scholarly journals Columnar Vertical Profile (CVP) Methodology for Validating Polarimetric Radar Retrievals in Ice Using In Situ Aircraft Measurements

2020 ◽  
Vol 37 (9) ◽  
pp. 1623-1642
Author(s):  
Amanda M. Murphy ◽  
Alexander Ryzhkov ◽  
Pengfei Zhang
Keyword(s):  
Vertical Profile ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Limited Region ◽  
Convective Systems ◽  
In Situ Data ◽  
Mesoscale Convective ◽  
Research Aircraft ◽  
Data Representative

AbstractA novel way to process polarimetric radar data collected via plan position indicator (PPI) scans and display those data in a time–height format is introduced. The columnar vertical profile (CVP) methodology uses radar data collected via multiple elevation scans, limited to data within a set region in range and azimuth relative to the radar, to create vertical profiles of polarimetric radar data representative of that limited region in space. This technique is compared to others existing in the literature, and various applications are discussed. Polarimetric ice microphysical retrievals are performed on CVPs created within the stratiform rain region of two mesoscale convective systems sampled during two field campaigns, where CVPs follow the track of research aircraft. Aircraft in situ data are collocated to microphysical retrieval data, and the accuracy of these retrievals is tested against other retrieval techniques in the literature.

scholarly journals Identification of Vertical Profiles of Reflectivity for Correction of Volumetric Radar Data Using Rainfall Classification

2010 ◽  
Vol 49 (10) ◽  
pp. 2167-2180 ◽  
Author(s):  
Pierre-Emmanuel Kirstetter ◽  
Hervé Andrieu ◽  
Guy Delrieu ◽  
Brice Boudevillain
Keyword(s):  
Vertical Profile ◽  
Positive Impact ◽  
Radar Data ◽  
Bias Reduction ◽  
Shallow Convection ◽  
Classification Procedure ◽  
Convective Systems ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation ◽  
Mesoscale Convective

Abstract Nonuniform beam filling associated with the vertical variation of atmospheric reflectivity is an important source of error in the estimation of rainfall rates by radar. It is, however, possible to correct for this error if the vertical profile of reflectivity (VPR) is known. This paper presents a method for identifying VPRs from volumetric radar data. The method aims at improving an existing algorithm based on the analysis of ratios of radar measurements at multiple elevation angles. By adding a rainfall classification procedure defining more homogeneous precipitation patterns, the issue of VPR homogeneity is specifically addressed. The method is assessed using the dataset from a volume-scanning strategy for radar quantitative precipitation estimation designed in 2002 for the Bollène radar (France). The identified VPR is more representative of the rain field than are other estimated VPRs. It has also a positive impact on radar data processing for precipitation estimation: while scatter remains unchanged, an overall bias reduction at all time steps is noticed (up to 6% for all events) whereas performance varies with type of events considered (mesoscale convective systems, cold fronts, or shallow convection) according to the radar-observation conditions. This is attributed to the better processing of spatial variations of the vertical profile of reflectivity for the stratiform regions. However, adaptation of the VPR identification in the difficult radar measurement context in mountainous areas and to the rainfall classification procedure proved challenging because of data fluctuations.

scholarly journals Precipitation Characteristics in West and East Africa from Satellite and in Situ Observations

2017 ◽  
Vol 18 (6) ◽  
pp. 1799-1805 ◽  
Author(s):  
Amin K. Dezfuli ◽  
Charles M. Ichoku ◽  
Karen I. Mohr ◽  
George J. Huffman
Keyword(s):  
East Africa ◽  
Tropical Rainfall Measuring Mission ◽  
Convective Rainfall ◽  
Convective Systems ◽  
In Situ Data ◽  
Precipitation Measurement ◽  
Mesoscale Convective ◽  
Rain Events ◽  
Global Precipitation

Abstract Using in situ data, three precipitation classes are identified for rainy seasons of West and East Africa: weak convective rainfall (WCR), strong convective rainfall (SCR), and mesoscale convective systems (MCSs). Nearly 75% of the total seasonal precipitation is produced by the SCR and MCSs, even though they represent only 8% of the rain events. Rain events in East Africa tend to have a longer duration and lower intensity than in West Africa, reflecting different characteristics of the SCR and MCS events in these two regions. Surface heating seems to be the primary convection trigger for the SCR, particularly in East Africa, whereas the WCR requires a dynamical trigger such as low-level convergence. The data are used to evaluate the performance of the recently launched Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) project. The IMERG-based precipitation shows significant improvement over its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), particularly in capturing the MCSs, due to its improved temporal resolution.

The Analysis and Prediction of Microphysical States and Polarimetric Radar Variables in a Mesoscale Convective System Using Double-Moment Microphysics, Multinetwork Radar Data, and the Ensemble Kalman Filter

2014 ◽  
Vol 142 (1) ◽  
pp. 141-162 ◽  
Author(s):  
Bryan J. Putnam ◽  
Ming Xue ◽  
Youngsun Jung ◽  
Nathan Snook ◽  
Guifu Zhang
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Cold Pool ◽  
Convective System ◽  
Polarimetric Radar ◽  
Microphysics Scheme ◽  
Mesoscale Convective ◽  
Double Moment

Abstract Doppler radar data are assimilated with an ensemble Kalman Filter (EnKF) in combination with a double-moment (DM) microphysics scheme in order to improve the analysis and forecast of microphysical states and precipitation structures within a mesoscale convective system (MCS) that passed over western Oklahoma on 8–9 May 2007. Reflectivity and radial velocity data from five operational Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band radars as well as four experimental Collaborative and Adaptive Sensing of the Atmosphere (CASA) X-band radars are assimilated over a 1-h period using either single-moment (SM) or DM microphysics schemes within the forecast ensemble. Three-hour deterministic forecasts are initialized from the final ensemble mean analyses using a SM or DM scheme, respectively. Polarimetric radar variables are simulated from the analyses and compared with polarimetric WSR-88D observations for verification. EnKF assimilation of radar data using a multimoment microphysics scheme for an MCS case has not previously been documented in the literature. The use of DM microphysics during data assimilation improves simulated polarimetric variables through differentiation of particle size distributions (PSDs) within the stratiform and convective regions. The DM forecast initiated from the DM analysis shows significant qualitative improvement over the assimilation and forecast using SM microphysics in terms of the location and structure of the MCS precipitation. Quantitative precipitation forecasting skills are also improved in the DM forecast. Better handling of the PSDs by the DM scheme is believed to be responsible for the improved prediction of the surface cold pool, a stronger leading convective line, and improved areal extent of stratiform precipitation.

scholarly journals Vertical profile of peroxyacetyl nitrate (PAN) from MIPAS-STR measurements over Brazil in February 2005 and its contribution to tropical UT NO<sub>y</sub> partitioning

2008 ◽  
Vol 8 (16) ◽  
pp. 4891-4902 ◽  
Author(s):  
C. Keim ◽  
G. Y. Liu ◽  
C. E. Blom ◽  
H. Fischer ◽  
T. Gulde ◽  
...  
Keyword(s):  
Vertical Profile ◽  
Trace Gases ◽  
Simultaneous Measurements ◽  
Remote Sensor ◽  
Research Aircraft ◽  
Careful Handling ◽  
Tropical Troposphere ◽  
Selection Of ◽  
Made In

Abstract. We report on the retrieval of PAN (CH3C(O)OONO2) in the upper tropical troposphere from limb measurements by the remote-sensor MIPAS-STR on board the Russian high altitude research aircraft M55-Geophysica. The measurements were performed close to Araçatuba, Brazil, on 17 February 2005. The retrieval was made in the spectral range 775–820 cm−1 where PAN exhibits its strongest feature but also more than 10 species interfere. Especially trace gases such as CH3CCl3, CFC-113, CFC-11, and CFC-22, emitting also in spectrally broad not-resolved branches, make the processing of PAN prone to errors. Therefore, the selection of appropriate spectral windows, the separate retrieval of several interfering species and the careful handling of the water vapour profile are part of the study presented. The retrieved profile of PAN has a maximum of about 0.14 ppbv at 10 km altitude, slightly larger than the lowest reported values (<0.1 ppbv) and much lower than the highest reported in the literature (0.65 ppbv). Besides the NOy constituents measured by MIPAS-STR (HNO3, ClONO2, HO2NO2, PAN), the in situ instruments aboard the Geophysica provide simultaneous measurements of NO, NO2, and the sum NOy. Comparing the sum of in-situ and remotely derived NO+NO2+HNO3+ClONO2+HO2NO2+PAN with total NOy a deficit of 30–40% (0.2–0.3 ppbv) in the troposphere remains unexplained whereas the values fit well in the stratosphere.

scholarly journals Vertical Moistening by AMMA Mesoscale Convective Systems

2011 ◽  
Vol 28 (5) ◽  
pp. 617-639 ◽  
Author(s):  
G. Scialom ◽  
Y. Lemaître
Keyword(s):  
Energy Transport ◽  
Low Cost ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Mixing Ratio ◽  
Convective Systems ◽  
Wind Analysis ◽  
Empirical Relations ◽  
Convective Scale ◽  
Mesoscale Convective

Abstract The apparent heat source Q1 and the apparent moisture sink Q2 are crucial parameters for precipitating systems studies because they allow for the evaluation of their contribution in water and energy transport and infer some of the mechanisms that are responsible for their evolution along their lifetime. In this paper, a new approach is proposed to estimate Q2 budgets from radar observations within precipitating areas at the scale of the measurements, that is, either convective scale or mesoscale, depending on the selected retrieval zone. This approach relies upon a new analysis of the radar reflectivity based on the concept of the traditional velocity–azimuth display (VAD) analysis. From the following five steps, Q2 is deduced from velocity and reflectivity fields: (i) mixing ratio retrieval using empirical relations, (ii) radial wind analysis using the VAD analysis, (iii) radar reflectivity analysis using a new analysis called reflectivity–azimuth display (RAD), (iv) retrieval of mixing ratio derivatives, and (v) Q2 retrieval. The originality and the main interest of the present approach with respect to previous studies rely on the fact it uses radar data alone and is based on a relatively low-cost analysis, allowing future systematic application on large datasets. In the present paper, this analysis is described and its robustness is evaluated and illustrated on three cases observed during the African Monsoon Multidisciplinary Analyses (AMMA) special observing period (SOP) field experiment (15 June–15 September) by means of the Recherche sur les Orages et Nuages par un Système Associé de Radars Doppler (RONSARD) radar. Results are analyzed in terms of the convective or stratiform character of observed precipitation.

scholarly journals Triple-frequency radar retrieval of microphysical properties of snow

2021 ◽  
Vol 14 (11) ◽  
pp. 7243-7254
Author(s):  
Kamil Mroz ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew Heymsfield ◽  
Alain Protat ◽  
...  
Keyword(s):  
Water Content ◽  
Radar Data ◽  
Characteristic Size ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
Radar Measurements ◽  
Highly Correlated ◽  
Mean Square Errors

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterised by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment For Future Precipitation Mission. During this campaign, in situ microphysical probes were mounted on the same aeroplane as the radars. This nearly perfectly co-located dataset of the remote and in situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content (IWC) and mean mass-weighted diameters obtaining root-mean-square errors of 0.13 and 0.15, respectively, for log 10IWC and log 10Dm. The retrieval of the degree of riming is more challenging, and only the algorithm that uses Doppler information obtains results that are highly correlated with the in situ data.

scholarly journals Classification of Rainfall Types Using Parsivel Disdrometer and S-Band Polarimetric Radar in Central Korea

2020 ◽  
Vol 12 (4) ◽  
pp. 642 ◽  
Author(s):  
Jui Le Loh ◽  
Dong-In Lee ◽  
Mi-Young Kang ◽  
Cheol-Hwan You
Keyword(s):  
Vertical Profile ◽  
Drop Size ◽  
Classification Scheme ◽  
Radar Data ◽  
Number Concentration ◽  
Polarimetric Radar ◽  
Retrieval Method ◽  
Median Volume ◽  
Better Than

Tools to identify and classify stratiform and convective rains at various times of the 12 days from June 2015 to March 2016 in Jincheon, Korea, were developed by using a Parsivel disdrometer and S-band polarimetric (S-POL) radar data. Stratiform and convective rains were identified using three different methods (vertical profile of reflectivity (VPR), the method proposed by Bringi et al. (BR03), and a combination of the two (BR03-VPR)) by using a Parsivel disdrometer for its applications to radar as a reference. BR03-VPR exhibits a better classification scheme than the VPR and BR03 methods. The rain types were compared using the drop size distribution (DSD) retrieved from polarimetric variables and reflectivity only. By using the DSD variables, a new convective/stratiform classification line of the log-normalized droplet number concentration ( log 10 N w ) − median volume diameter ( D 0 ) was derived for this area to classify the rainfall types using DSD variables retrieved from the polarimetric radar. For the radar variables, the method by Steiner et al. (SHY95) was found to be the best method, with 0.00% misclassification of the stratiform rains. For the convective rains, the DSD retrieval method performed better. However, for both stratiform and convective rains, the fuzzy method performed better than the SHY95 and DSD retrieval methods.

On the diurnal cycle of rainfall and convection over Lake Victoria and its catchment. Part 1: Rainfall and Mesoscale Convective Systems

2021 ◽  
Author(s):  
Sharon E. Nicholson ◽  
Adam T. Hartman ◽  
Douglas A. Klotter
Keyword(s):  
Diurnal Cycle ◽  
Lake Victoria ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Early Evening ◽  
Lake Effect ◽  
Mesoscale Convective ◽  
Dry Seasons

AbstractThis article examines the diurnal cycle of lake-effect rains over Lake Victoria and of rainfall in the surrounding catchment. The analysis focuses on four months, which represent the two wet seasons (April and November) and the two dry seasons (February and July). Lake-effect rains are strongest in April, weakest in July. In all cases there is a nocturnal rainfall maximum over the lake and a daytime maximum over the catchment, with the transition between rainfall over the lake and over the catchment occurring between 1200 and 1500 LST. During the night the surrounding catchment is mostly dry. Conversely, little to no rain falls over the lake during the afternoon and early evening. In most cases the maximum over the lake occurs at either 0600 or 0900 LST and the maximum over the catchment occurs around 1500 to 1800 LST. The diurnal cycle of Mesoscale Convective Systems (MCSs) parallels that of over-lake rainfall. MCS initiation generally begins over the catchment around 1500 LST and increases at 1800 LST. MCS initiation over the lake begins around 0300 LST and continues until 1200 LST. While some MCSs originate over the highlands to the east of the lake, most originate in situ over the lake. Maximum MCS activity over the lake occurs at 0600 LST and is associated with the systems that initiate in situ.

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