Transcript View ePoster - 2015 AGU Fall Meeting

G13A-0936. Towards a New Vertical Datum
Daniel R. Roman1, Xiaopeng Li2, Simon A. Holmes3, Vicki A. Childers4, and Yan M. Wang1
1. Geosciences Research Division, NOAA's National Geodetic Survey, Silver Spring, MD, United States. 2. Earth Resources Technology, Inc., NOAA's National Geodetic Survey, Silver Spring, MD, United States
3. Stinger Ghaffarian Technologies, Inc., NOAA's National Geodetic Survey, Silver Spring, MD, United States. 4. Observations and Analysis Division, NOAA's National Geodetic Survey, Silver Spring, MD, United States .
ABSTRACT
Figure 1. Difference between terrestrial and airborne gravity between degrees 150
and 450 (40-130 km spatial resolution). Multi-mGal features spanning 100 km can
result in dm-level geoid errors. GOCE cannot resolve such errors.
APPROACH
The National Geodetic Survey (NGS) is responsible for maintaining and improving the National Spatial
Reference System. This paper particularly focuses on developments leading to a new vertical datum to
replace the existing North American Vertical Datum of 1988 (NAVD 88). This new model will be developed
from a combination of satellite, airborne, and terrestrial gravity data to define a gravimetric geoid height
model. In particular, the aerogravity data collected as a part o the Gravity for the Redefinition of the
American Vertical Datum (GRAV-D) Project are intended to help achieve the goal of a cm-level accurate
geoid model to serve as the new vertical datum. The different data sources have been melded into a single
gravity field model consistent across the entire spectrum to about 2 km resolution. A previous comparison
developed a localized model over just the southern Texas region, where the Geoid Slope Validation Study
for 2011 (GSVS 11) demonstrated that it was possible to achieve the desired accuracy. This new model was
developed using methodology consistent at regional to national scales following techniques used to make
USGG2009 and USGG2012, but now incorporating aerogravity. This new model proves out the basic
concepts behind GRAV-D in that the aeorgravity bridge the spectral gap between satellite and terrestrial
data and provide the requisite improvements to the derived gravimetric geoid height model - all without
artificially targeting a solution to a specific test area. Additional comparisons were made to tidal bench
mark data observed by GPS in combination with ocean topography models to validate the behavior of the
model in the coastal regions.
Aerogravity were combined with the GOCO03S model (Mayer-Gürr et al. 2012) to develop a model
of the Earth’s gravity field that are independent of NGS’s terrestrial data. The aerogravity profiles
were collected under the Gravity for the Redefinition of the American Vertical Datum (GRAV-D)
program (Smith 2007) specifically with the intent of developing a cm-level accurate geoid height
model. These data are collected between 6-11 km in elevation and at 10 km track spacing. This
necessarily limits the lower resolution of the aerogravity to 20 km. In fact, after analysis, it has been
determined to be reliable to about 40 km, though future filtering improvements should result in
achieving 20 km resolution. The tracks themselves are typically about 500 km long due to aircraft
and fuel limitations. This still allows significant spectral overlap with satellite-only models such as
GOCO03S built using GRACE and GOCE (Drinkwater et al. 2006) data. The expected resolution of the
aerogravity is currently between degrees 100 and about 540 (40 km equivalent) expressed in
ellipsoidal harmonics. To permit a smoother transition, the GOCO03S model is tapered to zero
between degrees 100 and 200 with the half power point at degree 150. The aerogravity are
developed in a harmonic model and blended from zero to full power in the same range, making the
effective transition from aerogravity to satellite data at about degree 150. Finally, the EHM is filtered
to zero at degree 540 with the half power point at degree 450. The effective range of the
aerogravity is then between degrees 150 and 450.
INTRODUCTION
To provide a consistent comparison, EGM2008 was similarly adapted. GOCO03S was blended in with
a half power point of 150 and then filtered to zero at degree 540 with a half power point at degree
450. Since both this adapted EGM2008 model and the combined NSG satellite-aerogravity model
are built on GOCO03S through degree 150, differences seen between the models will emphasize any
long to intermediate wavelengths between terrestrial data in EGM2008 and the aerogravity (Figure
1). Much of the terrestrial data that NGS holds was available to the National Geospatial-Intelligence
Agency and was used in making EGM2008. Hence a comparison to this grid of differences to the
terrestrial points values will highlight potential corrections.
EGM2008 was built using GRACE (Tapley et al. 2004) gravity field models and a significant terrestrial gravity
data set. In parts of the United States, much of this data is suspect. This paper focuses on a data domain
solution to cleaning such data. A previous study (Smith 2011) demonstrated that satellite, airborne and
terrestrial gravity data could be spectrally merged to produce a gravimetric geoid height model accurate
most likely to the cm-level. While this certainly met the desired goal of accuracy, the approach did not
resolve issues in the underlying terrestrial data (Saleh et al. 2012), Poorer performing data were detected
using established techniques (Roman et al. 2013). New here is that appropriate corrections were
determined & applied, and a final comparison then made to determine if this approach is viable for
cleaning the extensive terrestrial gravity data set at the National Geodetic Survey (NGS), where nearly two
million points are used in modeling.
Figure 2. Separation of points in surveys bases on comparisons with aerogravity.
Retained data statistics are on left and rejected data on right. Note that data are
broken out by survey line.
This is very urgent because NGS will adopt a new vertical datum in 2022 based on a gravimetric geoid. A
regional model that is acceptable to Canada, Mexico, Central American nations and nations in the
Caribbean is also very desirable (Smith et al. 2013). To that end then, resolving systematic errors in the
existing NGS gravity data is essential and away forward is needed. The magnitude of these gravity errors is
usually just a few mGal’s but their spatial extent results in errors at the dm-level. This work demonstrates
that detecting and cleaning such data is feasible though much work remains to be done.
Figure 2 provides the comparison of the existing terrestrial data to a EHM developed from the
GRAV-D aerogravity. Points are collected in surveys and are thought to have systematic features
associated within each survey. Points in surveys as an aggregate were evaluated specifically looking
for potential biases or trends. Those points with significant systematic differences were rejected
lower right of Figure 2. The good data are shown in Figure 3 are then the retained data that are
gridded, while Figure 4 shows the magnitudes of the rejected data. Figure 5 shows the interpolated
corrections determined from Figure 1. When these were applied to the rejected points in Figure 4,
the resulting “cleaned” data are then shown in Figure 6 and are available for further analysis. Figure
7 shows a grid of all passed and cleaned data.
Figure 8. Geoid Slope Validation Study Line for 2011 (GSVS 11). Of primary interest were
minimally constrained GPS on leveling on 218 bench marks. These provide an independent
comparison for geoid models developed using different techniques.
COMPARISON TO GSVS 11 LINE
In 2011, NGS collected GPS, leveling, terrestrial gravity, astrogeodetic Deflections of the
vertical, and gravity gradients all along a 330 km line in South Central Texas (Figure 8). This
line of data is intended for geoid studies and was collected under the the Geoid Slope
Validation Study for 2011 (GSVS 11) project (Smith 2011). This line of data was collected
under the TX09 aerogravity collection region with the specific intent of determining the
feasibility of cm-level accuracy in gravimetric geoids. It demonstrated that this was feasible.
However, the approach relied strictly on a spectral merging of data sets that had significant
systematic effects as is seen in Figure 1. The intent here then is to make multiple
comparisons to determine if the cleaning approach employed here was successful. Models
for comparison were: (1) the enhanced version of EGM2008 (i.e., with GOCO03S blended
in), (2) a gravimetric geoid model developed from all NGS data that used the enhanced
EGM2008 model as a reference field, (3) a geoid model built using only those data deemed
to be relatively unbiased (i.e., “good”) on the enhanced EGM2008 model (Figure 3), and (4)
the good and cleaned data in a geoid model based on the enhanced EGM2008 model
(Figure 7). Comparisons were made to 218 GPS/leveling marks (Table 1), which were all
minimally constrained to obtain an internal consistency but not be tied to any datum
specific biases and trends (known to exist in leveling based on NAVD 88. The comparisons
show that dropping suspect data helped somewhat (S.D. improved from 1.6 cm to 1.5 cm),
but that cleaning the data and using that extra information did better still (S.D. of 1.3 cm.).
This is only a first attempt though and is based on the assumption that the terrestrial signal
in EGM2008 is directly related to that of the NGS terrestrial data.
Table 1. Comparisons to the GSVS 11 GPS/leveling line with interpolated values from geoids determined from
EGM2008, EGM2008 plus NGS terrestrial data, EGM2008 plus unbiased data only, and EGM2008 plus
unbiased and cleaned gravity data. Removing biased data helped but cleaning and restoring was better.
Data Set
EGM2008 EGM2008 +
all FAA
Average (m) 0.376
0.374
S.D. (m)
0.016
0.016
EGM2008 +
Unbiased FAA
0.374
0.015
EGM2008 +
Unbiased + Cleaned
0.374
0.013
CONCLUSIONS & OUTLOOK
Aerogravity have demonstrated that significant systematic effects exist in terrestrial gravity
data held at NGS. These data were separated and corrected based on differences between
EGM2008’s terrestrial signal and the aerogravity signal in the bandwidth between degrees
150 and 450. The corrected values were then combined with the data that had passed the
initial analysis step and then compared along the GSVS 11 profile. A definite improvement
was seen though not yet at the desired cm-level of accuracy. Continued refinements should
improve both the aerogravity products as well as the cleaned gravity data. Ten years remain
to determine a cm-level accurate geoid height model. This will likely be sufficient time but
research and development must continue at a vigorous pace to ensure it is done along with
the production and collection schedules.
REFERENCES
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Figure 3. Grid of retained data. Suspect data (black dots in
Figure 2) were removed and retained data were gridded.
Figure 4. Plot of suspect data not used in Figure 3. Note the bias
of nearly 1 mGal in this subset of data; evidence of biased data.
Figure 5. Corrections. At each suspect point in Figure 4, a
correction was interpolated from the Figure 1 grid.
Figure 6. Rejected data (Figure 4) are corrected (Figure 5) and new
residuals formed. Note reduction Of mean value from Figure 4.
Figure 7. Grid of retained and corrected/cleaned data.
Tapley BD, S Bettadpur, M Watkins, and C Reigber (2004) The gravity recovery and climate experiment:
Mission overview and early results. GEOPHYSICAL RESEARCH LETTERS 31 (9).