Use of Surface-Based GNSS Total Column Water Vapor Data for Operational Weather Forecasting and Climate Research John Forsythe Cooperative Institute for Research in the Atmosphere AT786 March 7,

2 1. Background *Note: In the literature, the terms TCWV, TPW, IWV, IPW, PWAT etc. are unfortunately used interchangeably to represent the vertical depth of water vapor in a column if it were all condensed. TCWV is the most widely used international term. Outline: 1.Background 2.Climate applications 3.Weather appplications 4.Topographic effects

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4 Total delay = dry + wet delay Dry delay is function of surface pressure Π is an empirical function relating wet delay to TPW Only a function of mean water vapor weighted temperature of the atmosphere Empirical estimated based on surface temperature Solving for Total Column Water Vapor Good error analysis in Means and Cayan, JTECH (2013)

5 Q: What is the error of surface-based GPS TCWV? A: < 5% or < 2mm Sources of error: Station pressure (perhaps 0.7 mm at most) T m estimation from Tsfc (regional differences) Spatial representativeness (topography, fronts) This error is equal or less than other techniques used to measure TCWV from the surface (radiosondes, upward looking radiometers). GPS TCWV commonly used as a validation source. Q: Estimate of highest observed TCWV?

6 All signals arriving at a GPS antenna with elevation angle greater than 7 degrees, within an inverted cone centered on the receiving antenna, are considered in determining the zenith tropospheric delay. Typical receivers track 12 or more satellites. At midlatitudes, the average elevation of the GPS satellites is about 25° above the horizon. Assuming a 5-km depth for the moist layer, the region observed by the GPS antenna is equivalent to an inverted cone with a radius of about 11 km. Viewed from space, this is roughly equivalent to an FOV of about 22 km. Rama Varja Raja et al. (2008) Q: What is the spatial resolution of surface-based GPS? A: It depends on the satellite viewing geometry, but ~ 20 km.

7 The Validation of AIRS Retrievals of Integrated Precipitable Water Vapor Using Measurements from a Network of Ground-Based GPS Receivers over the Contiguous United States M. K. RAMA VARMA RAJA et al.

NOAA GPS Met Sites in Gulf of Mexico DEV2 DEV1 Courtesy Seth Gutman, NOAA ESRL

MIRS/GPS Matchups: November 18, 2010 – Jan 6, < 1 hour time difference N = RMS: 5.3 mm Bias: 0.91 mm (MIRS minus GPS)

Histograms of GOES SNDR-East minus GPS TPW for matchups within 1 hour from May 24, 2011 to June 29, Results shown for 5° x 5° boxes having > 100 matchups. Green line is 0 difference. -10mm +10mm 0% 30% Frequency (%) SNDR-East minus GPS (mm)

Histograms of MIRS minus GPS TPW for matchups within 1 hour from Nov. 18, 2010 to Jan. 6, total matchups. Results shown for 5° x 5° boxes having > 100 matchups. Green line is 0 difference. -10 mm +10mm0% 30% (+)MIRS tendency often seen in imagery in this region

12 Strengths of surface-based TCWV from GPS: 1.Low-cost 2.All weather 3.High temporal resolution (~ 20 minute, 24 h / day) 4.Accuracy 5.Untapped networks for seismology/volcanology exist 6.A few very dense networks (Japanese GEONET ~ 800 stations) Limitations: 1.Sparse spatial coverage (centered on developed world, few ocean sites) 2.Climate record begins in 1995 at ~ 100 sites 3.No “one stop shopping”, networks are run by a wide variety of agencies. 4.While highly accurate, rare erroneous retrievals are possible (“orbit busts”).

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14 2. Climate Applications

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16 BAMS State of the Climate 2015, 2011

17 Normalized for topography

18 Surface-based GPS allows examination of the diurnal cycle in TCWV (also includes NARR data)

19 3. Weather Forecasting Applications

20 Dynamic Product Inputs InputSourceTemporalResolutionSpatial Resolution ResolutionLatency Global MIRS Merged TPW Retrieval Over Land/Ocean OSPO50 km1 – 6 hrs GPS Surface TPWNOAA GSD½ Hourly10-20 km½ hour GOES-11 Sounder TPWOSPOHourly10 km< 1 hour GOES-13 Sounder TPWOSPOHourly10 km< 1 hour Static Product Inputs InputComment GPS Station ListUpdate Quarterly MIRS static surface pressureRemapped to Grid Land MaskRemapped to Grid Grid Projection for RemappingUser specified Blended TPW Critical Design Review The Blended RR and High Res bTPW Products

21 GOES-East Sounder; 24 hour CONUS coverage Maximum GPS coverage Input TPW Datasets GOES-West Sounder; 24 hour CONUS coverage Local time of ascending node for spacecraft with microwave sensors Blue is MIRS over land

22 GPS Stations GOES E/W Sounder Blended MIRS TPW from N- 18,19, Metop-A Sample Blended TPW Product with MIRS added. July 15, 2011, 03 UTC See for near-realtime examples of the high resolution blended TPW and inputs. NOAA operational blended TPW, developed at CIRA, widely used by forecasters

polar inputs: Irregular diurnal sampling from polar orbiting satellites

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25 Means and Cayan, 2013 All sites with potential for TCWV retrieval

July 14, UTC One hour later GPS coverage varies hour to hour as well. July 27, Critical Design Review The Blended RR and High Res bTPW Products 26July 27, 2011

27 Example of anomalous GPS data in blended product

4. Accounting for Topography Effects in Ground-based GPS Measurements of Precipitable Water

NOAA Global Systems Division GPS station map as of February New stations continue to come online, for example the two new oil rig stations in the Gulf of Mexico (indicated by arrow). Typically ~250 – 300 stations are available half-hourly in near- realtime from gpsftp.fsl.noaa.gov.

800 hPa 850 hPa Polar Satellite Sounding (P sfc = 800 hPa) (like NOAA MIRS) Height GOES Sounding (P sfc = 780 hPa) 700 hPa Statement of the Problem: GPS sensors are at physically different altitudes, and satellite retrievals might use yet another value for surface pressure. How to combine them? Varies

Example of Hawaii GPS Station Elevations (Meters) Hilo, HI | Windward Lei, HI | Kokole Point, HI | Maui, HI | Mauna Kea, HI | Mauna Loa, HI | Pahoa, HI | U of HI Manoa, HI | Upolu Point, HI | Honolulu WAAS, HI |

Over ocean, Psfc ~ roughly constant at 1013 hPa, so effects of changing pressure are small. Over land, range might be 600 – 1050 hPa. A first order effect on TPW. Desire to show meteorological effects on TPW, not topographical effects. Similar to issues facing altimeter setting Challenge: Different TPW data sources (GPS, GOES Sounder, upcoming MIRS…) over land could each use a different surface pressure. AMSU and SSMIS TPW retrievals do not explicitly use P sfc. What is the correct Psfc in mountainous terrain at say a 16 km resolution to create a gridded product?

Effect of Varying Observation Heights on Layered Precipitable Water for a Saturated Layer (300 K; 1000 hPa)(300 K; 800 hPa)(275 K; 800 hPa)(275 K; 1000 hPa) (Mean Layer T; Mean Layer P) Provides upper bound on error from merging GPS at different station heights 0.05 mm / mb average error

1020 hPa MIRS static Psfc – based on topography GPS interpolated Psfc 700 hPa Blue implies estimated TPW too moist. Brown implies estimated TPW too dry hPa +200 hPa GPS Psfc lower GPS Psfc higher Sep. 24, UTC GPS interpolated minus MIRS static Psfc NOAA polar satellite retrieval – “Truth” Using GPS only

-200 hPa +200 hPa GPS Psfc lower GPS Psfc higher Psfc Mean TPW anomaly July 18, 2009 through November 13, 2009 (4x/day). 462 grids composited. Notice the similarity to the Psfc error map at extreme Psfc error. GPS interpolated minus MIRS static Psfc TPW anomaly climatology

wt = exp (- (ds**2.0 / a**2 + dp**2.0 / b**2 + sigma_max / sigma + dt/c**2)) Distance term, like in Barnes analysis a = 50 km Pressure term. MIRS Psfc used as truth. b = 20 mb Relative retrieval error GPS is 1 (reference), MIRS and GOES twice as noisy (0.5) Time error term (currently unused). Current design is to use 100 km radius grid box region around point-in-question for data inputs in Step 2. This is adjustable. New Cost Function for Interpolation Heritage method only has the distance term Reduces topographic effects of GPS stations on mountains or in valleys July 27, Critical Design Review The Blended RR and High Res bTPW Products 36July 27, 2011

Summary Strengths of surface-based TCWV from GPS: 1.Low-cost 2.All weather 3.High temporal resolution (~ 20 minute, 24 h / day) 4.Accuracy 5.Untapped networks for seismology/volcanology exist 6.A few very dense networks (Japanese GEONET ~ 800 stations) Limitations: 1.Sparse spatial coverage (centered on developed world, few ocean sites). 2.Climate record begins in 1995 at ~ 100 sites. 3.No “one stop shopping”, networks are run by a wide variety of agencies. 4.While highly accurate, rare erroneous retrievals are possible (“orbit busts”).

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