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Surface Precipitation Rate (SPR) - Version 12

Surface Precipitation Rate (SPR) - Version 12

Short Description

Uses RAP model sounding data, the Seamless Hybrid Scan Reflectivity (SHSR) mosaic and Surface Precipitation Type (SPT) field to compute instantaneous rain rates in mm/hr. Different rainfall rate relationships are assigned to provide the most accurate SPR field. Additionally, an evaporation correction has been added to reduce wet biases in this product.

Subproducts

None.

Primary Users

NWS: WFO, RFC

Input Sources

Seamless Hybrid Scan Reflectivity (SHSR), Surface Precipitation Type (SPT), RAP model sounding data

Resolution

Spatial resolution: 1 km x 1 km

Temporal resolution: 2 minutes

Product Creation

NOTE: As of Spring 2020, the MRMS Version 11.5 data is still what is operationally-supported. Version 12 data is available via LDM, set up manually at each site. Be aware that this page describes the experimental Version 12 Surface Precip Rate product. Please visit the Version 11.5 page for its information.

 

As of MRMS Version 12, the Surface Precip Rate (SPR) product uses a combination of Dual-Pol and non-Dual-Pol rainfall rate relationships based on location with respect to the Melting Layer. The Melting Layer is defined by RAP model sounding data. Below the Melting Layer, generally Dual-Pol relationships are used. Within or above the Melting Layer, non-Dual-Pol relationships are used with the same logic applied in the Version 11.5 product.

The reflectivity data used in these rainfall rate relationships is from the Seamless Hybrid Scan Reflectivity (SHSR) mosaic product. Additionally, an evaporation correction has been applied to the rain rates to reduce wet biases and "false precip" classifications that were negatively affecting the product.

Technical Details

Latest update: MRMS Version 12

Accessible on: operational AWIPS (via LDM, if set-up); MRMS Development site

 

The rainfall rate equations, along with their respective upper limits, are described in the table below:

where R(A) is based on specific attenuation and R(KDP) is based on specific differential phase.

Below the Melting Layer, R(A) is valid in areas of pure rain and works best in areas of light to moderate steady rainfall. The other two options are used when pure, steady rainfall does not exist. R(KDP) is more immune to hail, so it is preferred in areas of potential hail and in heavier rainfall returns where hail could be mixed in. In light or sporadic rain, the maximum between R(A) and the cool season stratiform Z-R relationship is used. (More details are provided below)

Within or above the Melting Layer, the algorithm defaults back to the Version 11.5 logic, where Z-R relationships are based on the Surface Precip Type (SPT) at each pixel. Please refer to that reference page for more information.

 

Detailed descriptions of the MRMS V12 R(A) technique can be found in Wang et al. 2019 with the following changes:

1. R(KDP) application in areas of potential hail:

  • Two R(KDP) relationships are applied based on rhoHV when Z >= 50 dBZ:

If ρHV <0.97, then R=29|KDP|0.770  

If ρHV>=0.97, then R=44|KDP|0.822

  • Both R(KDP) relationships are capped at 150mm/hr while R(A) is capped at 200 mm/hr. To assure a smooth transition of the rate value from R(A) to R(KDP), two transition zones are created:

If ρHV <0.97, the rate R would change linearly from 100% of R(A) at Z < 45dBZ to 100% of R=29|KDP|0.770 at Z >= 50dBZ; At Z = 47.5dBZ, R = 50% of R(A) + 50% of R(KDP).

If ρHV>=0.97, R changes from 100% of R(A) at Z < 48dBZ to 100% of R=44|KDP|0.822 at Z >= 50dBZ; At Z = 49dBZ, R = 50% of R(A) + 50% of R(KDP).


2. R(Z) application in areas of very light rain:

It was found that R(A) tends to underestimate in areas of very light and sporadic rain where the attenuation signal is too weak. Therefore, when the path integrated differential phase (ΔφDP) in a radial is too small (<3°), the precipitation rates in the radial is calculated as R = max {R(Z), R(A)} where the default Z(R) relationship is Z = 75R2.

 

Evaporation Correction

As of Version 12, an evaporation correction has been added. It is assumed that the radar-derived QPE estimated at beam level is equivalent to what reaches the surface; however, this is not the case since multiple environmental factors can influence precipitation rates between the beam level and the surface. One of these impacts is from evaporation. A scheme has been developed within MRMS to account for the evaporation of precipitation using three-dimensional model data and equations designed to be computationally efficient.

The scheme will only be applied to rain rates less than 1.00 inch per hour (assuming greater rates would saturated the vertical column) and utilizes RAP model data on an hourly scale to correct the rates. The RAP model data is translated onto a 10 km grid (for computational efficiency) and uses the vertical resolution of the MRMS 3D grid. 

Figure 1. Hourly MRMS radar-only QPE accumulations (left) before and (right) after evaporation correction during event 1 for the following times: (a),(b) 0800; (c),(d) 1300; (e),(f) 1800; and (g),(h) 2300 UTC 20 September 2016.

References

Cocks, S, L. Tang, et al., 2019: A one-year assessment of four radar-based QPEs across the continental US. 33rd Conference on Hydrology. Amer. Meteor. Soc., 6-10 Jan. 2019, Phoenix, AZ. Paper 886. https://ams.confex.com/ams/2019Annual/meetingapp.cgi/Paper/352864

Martinaitis, S. M., H. M. Grams, C. Langston, J. Zhang, and K. Howard, 2018: A real-time evaporation correction scheme for radar-derived mosaicked precipitation estimations. J. Hydrometeor., 19, 87–111. doi:10.1175/JHM-D-17-0093.1.

Ryzhkov, A. V., M. Diederich, P. Zhang, and C. Simmer, 2014: Potential utilization of specific attenuation for rainfall estimation, mitigation of partial beam blockage, and radar networking.  J. Atmos. Oceanic Technol., 31, 599–619.

Wang, Y., S. Cocks, et al., 2019: A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimteric Radar Utilizing Specific Attenuation and Specific Differential Phase: Part I – Algorithm Description and Initial Results.  J. Hydrometeor., [https://journals.ametsoc.org/doi/10.1175/JHM-D-18-0071.1]

Zhang, J., K Howard, C. Langston, et al., 2016: Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation: Initial Operating Capabilities. Bull. Amer. Met. Soc., 97, 621-638. 

 

Other MRMS product documentation: Seamless Hybrid Scan Reflectivity, Surface Precipitation Type, QPE - Radar Only