Contrasting the Effects of X-Band Phased Array Radar and S-Band Doppler Radar Data Assimilation on Rainstorm Forecasting in the Pearl River Delta
<p>(<b>a</b>) Location of Guangzhou SMSR (red pentagram) and nine XPARs in Guangdong Province (blue triangles), with the radar-coverage circles in 230 (solid red circle) and 60/40 (blue dashed circles) km ranges for SMSR and XPAR, respectively. The black dashed frame delineates the D03. (<b>b</b>) The position of automatic weather stations across Guangdong Province (green scatters).</p> "> Figure 2
<p>The potential geopotential height field (black contours, units: dagpm), temperature field (red contours, units: °C), wind field (wind barbs, units: m/s), and relative humidity field (shaded areas) from the ERA5 reanalysis data at 18:00 UTC on 6 June 2022 are depicted at different pressure levels: (<b>a</b>) 500 hPa; (<b>b</b>) 700 hPa; (<b>c</b>) 850 hPa; (<b>d</b>) 925 hPa. “D” in red represents the center of the cyclone. The brown line represents the wind shear line.</p> "> Figure 3
<p>Model grid configuration and topography (shaded). (<b>a</b>) Domain configuration; (<b>b</b>) D03 configuration.</p> "> Figure 4
<p>The flow chart for the DA experiments.</p> "> Figure 5
<p>Velocity spectrum width (SW) at 1.5° elevation angle for (<b>a</b>) SMSR and (<b>b</b>) XPARs. And (<b>c</b>) the spatial average velocity SW from the lowest to the highest of the first 9 elevation angles for both at 18:00 UTC on 6 June 2022. Unit: m/s.</p> "> Figure 6
<p>The average analysis increment in each model layer for the first assimilation cycle in the D03 region: (<b>a</b>) u (units: m/s), (<b>b</b>) v (units: m/s), (<b>c</b>) T (units: 10<sup>−3</sup> K), (<b>d</b>) q (units: g/kg).</p> "> Figure 7
<p>The first row shows the 850hPa horizontal wind field (vector) and wind speed (shaded, units: m/s) at 18:00 UTC on 6 June 2022, for (<b>a</b>) CTRL, (<b>b</b>) DA_S, (<b>c</b>) DA_X, and (<b>d</b>) DA_S_X. The second row depicts the incremental field of the horizontal wind field relative to CTRL, with wind speed greater than 5 m/s indicated by a red vector, for (<b>e</b>) DA_S, (<b>f</b>) DA_X, and (<b>g</b>) DA_S_X.</p> "> Figure 8
<p>Radar composite reflectivity-analysis field at 18:00 UTC in D03 on 6 June 2022, for (<b>a</b>) OBS-SMSR, (<b>b</b>) CTRL, (<b>c</b>) DA_S, (<b>d</b>) DA_X, and (<b>e</b>) DA_S_X; line AB is the profile in <a href="#remotesensing-16-02655-f009" class="html-fig">Figure 9</a> and <a href="#remotesensing-16-02655-f010" class="html-fig">Figure 10</a>.</p> "> Figure 9
<p>Vertical cross-sections of RF (shaded, units: dBZ) along the black solid line A (112.7°E, 21.6°N) and B (114.6°E, 23.2°N) in <a href="#remotesensing-16-02655-f008" class="html-fig">Figure 8</a> at 18:00 UTC on 6 June 2022. (<b>a</b>) OBS-SMSR, (<b>b</b>) CTRL, (<b>c</b>) DA_S, (<b>d</b>) DA_X, (<b>e</b>) DA_S_X. The height is from sea level.</p> "> Figure 10
<p>Vertical cross-sections of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>q</mi> </mrow> <mrow> <mi>r</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math>(first row), <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>q</mi> </mrow> <mrow> <mi>g</mi> </mrow> </msub> </mrow> </semantics></math> (second row), and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>q</mi> </mrow> <mrow> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math> (third row) along line AB for each experiment at 18:00 UTC on 6 June 2022. (<b>a</b>,<b>e</b>,<b>i</b>) CTRL, (<b>b</b>,<b>f</b>,<b>j</b>) DA_S, (<b>c</b>,<b>g</b>,<b>k</b>) DA_X, (<b>d</b>,<b>h</b>,<b>l</b>) DA_S_X. The black contours represent the distribution of hydrometeors in CTRL. The height is from sea level.</p> "> Figure 11
<p>Composite reflectivity at 19:00 UTC (first row), 20:00 UTC (second row), and 21:00 UTC (third row) on 6 June 2022 (units: dBZ). (<b>a</b>,<b>f</b>,<b>k</b>) OBS-SMSR, (<b>b</b>,<b>g</b>,<b>l</b>) CTRL, (<b>c</b>,<b>h</b>,<b>m</b>) DA_S, (<b>d</b>,<b>i</b>,<b>n</b>) DA_X, (<b>e</b>,<b>j</b>,<b>o</b>) DA_S_X.</p> "> Figure 12
<p>Vertical cross-sections of RF (shaded, units: dBZ) and wind (vector) along the black solid line A (113.0°E, 21.6°N) and B (114.5°E, 23.2°N) in <a href="#remotesensing-16-02655-f011" class="html-fig">Figure 11</a> at 19:00 UTC on 6 June 2022. (<b>a</b>) OBS-SMSR, (<b>b</b>) CTRL, (<b>c</b>) DA_S, (<b>d</b>) DA_X, (<b>e</b>) DA_S_X. The height is from sea level.</p> "> Figure 13
<p>Hourly precipitation from 18:00 UTC (first column) to 22:00 (last column) on 6 June 2022 (units: mm). (<b>a</b>–<b>d</b>) OBS, (<b>e</b>–<b>h</b>) CTRL, (<b>i</b>–<b>l</b>) DA_S, (<b>m</b>–<b>p</b>) DA_X, (<b>q</b>–<b>t</b>) DA_S_X.</p> "> Figure 14
<p>Threat Score (TS) (first row), False Alarm Rate (FAR) (second row) and Equitable Threat Score (ETS) (third row) for hourly precipitation from 18:00 to 22:00 on 6 June 2022 (<b>a</b>,<b>d,g</b>) for >1 mm, (<b>b</b>,<b>e,h</b>) for >5 mm, (<b>c</b>,<b>f,i</b>) for >10 mm.</p> ">
Abstract
:1. Introduction
2. Data and Methods
2.1. Observation Data
2.2. DA Method
2.2.1. 3Dvar
2.2.2. Radar Observation Operator
3. Case Introduction and Experimental Design
3.1. Overview of the Case
3.2. Model and Experimental Design
4. Data Analysis and Experimental Results
4.1. Radar Data Comparison Analysis
4.2. The Analysis Increment in the First Assimilation Cycle
4.3. Analysis Results
4.3.1. Wind Analysis
4.3.2. Radar Echo Analysis
4.3.3. Hydrometeor Analysis
4.4. Forecasting Results
4.4.1. Composite Reflectivity Forecast
4.4.2. Vertical Structure Analysis
4.4.3. Precipitation Forecast
5. Summary
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Name | Scheme |
---|---|
CTRL | No DA |
DA_S | Assimilating RV and RF of Guangzhou SMSR |
DA_X | Assimilating RV and RF of nine XPARs |
DA_S_X | Assimilating SMSR and XPARs data sequentially |
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He, L.; Min, J.; Yang, G.; Cao, Y. Contrasting the Effects of X-Band Phased Array Radar and S-Band Doppler Radar Data Assimilation on Rainstorm Forecasting in the Pearl River Delta. Remote Sens. 2024, 16, 2655. https://doi.org/10.3390/rs16142655
He L, Min J, Yang G, Cao Y. Contrasting the Effects of X-Band Phased Array Radar and S-Band Doppler Radar Data Assimilation on Rainstorm Forecasting in the Pearl River Delta. Remote Sensing. 2024; 16(14):2655. https://doi.org/10.3390/rs16142655
Chicago/Turabian StyleHe, Liangtao, Jinzhong Min, Gangjie Yang, and Yujie Cao. 2024. "Contrasting the Effects of X-Band Phased Array Radar and S-Band Doppler Radar Data Assimilation on Rainstorm Forecasting in the Pearl River Delta" Remote Sensing 16, no. 14: 2655. https://doi.org/10.3390/rs16142655