UP-TO-DATE RADAR-BASED PRODUCTS FOR POTENTIAL OPERATIONAL APPLICATION

Transcription

1 UP-TO-DATE RADAR-BASED PRODUCTS FOR POTENTIAL OPERATIONAL APPLICATION Heikki Pohjola and Uta Gjertsen OPERA work package 1.6 OPERA_2006_04 Final report, 31 st of October, 2006

2 Contents 1 Introduction 3 2 Summary 3 3 Radar products for international exchange 4 4, parameters and notes 6 5 Dual polarimetric products 14 6 Dictionary of products 18 7 Dictionary of Dual polarimetric products 19 8 References 19 2

3 1. Introduction In OPERA I, a list of radar products for international exchange was defined in document OPERA WD_21/99 (Galli et al 2001). This work is continued in work package 1.6 Product Definition in OPERA II. This report from WP 1.6 reviews the products defined in OPERA WD_21/99, and suggests new products for international exchange. In addition to documents from OPERA I, COST 717 and VOLTAIRE, this report is based on manuals of commercial software packages. Also the experiences from OPERA II work packages 1.2 Data Quality (Holleman et al 2006) and 1.3. User Requirements (Pohjola and Gjertsen 2006) are integrated. This report describes the properties of the products, while WP2.1 concentrates on data formats. OPERA WD_21/99 recommends six radar products for international exchange (Galli et al 2001). However, only a few of these products are exchanged operationally today. Vertical wind profiles are exchanged in the COST Wind Initiative for a Network Demonstration in Europe (CWINDE) project. PseudoCAPPI images or comparable data are exchanged for several international composites, for example within the NORDRAD network. One very promising improvement for the infrastructure of data exchange is pilot data hub built in WP5.1 (Harrison et al 2006). Radar products defined in OPERA WD_21/99: 1. Maximum vertical reflectivity 2. Constant altitude reflectivity (CAPPI) 3. Echo top altitude 4. Surface precipitation accumulation 5. Vertical reflectivity profile 6. Vertical wind profile 2. Summary To identify new products suitable for exchange, radar products provided by the most common radar processing systems used in Europe (Sigmet IRIS, Gematronik Rainbow, EEC EDGE, Gamic MURAN) were reviewed. The products and their availability in the systems are listed in detail in Section 6 and 7. Most conventional radar products are available in all commercial software packages. Exceptions are: VPR, Vertical wind profile, Height of maximum intensity, Layer mean reflectivity, Wind speed and direction, Multiple doppler wind barbs, Spectrum at Maximum Velocity, Storm Relative Velocity, Layer turbulence, Hail product. However, the VPR and Vertical wind profile are listed already in OPERA_WD_21/99 as suitable products for exchange. Wind profiles are exchanged in CWINDE. The products recommended for international exchange are listed in Sec. 3. In Sec. 4 all product descriptions and parameters are listed. Table 2 lists the dual polarimetric products available in commercial software packages. In Sigmet IRIS and Gematronik Rainbow, basic dual polarimetric parameters (φ DP, K DP, ρ hv, LRD, Z DR ) are available. Those can be exchanged in PPI format. Only the Gematronic Rainbow manual lists some dual polarimetric products for attenuation correction, hydrometeor classification and rainfall rate 3

4 estimation. However, radar companies are developing dual polarimetric products and in near future more products certainly will be available. At the moment documentation of the dual polarimetric products seems to be under construction in many companies and it is very difficult to know what products are really operationally available and what products are not. In the WP1.4 and WP1.5 (New technologies) investigate the state of the dual polarimetric technology. One important thing is quality information for the data which is studied and described in WP1.2. Quality descriptors were defined in WD_2005_19 (Holleman et al 2006). The proposed quality descriptors were divided in the following way:. Static descriptors. These indicators remain unchanged during most of the time. They are not influenced by changing external factors like environmental parameters, e.g., the weather Dynamic global descriptors. These indicators are time and situation dependent and thus they can change from one product to the following in time. They are, however, considered valid during a whole scan sequence and are associated to all data points contained in a given product Dynamic local descriptors. These indicators are also time and situation dependent. In addition, these indicators may change within a given product from one data point to the next one. For further information see WD_2005_ Radar products for international exchange This section lists the products recommended for international exchange. Of the products defined in (OPERA WD_21/99), the following products are kept in the list: Maximum vertical reflectivity, CAPPI (and PseudoCAPPI), surface precipitation accumulation, VPR, and vertical wind profile. The echo top altitude products is taken out. New products suggested are volume data and hydrometeor classification. The VPR product is becoming more and more important when the operational VPR-correction will be commonly used. VPR is also important for example to characterise the type of precipitation (convective, stratiform) and to give the height of the bright band (this was the idea in the OPERA 1). The exchange of VPRs for VPR-correction use is planned in the Nordic countries. However, the VPR is available only in the IRIS software. It is likely that a VPR product will be available also in Rainbow in the near future. The results from OPERA II WP1.3 Use of radar data by operational user communities, show that many user groups require a precipitation composite. The composite should be homogenously processed, i.e. all radar data processed with the same algorithms for error removal and quality control. Radar composites with ground precipitation are required for NWP verification, assimilation, road maintenance, and for hydrology. Some users require 3D radar data, for example aviation and NWP assimilation. The exchange of polar volumes of reflectivity and radial wind data should therefore have high priority in the future. The exchange of polar volumes makes the generation of homogeneous composites possible. At the same time, data will be available for the assimilation of radial winds and reflectivity into NWP models. Polar Volumes can be created from a series of PPIs taken at different elevation angles. The PPI is also ready to use in all software packages and it is possible to exchange many parameters, also dual polarimetric ones. 4

5 The most important outcome of this work is the suggestion of two new exchangeable products: hydrometeor classification and polar volumes. Exchanging of these products is the most important goal for the future. The exchange of polar volumes on an international level is complicated, and it will take some time. In the meantime, 2D products are still required. List of products recommended for exchange: 1. Maximum vertical reflectivity 2. Constant altitude reflectivity (CAPPI, PseudoCAPPI) 3. Surface precipitation accumulation 4. Vertical reflectivity profile 5. Vertical wind profile 6. Volume, cartesian or polar, both radial wind and reflectivity 7. Hydrometeor classification Other radar products: Reflectivity: Echo top altitude Echo base altitude Height of Maximum Intensity Layer mean reflectivity Wind: Wind speed and direction Multiple doppler wind barbs Doppler wind shear Spectrum at Maximum Velocity Storm Relative Velocity Layer turbulence Precipitation: Vertically Integrated Liquid Hail product Polarimetric Measurements: Hail signal product Rainfall rate estimation Differential phase shift Specific differential phase Polarimetric correlation coefficient Linear Depolarisation ratio Differential reflectivity 5

6 4. s, parameters, and notes 4.1. Maximum vertical reflectivity product 2D map containing the maximum reflectivity present in the vertical column over each surface point (ground view). In addition and optionally, the maximum reflectivity taken along a set of horizontal planes at different altitudes and along specified directions can be given (side-walls). Product data quantity: reflectivity Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Number of side-walls: (typically one from W to E and one from S to N) Orientation of side-walls: from W to E or E to W, from N to S or S to N Sequence of heights used for side-walls or vertical spacing: given in m a.s.l. or in m Level slicing method: list of values or formula parameters (see section 7 in WD21_99) Level slicing unit: dbz or mm/h (Z/R relationship required in the second case) : It is assumed that the level slicing used for the side-walls intensity is the same than for the ground map. For side-walls, if the height increment is constant then the vertical spacing is given instead of specifying the sequence of height values. If side-walls are present, then their number, orientation and height sequence are omitted Constant altitude reflectivity product (CAPPI): : 2D-map containing the representative reflectivity for the horizontal plane (layer) placed at a predefined altitude. A set of maps for various heights may be given inside of the same product. Product data quantity: reflectivity Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Layer thickness of the horizontal plane: in 0.1 km Layer centre altitude: in 0.1 km a.s.l. Layer associated value: average or maximum or nearest neighbour or interpolated Filling of (inner,outer) cones: (YES,YES) or (YES,NO) or(no,yes) or(no,no) Level slicing method: list of values or formula parameters (see section 7 in WD21_99) Level slicing unit: dbz or mm/h (Z/R relationship required in the second case) 6

7 : The parameter filling of cones can optionally be omitted Echo top altitude product : 2D-map containing the highest altitude reaching a predefined reflectivity threshold inside the vertical column over each surface point. Product data quantity: altitude Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Reflectivity threshold: value in 0.1 dbz Level slicing method: list of values in 0.1 km a.s.l. or formula parameters (see section 7 in WD21_99) : 4.4. Surface precipitation accumulation product: : 2D-map with the precipitation estimates at surface level accumulated during a predefined period of time. Product data quantity: precipitation amount Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Level slicing method: list of values in 0.1 mm or formula parameters (see section 7 in WD21_99) Adjustment method: None, Radar-to-gage factors (RT or CL), Gage-tuned Z-R relationship (RT or CL), Radar-to-gage regression (LL or NL or RT or CL), Vertical profile (SY or RE) Accumulation period: in minutes Accumulation method: Sampling-and-hold or Interpolation : RT: real-time, CL: climatological, LL: linear, NL: non-linear, SY: synthetic, 7

8 RE: real. The adjustment and accumulation methods can optionally be omitted Vertical reflectivity profile product: : Radar product giving the vertical profile of the reflectivity taken over a specified surface area. For each height level this product delivers a set of parameters that describes the reflectivity field inside the considered volume. Vertical spacing: height difference between successive samples in m Vertical range: range of considered altitudes (lower,upper) in 0.1 km a.s.l. Base area: location (lat, lon) and extension (equivalent radius) in km Data quantification method within the sliced volume: Averaging, Maximum Product data quantity for each height level: reflectivity in 0.1 dbz : The profile is taken in a vertical cylinder based above a ground area of specified form and position. Typically it is taken within a circular area centred around the radar station. If this is not the case (e.g. for an arbitrary form) the surface is described by its gravity centre and equivalent radius. The data quantification method describes the algorithm used to associate a reflectivity value to an height level. "When the vertical stratification is not regular the sequence of the used heights is to be specified. The base area and the quantification method can optionally be omitted Vertical wind profile product: : Radar product with the vertical profile of the wind estimated from Doppler measurements above the weather radar station. For each height level this product gives a set of parameters describing the wind field. Vertical spacing: height difference between successive samples in m Vertical range: range of considered altitudes (lowest, upper) in 0.1 km a.s.l. Volume shape: Cylindrical, Conical,... Quality information: (OK or suspect or not-applicable or missing) Product data quantity for each height level: horizontal and vertical velocity in 0.1 m/s and direction in degrees : 8

9 Detailed information is present in documents OPERA 22-1/99 and 22-2/99. " When the vertical stratification is not regular the sequence of the used heights is to be specified. " The volume shape can optionally be omitted Plan position indicator PPI (Polar volume) : The PPI is a 2D-map projection of a conical surface at predefined elevation containing either reflectivity, precipitation intensity, the radial component of wind velocity or one of the dual polarization parameters. A Polar volume consists of many PPIs. A set of PPIs for various elevations may be given inside of the same product, but they all must contain the same product data quantity. Product data quantity: reflectivity, velocity or one of the dual polarization parameters. Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Elevation: in decimals of degrees. Level slicing method: list of values or formula parameters (see section 7 in WD21_99) Level slicing unit: dbz, mm/h For velocity: unambiguous velocity, unfolding method used if any (typically dual PRF) PPI of velocity can be used as input for dual Doppler products For dual pol parameters other optional parameters Echo base altitude : The echo base product provides for each point on the surface, an estimate of the height of the lowest elevation of the first echo return that is above a reflectivity threshold. Product data quantity: altitude Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Reflectivity threshold: value in 0.1 dbz Level slicing method: list of values in 0.1 km a.s.l. or formula parameters (see section 7 in WD21_99) : 9

10 In areas where precipitation reaches ground or lowest measurement bin, this product shows undefined values. The quality of this product depends crucially on number of elevations in the polar volume Height of Maximum Intensity 2D-map containing the altitude of highest reflectivity value inside the vertical column over each surface point. Parameters Product data quantity: altitude Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Level slicing method: list of values in 0.1 km a.s.l. or formula parameters (see section 7 in WD21_99) (Optional: Reflectivity threshold: value in 0.1 dbz ) In stratiform rain, the product can be used to determine the height of bright band (melting layer). However, if there is no melting layer, it will show a value inside of an ice cloud. To avoid such problems, an optional threshold could be used (show only product for pixels where maximum intensity is over a dbz threshold.) Rapidly decreasing heights in convective storms may indicate the presence of a microburst. The quality of this product depends crucially on number of elevations in the polar volume, even more than in other products, as it is not possible to interpolate the maximum Layer Mean Reflectivity The layer mean reflectivity is a 2D-map showing the mean reflectivity in a user-defined layer between two CAPPI surfaces. Product data quantity: dbz Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Level slicing unit: dbz Height (top and bottom): km 10

11 4.11. Wind speed and direction 2D-array of horizontal wind vectors, based on single Doppler radar measurements and eg. the uniform wind algorithm. Parameters Product data quantity: array of speed (tenths of m/s and direction (degrees) of wind Image size: number of arrays per row (# of columns) and per column (# of rows) Array spacing: km Upper limit altitude: m a.s.l. Lower limit altitude: m a.s.l. Range and Azimuth Spacing: These fields define the resolution of computing the wind vectors in polar coordinates. Quality indicator: Ref. WP 1.2 : Because vertical shear can be substantial, it is recommended that the layer between upper and lower limit should be around 1 km A quality indicator should be defined for this! Multiple Doppler wind barbs 2D-array of horizontal wind vectors, based on measurements of two doppler radars located typically less than 100 km from each other.. Parameters Product data quantity: array of speed (tenths of m/s and direction (degrees) of wind Image size: number of arrays per row (# of columns) and per column (# of rows) Coordinates of central point of the image Array spacing: km Upper limit altitude: m a.s.l. Lower limit altitude: m a.s.l. Maximum unambigious speed Unfolding method used Fallspeed correction method used if any. The barbs cannot be used at area where the beams of the two radars are almost parallel. From this and other reasons, a quality indicator is essential. 11

12 4.13. Wind shear 2D-map projection of a conical surface at predefined elevation containing change of the radial component of wind in Radial, Azimuthal or elevational direction or combined. Parameters Product data quantity: wind shear in tenths of m/s/km Radial, Azimuthal or elevation shear, or combined R+A, R+A+E, etc. The radial velocity data should be of high quality because of danger of false alarms Spectrum at Maxiumum Velocity Visualisation of areas with high velocity and high spectrum width (potential risk For air traffic). No height information given. V and W must be scanned together to make this product. Range Image size Height (top and bottom) Storm Relative Velocity Shows local radial velocity values relative to a moving storm. Can be aplied on polar volume data of radial velocity. Parameters Range Image size Center point (unit and coordinates) Base wind (Keep base wind, remove automatic profile, remove constant profile) 12

13 4.16. Layer turbulence 2D map containing the mean spectral width between set upper and lower limits in altitude in the vertical column over each surface point (ground view). LTB is calculated using a polar volume data set with spectral width as input. Range: diplayed range Image size Pixel resolution Top: Height above MSL of upper data layer Bottom: Height above MSL of lower data layer : LTB can be used to observe turbulence on flight levels. The radar scan should be optimized for this purpose, low antenna rotation speed to get a good enough data set of W Vertically Integrated Liquid VIL : 2D map containing the integrated liquid water content between set upper and lower limits in altitude in the vertical column over each surface point. Parameters Product data quantity: W (intergrated liquid water content) Unit: mm Upper limit altitude: km Lower limit altitude: km Z/W relationship used Optional: height of melting layer Image size: number of pixels per row (# of columns) and per column (# of rows) Pixel size: horizontal and vertical extension of the pixel in km Level slicing method: list of values or formula parameters (see section 7) Level slicing unit: mm. Z/W relationships are different for snow and water The bright band biases VIL results, so the top and bottom should be either above or below 13

14 melting layer altitude Hail product Uses volumetric data to determine the probability of hail. These data consists of Vertically Integrated Liquid (VIL), the Melting Level, Zonal (East-West component) wind Velocity and average Relative Humidity (0 to 500 mb). The probability is determined for each column of bins within VIL in the area of surveillance and mapped in the Hail Probability Product. Upper limit: km Lower limit: km Humidity: % Melting level: km Zonal wind at 500 mb: m/s Range: km. Z/W relationships is used for VIL The upper and lower limits are the heights above and below which data in the data volume are not considered for the VIL calculation 5. Dual polarimetric products 5.1. Hail Signal The Hail Signal product exploits the inherent differences in the radar signatures of rain and hail. Raindrops maintain predominately regular, oblate spheroid shapes as the fall to the earth. Hail stones, however, are irregular in shape and tumble as they fall to the earth. The Z dr for rain is generally positive but may range from 0 to 4 db whereas the Z dr for hail is generally 0 db. Upper limit: km Lower limit: km Range: km 14

15 The upper and lower limits are the heights above and below which data in the data volume are not considered for the for the hail signal product 5.2. Hydrometeor classification Hydrometeor classification products are based on reflectivity and on the dual polarization variables differential reflectivity, specific differential phase, correlation coefficient and the linear depolarization ratio. Dual-channel measurements are used to deduce the types of scatterers present in the atmosphere, such as rain, hail, snow, graupel and even non-meteorological targets such as insects, chaff and clutter. dbz h, dbz v, ρ hv, φ DP, Z DR, LDR 5.3. Rainfall rate estimation An improved rainfall rate estimate can be obtained from Z and Z DR. The value of the median volume drop diameter can be estimated from Z DR. This makes it possible to adopt the Z-R relationship and should result in more accurate rainfall estimates Differential Phase shift φ DP : Differential phase shift φ DP is the phase shift between the horizontally polarized wave and the vertically polarized wave. See

16 Since φ DP is not affected by attenuation, it can be used to develop and check attenuation correction schemes. Attenuation correction based on using the total Differential Phase Shift as a constraint is selectable for reflectivity products. Reflectivity products can be viewed with or without attenuation correction. Correction of Differential Reflectivity due to differential attenuation is also available 5.5. Specific differential phase shift K DP The Specific Differential Phase K DP denotes the difference between the propagation constant for the horizontally and vertically polarized wave. In a homogeneous medium K DP can be directly obtained from the differential phase shift φ DP at two different locations. See 4.7 K DP is only affected by anisotropic hydrometeors (rain) and therefore K DP allows to discriminate between rain and frozen precipitation Polarimetric correlation coefficient ρ hv The Polarimetric Correlation Coefficient ρ hv provides the complex correlation between the horizontally and the vertically polarized signals. See 4.7 The ρ hv data is a useful indicator describing the regularity or irregularity, shape and canting angles of hydrometeors Linear depolarisation ratio LRD 16

17 The linear depolarization ratio LDR is the ratio of the vertically polarized reflectivity to the horizontally polarized reflectivity for a horizontally polarized transmitter pulse, in other words: the ratio of the cross-polarized reflectivity to the co-polarized reflectivity.. See 4.7 Measurement needs usually different radar measurement mode Differential reflectivity Z DR Since Z DR is the ratio of power returned at the horizontal and vertical polarization, the quantity will be positive (in db scale) if more power is returned in the horizontal polarization than in the vertical polarization. See 4.7 Z DR data are used to distinguish between liquid and ice phases of water, and to describe the shapes of raindrops. 17

18 6. Dictionary of products Table 1: List of products provided by the commercial systems Sigmet IRIS Gematronik Rainbow EEC Edge DWD Gamic Maximum vertical reflectivity MAX MAX CMAX MAXDISPLAY Constant altitude CAPPI CAPPI CAPPI CAPPI reflectivity Echo top altitude TOPS EHT (echo top ETOPS ECHO-TOP height) 4 Surface precipitation accumulation RAINN PAC IPCP PPI-ACCU (for PPI) 5 Vertical reflectivity profile VVP 6 Vertical wind profile VVP VVP PROFILE 7 Plan position indicator PPI PPI PPI PPI 8 Echo base altitude BASE EHT EBASE ECHO-BASE 9 Height of Maximum Intensity HMAX EHT HMAX 10 Layer mean reflectivity LMR LRA 11 Wind speed and direction WIND UWT, HWIND UWT 12 Multiple Doppler wind barbs NDOP 13 Doppler wind shear SHEAR SHEAR SHEAR SHEAR 14 Spectrum at Maximum SMV Velocity Storm Relative Velocity SRV VECTOR STP (storm 15 tracking product) 16 Layer turbulence LTB LTB 17 Vertically Integrated Liquid VIL VIL VIL VIL 18 Hail product Planned (HAIL) HAIL PROB WARNINGS (hail, rain, shear) 18

19 7. Dual polarimetric products Table 2: List of polarimetric products provided by the commercial systems Sigmet IRIS Gematron ik Rainbow EEC Edge DWD Gamic 1 Hail signal product HAIL SIGNAL 2 3 Hydrometeor classification HydroClass HMC Rainfall rate estimation RRE SRI 4 Differential phase shift φ DP x x x? x? Specific differential phase x x x? x? 5 K DP Polarimetric correlation x x x? x? 6 coefficient ρ hv Linear depolarisation ratio x x x? x? 7 LRD 8 Differential reflectivity Z DR x x x x? 8. References DVD Gamic 2006: Deutscher Wetterdienst MURAN manual,. Enterprise Elctronic Corporation, 2003: Edge operation manual ver Selex Gematronik Gmbh 1999: Rainbow Operator s manual, ver 3.3. Sigmet, 2006: IRIS Product and Display Manual ver Galli, G., Ciotti, C., Divjak, M., Kracmar, J., Svensson, J. 2001: Definition of radar products to be exchanged internationally. OPERA I WD-21/99 Golz, C., Einfalt, T., Gabella, M., and Galli, G. 2005: VOLTAIRE Work Package 1 & 2 Metadata definition, version 1.2. Harrison, D., Scovell R., Lewis H. and S. Matthews, 2006: The development of the EUMETNET OPERA radar data hub. Proceedings of ERAD 2006, pp

20 Holleman I., Michelson, D., Galli, G., Germann, U.., and Peura M., 2006: Quality information for radars and radar data, OPERA working document WD_2005_19 Michelson, D., I. Holleman, H. Hohti, and M. Salomonsen, 2003: HDF5 information model and implementation specification for weather radar data. COST717 Working Document WDF_02_200204_1, 24 pp Pohjola, H. and U. Gjertsen, 2006: Use of radar data by operational user communities. OPERA II Working Document WD_2005_17 20