terminal Velocity and VHF
Backscatter from Precipitation Particles Using the Chung-Li VHF Radar Yen-Hsyang Chu, Shun-Peng Shih, Ching-Lun
Su, Kan-Lin Lee, Tzer-Horng
Lin, Wei-Chung Liang Journal
of Applied Meteorology Volume
38, Issue 12 (December 1999) pp. 1720-1729 doi:
http://dx.doi.org/10.1175/1520-0450(1999)038<1720:ASOTRB>2.0.CO;2
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Coastal Orographic Rainfall Processes Observed by Radar during
the California Land-Falling Jets Experiment Allen
B. White, Paul J. Neiman, F. Martin Ralph, David E. Kingsmill, P. Ola G. Persson Journal
of Hydrometeorology Volume
4, Issue 2 (April 2003) pp. 264-282 doi:
http://dx.doi.org/10.1175/1525-7541(2003)4<264:CORPOB>2.0.CO;2
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Horizontal Distribution of Electrical and Meteorological
Conditions across the Stratiform Region of a Mesoscale Convective System Maribeth Stolzenburg, Thomas C. Marshall, W. David Rust, Bradley
F. Smull Monthly
Weather Review Volume
122, Issue 8 (August 1994) pp. 1777-1797 doi:
http://dx.doi.org/10.1175/1520-0493(1994)122<1777:HDOEAM>2.0.CO;2
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Differences between East and West Pacific Rainfall Systems Wesley
Berg, Christian Kummerow, Carlos A. Morales Journal
of Climate Volume
15, Issue 24 (December 2002) pp. 3659-3672 doi:
http://dx.doi.org/10.1175/1520-0442(2002)015<3659:DBEAWP>2.0.CO;2
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Comparison of Freezing-Level Altitudes from the NCEP
Reanalysis with TRMM Precipitation Radar Brightband Data Gettys N.
Harris Jr., Kenneth P. Bowman, Dong-Bin Shin Journal
of Climate Volume
13, Issue 23 (December 2000) pp. 4137-4148 doi:
http://dx.doi.org/10.1175/1520-0442(2000)013<4137:COFLAF>2.0.CO;2
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40
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A Summary of Reflectivity Profiles from the First Year of TRMM
Radar Data Dong-Bin
Shin, Gerald R. North, Kenneth P. Bowman Journal
of Climate Volume
13, Issue 23 (December 2000) pp. 4072-4086 doi:
http://dx.doi.org/10.1175/1520-0442(2000)013<4072:ASORPF>2.0.CO;2
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Evaluation and Comparison of Microphysical Algorithms in
ARW-WRF Model Simulations of Atmospheric River Events Affecting the
California Coast Isidora Jankov, Jian-Wen Bao, Paul J.
Neiman, Paul J. Schultz, Huiling Yuan, Allen B.
White Journal
of Hydrometeorology Volume
10, Issue 4 (August 2009) pp. 847-870 doi:
http://dx.doi.org/10.1175/2009JHM1059.1
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A Real-Time Algorithm for the Correction of Brightband Effects
in Radar-Derived QPE Jian
Zhang, Youcun Qi Journal
of Hydrometeorology Volume
11, Issue 5 (October 2010) pp. 1157-1171 doi:
http://dx.doi.org/10.1175/2010JHM1201.1
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Aircraft Multifrequency Passive
Microwave Observations of Light Precipitation over the Ocean Robert
F. Adler, Ida M. Hakkarinen Journal
of Atmospheric and Oceanic Technology Volume
8, Issue 2 (April 1991) pp. 201-220 doi:
http://dx.doi.org/10.1175/1520-0426(1991)008<0201:AMPMOO>2.0.CO;2
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The Interpretation and Meteorological Application of Radar
Backscatter Amplitude Ratios at Linear Polarizations A.
R. Jameson Journal
of Atmospheric and Oceanic Technology Volume
6, Issue 6 (December 1989) pp. 908-919 doi:
http://dx.doi.org/10.1175/1520-0426(1989)006<0908:TIAMAO>2.0.CO;2
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Differential Reflectivity Calibration for Operational Radars R. Bechini, L. Baldini, R. Cremonini,
E. Gorgucci Journal
of Atmospheric and Oceanic Technology Volume
25, Issue 9 (September 2008) pp. 1542-1555 doi:
http://dx.doi.org/10.1175/2008JTECHA1037.1
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Classification of Tropical Precipitating Systems Using Wind
Profiler Spectral Moments. Part I: Algorithm Description and Validation T.
Narayana Rao, N. V. P. Kirankumar, B. Radhakrishna, D. Narayana Rao, K. Nakamura Journal
of Atmospheric and Oceanic Technology Volume
25, Issue 6 (June 2008) pp. 884-897 doi:
http://dx.doi.org/10.1175/2007JTECHA1031.1
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Comparison of Radar Reflectivity and Vertical Velocity
Observed with a Scannable C-Band Radar and Two UHF
Profilers in the Lower Troposphere M. Lothon, B. Campistron, S.
Jacoby-Koaly, B. Bénech,
F. Lohou, F. Girard-Ardhuin Journal
of Atmospheric and Oceanic Technology Volume
19, Issue 6 (June 2002) pp. 899-910 doi:
http://dx.doi.org/10.1175/1520-0426(2002)019<0899:CORRAV>2.0.CO;2
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Electric Fields and Charges near 0°C in Stratiform Clouds Tommy
R. Shepherd, W. David Rust, Thomas C. Marshall Monthly
Weather Review Volume
124, Issue 5 (May 1996) pp. 919-938 doi:
http://dx.doi.org/10.1175/1520-0493(1996)124<0919:EFACNI>2.0.CO;2
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The Structure of a Small, Intense Hurricane—Inez 1966 Harry
F. Hawkins, Stephen M. Imbembo Monthly
Weather Review Volume
104, Issue 4 (April 1976) pp. 418-442 doi:
http://dx.doi.org/10.1175/1520-0493(1976)104<0418:TSOASI>2.0.CO;2
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Vertical Structure of Convective Systems during NAME 2004 David
G. Lerach, Steven A. Rutledge, Christopher R.
Williams, Robert Cifelli Monthly
Weather Review Volume
138, Issue 5 (May 2010) pp. 1695-1714 doi:
http://dx.doi.org/10.1175/2009MWR3053.1
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Development of an Effective Double-Moment Cloud Microphysics
Scheme with Prognostic Cloud Condensation Nuclei (CCN) for Weather and
Climate Models Kyo-Sun
Sunny Lim, Song-You Hong Monthly
Weather Review Volume
138, Issue 5 (May 2010) pp. 1587-1612 doi:
http://dx.doi.org/10.1175/2009MWR2968.1
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TELEX The Thunderstorm Electrification and Lightning
Experiment Donald
R. MacGorman, W. David Rust, Conrad L. Ziegler,
Edward R. Mansell, Terry J. Schuur, Michael I. Biggerstaff, Jerry M. Straka,
Eric C. Bruning, Kristin M. Kuhlman, Nicole R.
Lund, Clark Payne, Nicholas S. Biermann, William H.
Beasley, Larry D. Carey, Paul R. Krehbiel, William
Rison, Kenneth B. Eack Bulletin
of the American Meteorological Society Volume
89, Issue 7 (July 2008) pp. 997-1013 doi:
http://dx.doi.org/10.1175/2007BAMS2352.1
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A New Look at the Melting Layer Fiona
J. Drummond, R. R. Rogers, S. A. Cohn, W. L. Ecklund,
D. A. Carter, J. S. Wilson Journal
of the Atmospheric Sciences Volume
53, Issue 5 (March 1996) pp. 759-769 doi:
http://dx.doi.org/10.1175/1520-0469(1996)053<0759:ANLATM>2.0.CO;2
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The Transition Zone and Secondary Maximum of Radar
Reflectivity behind a Midlatitude Squall Line:
Results Retrieved from Doppler Radar Data Scott
A. Braun, Robert A. Houze Jr. Journal
of the Atmospheric Sciences Volume
51, Issue 19 (October 1994) pp. 2733-2755 doi:
http://dx.doi.org/10.1175/1520-0469(1994)051<2733:TTZASM>2.0.CO;2
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EYE REGION OF HURRICANE EDNA, 1954 Edwin
Kessler III Journal
of Meteorology Volume
15, Issue 3 (June 1958) pp. 264-270 doi:
http://dx.doi.org/10.1175/1520-0469(1958)015<0264:EROHE>2.0.CO;2
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DROP SIZE AND RADAR STRUCTURE OF A PRECIPITATION STREAMER David
Atlas Journal
of Meteorology Volume
14, Issue 3 (June 1957) pp. 261-271 doi:
http://dx.doi.org/10.1175/1520-0469(1957)014<0261:DSARSO>2.0.CO;2
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Classification and Characterization of Tropical Precipitation
Based on High-Resolution Airborne Vertical Incidence Radar. Part I:
Classification Bart
Geerts, Yu Dawei Journal
of Applied Meteorology Volume
43, Issue 11 (November 2004) pp. 1554-1566 doi:
http://dx.doi.org/10.1175/JAM2158.1
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Drop Size Distribution Retrieval with Polarimetric Radar:
Model and Application Edward
A. Brandes, Guifu Zhang, J. Vivekanandan Journal
of Applied Meteorology Volume
43, Issue 3 (April 2004) pp. 461-475 doi:
http://dx.doi.org/10.1175/1520-0450(2004)043<0461:DSDRWP>2.0.CO;2
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Discrimination between Rain and Snow with a Polarimetric RadarA.
V. Ryzhkov, D. S. Zrnic Journal
of Applied Meteorology Volume
37, Issue 10 (October 1998) pp. 1228-1240 Polarimetric signatures of snow precipitation for six Oklahoma snowstorms are examined. The available data consist of specific differential phase KDP, differential reflectivity ZDR, cross-correlation coefficient rou-hv, and radar reflectivity factor Z. These data were obtained with the 10-cm-wavelength Cimarron polarimetric weather radar. The data suggest that in pure snow the average values of KDP and ZDR do not follow a systematic trend with change of the radar reflectivity factor if Z < 35 dBZ; this is not the case in rain. Precipitation is qualified as snow if the average ZDR is less than 0.2 dB for Z < 35 dBZ. The presence of a bright band with a pronounced rou-hv minimum and ZDR maximum is a good discernible feature for discriminating between snow and rain. Thus, a localized deep minimum of the cross-correlation coefficient delineates the transition region between snow and rain in the horizontal direction if sufficiently large snowflakes are generated in the transition area. Otherwise, a sharp change of ZDR can be used to localize the position of the snow–rain line. [Abstract]
[Full
Text] [PDF (1556 KB)] [Add
to Favorites] doi:
http://dx.doi.org/10.1175/1520-0450(1998)037<1228:DBRASW>2.0.CO;2 S帯偏波レーダで確認される雨雪判別。オクラホマの6降雨。KdpとZDRの特徴はZほど系統的な変化を示さない。35ｄBZ未満の時。ZDR<0.2、35ｄBZ未満で雪。ρhv最小とZDR最大でブライトバンドが顕著で、雨雪の判別に有効。大粒子が十分にあればρhvで平面的に雨と雪の遷移線を分けることができる。また、ZDRの急激な変化【変化率】は雨雪線を引くのに利用できる。1/17’12 |
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Differential Doppler Velocity: A Radar Parameter for
Characterizing Hydrometeor Size Distributions Damian
R. Wilson, Anthony J. Illingworth, T. Mark Blackman Journal
of Applied Meteorology Volume
36, Issue 6 (June 1997) pp. 649-663 doi:
http://dx.doi.org/10.1175/1520-0450-36.6.649
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Classification of precipitation types during transitional
winter weather using the RUC model and polarimetric radar retrievals Terry
J. Schuur, Hyang-Suk
Park, Alexander V. Ryzhkov, Heather D. Reeves Journal
of Applied Meteorology and Climatology Volume
0, Issue 0 ( ) pp. doi:
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Real-Time Comparisons of VPR-Corrected Daily Rainfall
Estimates with a Gauge Mesonet Aldo
Bellon, Gyu Won Lee, Alamelu
Kilambi, Isztar Zawadzki Journal
of Applied Meteorology and Climatology Volume
46, Issue 6 (June 2007) pp. 726-741 doi:
http://dx.doi.org/10.1175/JAM2502.1
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Characteristics of Rain Integral Parameters during Tropical
Convective, Transition, and Stratiform Rain at Gadanki
and Its Application in Rain Retrieval Sanjay
Sharma, Mahen Konwar, Diganta Kumar Sarma, M. C. R. Kalapureddy, A. R. Jain Journal
of Applied Meteorology and Climatology Volume
48, Issue 6 (June 2009) pp. 1245-1266 doi:
http://dx.doi.org/10.1175/2008JAMC1948.1
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Rain versus Snow in the Sierra Nevada, California: Comparing
Doppler Profiling Radar and Surface Observations of Melting Level Jessica
D. Lundquist, Paul J. Neiman, Brooks Martner, Allen
B. White, Daniel J. Gottas, F. Martin Ralph Journal
of Hydrometeorology Volume
9, Issue 2 (April 2008) pp. 194-211 doi:
http://dx.doi.org/10.1175/2007JHM853.1
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Developing a Performance Measure for Snow-Level Forecasts Allen
B. White, Daniel J. Gottas, Arthur F. Henkel, Paul
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of Hydrometeorology Volume
11, Issue 3 (June 2010) pp. 739-753 doi:
http://dx.doi.org/10.1175/2009JHM1181.1
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Thermodynamic and Kinematic Structure of a Snowband
and Freezing Rain Event during STORM-FEST Hunter
Coleman, John Marwitz Weather
and Forecasting Volume
17, Issue 1 (February 2002) pp. 27-46 doi:
http://dx.doi.org/10.1175/1520-0434(2002)017<0027:TAKSOA>2.0.CO;2
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An Integrated Approach to Error Correction for Real-Time
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of Atmospheric and Oceanic Technology Volume
23, Issue 1 (January 2006) pp. 67-79 doi:
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An Automated Brightband Height Detection Algorithm for Use
with Doppler Radar Spectral Moments Allen
B. White, Daniel J. Gottas, Eric T. Strem, F. Martin Ralph, Paul J. Neiman Journal
of Atmospheric and Oceanic Technology Volume
19, Issue 5 (May 2002) pp. 687-697 doi:
http://dx.doi.org/10.1175/1520-0426(2002)019<0687:AABHDA>2.0.CO;2
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A Midlatitude Squall Line with a
Trailing Region of Stratiform Rain: Radar and Satellite Observations Bradley
F. Smull, Robert A. Houze Jr. Monthly
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113, Issue 1 (January 1985) pp. 117-133 doi:
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Assimilation of Simulated Polarimetric Radar Data for a Convective
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Jung, Guifu Zhang, Ming Xue Monthly
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136, Issue 6 (June 2008) pp. 2228-2245 doi:
http://dx.doi.org/10.1175/2007MWR2083.1
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The Characteristics and Evolution of Orographic Snow Clouds
under Weak Cold Advection Kenichi
Kusunoki, Masataka Murakami, Mizuho Hoshimoto, Narihiro
Orikasa, Yoshinori Yamada, Hakaru Mizuno, Kyosuke Hamazu, Hideyuki
Watanabe Monthly
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Hurricane Georges's Landfall in the
Dominican Republic: Detailed Airborne Doppler Radar Imagery Bart
Geerts, Gerald M. Heymsfield, Lin Tian, Jeffrey B.
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of the American Meteorological Society Volume
81, Issue 5 (May 2000) pp. 999-1018 doi:
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Local Structure of the Convective Boundary Layer from a
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of the Atmospheric Sciences Volume
57, Issue 14 (July 2000) pp. 2281-2296 doi:
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Mesoscale and Convective-Scale Characteristics of Mature
Hurricanes. Part I: General Observations by Research Aircraft David
F. Jorgensen Journal
of the Atmospheric Sciences Volume
41, Issue 8 (April 1984) pp. 1268-1286 doi:
http://dx.doi.org/10.1175/1520-0469(1984)041<1268:MACSCO>2.0.CO;2
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Accurate Determination of Vertical Air Velocities in Rain by
Doppler-Radar Wim
Klaassen Journal
of Climate and Applied Meteorology Volume
22, Issue 10 (October 1983) pp. 1788-1793 doi:
http://dx.doi.org/10.1175/1520-0450(1983)022<1788:ADOVAV>2.0.CO;2
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Mesobeta
Profiles to Extrapolate Radar Precipitation Measurements above the Alps to
the Ground Level Urs Germann, Jürg Joss Journal
of Applied Meteorology Volume
41, Issue 5 (May 2002) pp. 542-557 doi:
http://dx.doi.org/10.1175/1520-0450(2002)041<0542:MPTERP>2.0.CO;2
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A Melting-Layer Model for Passive/Active Microwave Remote
Sensing Applications. Part I: Model Formulation and Comparison with
Observations William
S. Olson, Peter Bauer, Nicolas F. Viltard, Daniel
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Liang Liao Journal
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40, Issue 7 (July 2001) pp. 1145-1163 doi:
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Comparisons of Cross Sections for Melting Hydrometeors as
Derived from Dielectric Mixing Formulas and a Numerical Method R. Meneghini, L. Liao Journal
of Applied Meteorology Volume
35, Issue 10 (October 1996) pp. 1658-1670 doi:
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Evaluation of Radar Precipitation Estimates from the National
Mosaic and Quantitative Precipitation Estimation System and the WSR-88D
Precipitation Processing System over the Conterminous United States Wanru Wu,
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Wu Journal
of Hydrometeorology Volume
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Observations of Winter-time US West Coast Precipitating
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Raindrop Size Distributions and Rain Characteristics in
California Coastal Rainfall for Periods with and without a Radar Bright Band Brooks
E. Martner, Sandra E. Yuter,
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of Hydrometeorology Volume
9, Issue 3 (June 2008) pp. 408-425 doi:
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The Life Cycle and Internal Structure of a Mesoscale
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Evolution of the Structure of Precipitation in Hurricane Allen
(1980) Frank
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Analysis of a Small, Vigorous Mesoscale Convective System in a
Low-Shear Environment. Part I: Formation, Radar Echo Structure, and Lightning
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The IMPROVE-1 Storm of 1–2 February 2001. Part II: Cloud
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Cross-Barrier Flow during Orographic Precipitation Events:
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A Numerical Study of the Stratiform Region of a Fast-Moving
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Dual-Doppler Radar Analysis of a Midlatitude
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The Structure and Evolution of Convection in a Tropical Cloud
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Passive Microwave Observations of the Stratiform Regions of
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A Double-Moment Multiple-Phase Four-Class Bulk Ice Scheme.
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end