1. Estimation of precipitation over the OLYMPEX domain during winter 2015-2016
Dennis P. Lettenmaier a, Qian Cao a, Tom Painter b, Jessica Lundquist c, Walter Petersen d
a Department of Geography, University of California, Los Angeles, Los Angeles, CA
b NASA Jet Propulsion Laboratory, Pasadena, CA
c University of Washington, Seattle, WA
d NASA Marshall Space Flight Center, Huntsville, AL
OLYMPEX workshop
March 22, 2017

2. Background and Objective
A primary goal of Global Precipitation Mission (GPM) is to measure precipitation globally especially in areas lacking ground observations.
One goal of the OLYMPEX campaign is to better assess precipitation products based on GPM and other satellites
Especially in cold seasons and where orographic factors exert strong controls on precipitation
Our objective
To develop the best product we can for the evaluation of GPM-based precipitation products such as NASA’s IMERG over the OLYMPEX domain, which for our purposes was defined as the Olympic Peninsula plus the Chehalis River basin. Our period of analysis is winter , which we define as Oct 2015 – Apr 2016.

3. Resources of data Precipitation data
NOAA WSR-88D (primarily the site at Langley Hill, on the Washington Coast)
NOAA’s National Severe Storms Laboratory (NSSL) Mountain Mapper product
Precipitation gauges
COOP (Cooperative Observer Network)
CoCoRaHS (Community Collaborative Rain, Hail and Snow Network)
SNOTEL
RAWS (Remote Automatic Weather Stations)
HADS (Hydrometeorological Automated Data System)
ASOS (Automated Surface Observing System)
OLYMPEX
Snow data
Snow depth maps for the interior of the Olympic Peninsula from two flights of NASA/JPL’s Airborne Snow Observatory (ASO) on Feb 8-9 and Mar
In situ observations
4 SNOTEL sites

4. Langley Hill Radar Terrain blockage of the Langley Hill Radar coverage
Due to terrain blockage, the radar captures precipitation on the west side of the mountain areas, but basically nothing on the east side

5. Precipitation gauges Map of precipitation gauges
There are 120 rain gauges that were operational during at least 50% of the period Oct Apr :
COOP
CoCoRaHS
SNOTEL
RAWS
ASOS
OLYMPEX
(in Quinault and Chehalis Basins)
Very few stations are located at elevations higher than about 500m
The distribution of gauges is nonuniform. Most gauges are on the east side while the coverage on the west is sparse

6. Sites at higher elevations
Few stations are located at elevations higher than about 500m
Much of the interior Olympic Mountain is above 500 m elevation with substantial winter snow cover, but few measurements
Precipitation in this area is winter dominant
a) yes there are 135 stations, but many big gaps
b) much of the interior above ~500m elevation has substantial winter snow cover, but few measurements
precipitation is winter dominate

7. ASO snow depth maps
Feb snow depth map in 3 m resolution overlaid with 1/32 degree mesh
Mar snow depth map
in 3 m resolution
1/32 degree mesh for our product
the February data extent is smaller because it was a partial collection due to weather etc

8. Methodology Estimation of precipitation at lower elevations
Merge NOAA National Severe Storms Laboratory (NSSL) Radar product with Mountain Mapper
Augment the merged product with 120 additional gauges
Estimation of precipitation at higher elevations: We use VIC model driven by observed forcings and adjusted by ASO SWE ahead of two flight dates
Temperature from SNOTEL and HOBO sites gridded by daily residuals subtracted from elevation-based seasonal mean
Create SWE using ASO snow depth and density field generated by VIC and modified by site observations
Adjust precipitation factor to force the simulated SWE to match the ASO SWE
overall strategy for developing a precip product for the olympex winter
gridded precipitation, temperature, and other surface variables available

9. Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model

10. Estimation of precipitation at lower elevations
Merging NSSL MRMS radar and Mountain Mapper
Radar
Mountain Mapper
Radar quality index mm mm

11. Estimation of precipitation at lower elevations
Integration of MRMS radar precipitation with gauge observations
Mean daily precipitation (Nov ~Mar )
MRMS merged
Integrated with additional stations

12. Estimation of precipitation at lower elevations
Evaluate merging method by systematically removing individual stations one at a time

13. Estimation of precipitation at higher elevations
ASO snow depth aggregated to 1/32 degree

14. Estimation of precipitation at higher elevations
ASO SWE Maps

15. Estimation of precipitation at higher elevations
Mean daily precipitation (Nov – Feb )
Before Adjustment
After Adjustment

16. Estimation of precipitation at higher elevations
Mean daily precipitation (Feb – Mar )
Before Adjustment
After Adjustment

17. Evaluation of IMERG
IMERG (satellite only product) grids within the OLYMPEX domain
Integrated Multi-satellitE Retrievals
This algorithm is intended to intercalibrate, merge, and interpolate “all” satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators at fine time and space scales for the TRMM and GPM eras over the entire globe.
precpitationUncal: Multi-satellite precipitation estimate
PrecipitationCal: precipitation estimates using gauge calibration over land
randomError: random error estimate of precipitation
Hqprecipitation: Instantaneous microwave-only precipitation estimate

18. Spatial comparison by month
Integrated Multi-satellitE Retrievals
This algorithm is intended to intercalibrate, merge, and interpolate “all” satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators at fine time and space scales for the TRMM and GPM eras over the entire globe.
precpitationUncal: Multi-satellite precipitation estimate
PrecipitationCal: precipitation estimates using gauge calibration over land
randomError: random error estimate of precipitation
Hqprecipitation: Instantaneous microwave-only precipitation estimate

19. Storm interarrival time
Comparison of exceedance probability of storm interarrival time (in hours)
from October to April
Ground obs includes hourly data from both radar and gauges

20. Daily comparison
CDF of daily precipitation from October to April

21. Seasonal comparison

22. Conclusions
IMERG hourly data captures the temporal frequency of storms well except for Region II and IV(b) where radar and mountain mapper products show relatively low temporal correlation
IMERG tends to underestimate precipitation for all winter months and over all sub-regions
The underestimation is higher in mountainous region IV and is obvious especially for orographic enhancement in the mountainous interior of the OLYMPEX domain, up to 87% in region IV(a) on a seasonal basis
IMERG shows a better match for the domain average in relatively inland Region II and III where there is less winter precipitation than coastal Region I with more precipitation
On a monthly basis, IMERG shows smaller underestimation in October and April when temperature is higher and precipitation is less