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VIC MODEL CALIBRATION AND FUTURE HYDROCLIMATE ANALYSIS IN SELECTED UTAH WATERSHEDS

Report to the Utah Division of Water Resources

(source: http://upload.wikimedia.org/wikipedia/commons/2/2c/Usa_Utah_Brighton_Peaks.jpg)

Prepared by

Andy Wood, NCAR Research Applications Laboratory, Boulder, CO

with assistance from

Tim Bardsley, NOAA Western Water Assessment, Salt Lake City, UT

February 24, 2015

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1. BACKGROUND AND OBJECTIVES

The Utah Division of Water Resources (UTDWR) is interested in improving the quality of the hydrological model results for climate change scenario analysis based on the BCSD downscaled CMIP5 climate and hydrology projections (termed the ‘BCSD5’ dataset)1. The hydrology models used to generate the BCSD5 runoff projections were not explicitly calibrated for the basins of interest to UTDWR, nor were streamflow routing models implemented to provide daily streamflow estimates at the gage locations for the basins. As a result, the runoff simulations for both the current and future climate periods contain systematic, substantial biases that can hamper their interpretation for watershed-‐scale planning studies.

The project described in this report was designed to improve the quality and usability of streamflow projections in the eight river basins listed in Table 1. Three primary activities were undertaken.

1. Implementation of a daily streamflow routing models in each of the basins. 2. Model parameter estimation (ie, calibration) to achieve improved daily and/or

monthly streamflow simulation for the historical period. 3. Simulations of the 97 available BCSD5 climate scenarios using the calibrated

models, yielding daily and monthly streamflow projections.

Table 1. Study Watersheds

NWS Handbook 5 ID USGS ID Location Name

OAWU1 10128500 Weber River near Oakley

WOOU1 10154200 Provo River near Woodland

LGNU1 10109001 Combined Flow Logan River

SFSU1 N/A Scofield Reservoir inflow

HATU1 10174500 Sevier River at Hatch

BEVU1 10234500 Beaver River at Beaver

WTRU1 09299500 Whiterocks River near Whiterocks

BCTU1 10168500 Big Cottonwood Creek near Salt Lake City

1 The BCSD5 projections are available online at http://gdo-dcp.ucllnl.org/

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The models used in the project are the Variable Infiltration Capacity (VIC) hydrologic model of Liang et al. (1999) (version 4.1.2.h) and unit hydrograph based streamflow routing model of Lohmann et al (1996, 1998). Both models were used in generating the original BCSD5 dataset. All models and data used in the study are publicly available.

2. TASK DESCRIPTION

The project involved three major tasks, other than compiling this report: (1) implementing the VIC and routing models for the 8 study basins; (2) calibrating the VIC models; and (3) running and analyzing the BCSD5 climate simulations.

2.1 IMPLEMENTING THE VIC AND ROUTING MODELS

The default VIC parameter and forcing inputs and model code were taken from the BCSD5 effort described in Reclamation (2013). Several GIS datasets were obtained and processed for the watershed areas, including the basin boundaries (from the Colorado Basin River Forecast Center, CBRFC) and a streamline coverage (from the USGS NHDPlus dataset). The 1/8th degree VIC model grid was clipped using the basin boundaries, and the fractional contributing areas for each grid cell were determined. The river basin routing model plots shown in Appendix 7.1 were used to verify the model configuration and correct for routing network errors. The model drainage areas were compared with USGS drainage areas and confirmed to be within 5% of the USGS estimates.

Observed streamflow data for the catchments were obtained from the USGS, CBRFC, and the Salt Lake City Department of Public Utilities (for BCTU1). The CBRFC flow record period was 1981-‐2010, whereas the other sources had records extending back at least to 1950, with the exception of WOOU1, where the data began in 1964. The only SFSU1 flow records were from CBRFC, and were estimated from reservoir changes and partial inflows.

2.2 CALIBRATING THE VIC WATERSHED MODELS

The VIC models and routing were run with the default calibration and the historical observed gridded forcing dataset of Maurer et al. (2002), for the period 1950-‐2010 (which is also the base period for bias-‐correction in the BCSD scenarios). Because at least one of the watersheds (SFSU1) had flow data only for the 1981-‐2010 period, however, this was chosen to be the calibration period for the models. The simulated streamflows with default VIC parameters, which are shown by the blue lines in the model calibration figures of Appendix 7.2, were found to exhibit substantial biases.

The automated multi-‐objective optimization calibration software (‘MOCOM-‐UA’ of Yapo et al, 1998) was implemented to calibrate each watershed separately. The objective function of the calibration included three objective metrics: maximize the Nash Sutcliff Efficiency

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(NSE) of simulated flow and log simulated flow, and minimize the maximum bias in mean monthly log flow. The model calibration parameters included the six VIC soil parameters (layer 2 and 3 depth, the b infiltration parameter (Bi), and the Ws, Ds, and Dsmax baseflow parameters) that are commonly adjusted in VIC model calibration efforts.

Each parameter optimization run returned a pareto-‐optimal set of 16 equifinal (also called ‘non-‐dominated’) acceptable parameter solutions, from which one was selected by visual evaluation of daily and monthly hydrograph time series.

2.3 RUNNING AND ANALYZING THE BCSD5 CLIMATE SIMULATIONS

When the calibrated parameter set for each basin was determined, the 97 BCSD5 projection forcings (daily precipitation, maximum and minimum temperature, and wind speed) were used to produce daily flow simulations from January 1, 1950 to December 12, 2099. The BCSD5 projections are extensively documented in Reclamation (2013), and details of the BCSD5 ensemble are not repeated here. The simulated flow outputs were aggregated to a monthly timestep and converted from model output units of cubic feet per second (CFS) to acre-‐feet (AF). Monthly streamflow outputs were further averaged for six periods: calendar years 1950-‐1999, and water years 1981-‐2010, 2010-‐2039, 2040-‐2069, 2045-‐2074, and 2070-‐2099. In addition, the day of year and date of the centroid of water year flow (or ‘center timing’) was calculated. The timing and monthly average flow results were tabulated to facilitate further analysis.

3. RESULTS

For each of the study watersheds, the individual VIC and routing model domains are shown in the figures of Appendix 7.1. Most of the watersheds were encompassed by fewer than 10 VIC 1/8th degree grid cells, although the number of computation units is higher because each grid cell contains multiple elevation bands and vegetation types, each permutation of which is individually simulated before being re-‐combined (without routing) to output grid cell average moisture fluxes (eg, runoff and baseflow).

The default model calibrations for all locations were generally poor, with a tendency for under-‐simulated low flow periods and over-‐simulated high flow periods. The automatic calibration routine required between a few hundred and approximately 1000 iterations in each watershed to yield acceptable calibrations for the purpose of this study, and one calibration parameter set was selected for each basin. The default and final model calibration results are shown for each location are shown in Appendix 7.2.

Several of the watersheds (WTRU1, SFSU1, OAWU1) were difficult to calibrate, requiring relatively more iterations to come to a final solution. In some cases, the BCSD5 base period simulation results revealed a bias relative to the historical model simulation for the same

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period. Typically, BCSD5 base case flows in April, May and June were biased low, despite matching the historical simulation in other months. Because a major objective of this effort is to reduce the overall bias in BCSD5 base period flows to inspire confidence in future BCSD5 flow projections, the selection of the final model calibration parameters also considered, and attempted to offset, the BCSD5 base case flow bias tendencies. In effect, the resulting watershed models are calibrated to reproduce the observed streamflow climatology given the BCSD5 base case meteorological climatology, over the 1950-‐1999 base case period. This base period was used training the BCSD5 climate downscaling.

Figures 1-‐8 show mean monthly streamflow hydrographs for the 8 study locations. The top panel of each figure compares the observed historical flow for a base period of 1950-‐1999 (in solid black), the VIC model simulated flow for the same base period (in red), and the BCSD5 ensemble mean flow for the base period (dashed black line). The uncalibrated/default parameter simulations shown (in blue) in the calibration plots of Appendix 7.2 are not included here. For the WOOU1 and SFSU1 locations, the base period flows were not available, and an alternate period is shown (WY1964-‐1999 and WY1981-‐2010, respectively) instead.

The bottom panel of each plot shows the BCSD5 ensemble means for the base period and for four other periods often used in climate and water studies: 1981-‐2010, 2010-‐2039, 2040-‐2069, and 2070-‐2099 (using water years). The base period BCSD5 results from the top plot (dashed black line) are also shown in this plot for comparison with the future runs.

The model calibration effort was effective in reducing the hydrology model and downscaling biases so that the BCSD base case ensemble means reproduce the observed monthly mean hydrograph. In cases such as LGNU1, the BCSD base case for this metric is almost completely unbiased. For several cases such as WTRU1, however, biases remain that may need to be removed through a additional steps to interpret the projected streamflow changes in the context of the observed flow climatology. In all cases, the model performance and resulting BCSD5 simulations are greatly improved relative to those that would have been achievable with the uncalibrated BCSD5 results.

The BCSD5 flow results for ensemble means show clearly the projected mean changes in hydrology for the study locations. Table 2 summarizes quantiles of the BCSD5 ensemble distribution for the different periods listed above. At most locations, median flow volumes increase in the future periods relative to 1950-‐1999, with only HATU1 and SFSU1 showing decreases, and BEVU1 remaining about the same. All projections show increased spread (ie, lower quantiles decrease and upper quantiles increase) in the future, relative ot the past In general, the shift of flow timing toward an earlier peak runoff that has been documented elsewhere in the western US is evident at all sites (Table 3).

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Figure 1. Mean monthly hydrographs at BCTU1 for (top) observed flow, simulated flow, and ensemble mean BCSD5 simulated flow, for the base period of 1950-‐1999; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

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Figure 2. Mean monthly hydrographs at BEVU1 for (top) observed flow, simulated flow, and ensemble mean BCSD5 simulated flow, for the base period of 1950-‐1999; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

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Figure 3. Mean monthly hydrographs at HATU1 for (top) observed flow, simulated flow, and ensemble mean BCSD5 simulated flow, for the base period of 1950-‐1999; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

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Figure 4. Mean monthly hydrographs at LGNU1 for (top) observed flow, simulated flow, and ensemble mean BCSD5 simulated flow, for the base period of 1950-‐1999; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

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Figure 5. Mean monthly hydrographs at OAWU1 for (top) observed flow, simulated flow, and ensemble mean BCSD5 simulated flow, for the base period of 1950-‐1999; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

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Figure 6. Mean monthly hydrographs at SFSU1 for (top) observed flow, simulated flow, and ensemble mean BCSD5 simulated flow, for the base period of 1981-‐2010; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

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Figure 7. Mean monthly hydrographs at WOOU1 for (top) observed flow and simulated flows for for WY 1964-‐1999, and ensemble mean BCSD5 simulated flows for the base period of 1950-‐1999; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

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Figure 8. Mean monthly hydrographs at WTRU1 for (top) observed flow, simulated flow, and ensemble mean BCSD5 simulated flow, for the base period of 1951-‐1999; and (bottom) ensemble mean BCSD5 simulated flows for the base period and four additional periods.

Tables 2 and 3 (following two pages). Percentiles of BCSD5 ensembles for annual flow (KAF) and center timing (day of water year, DWY) averaged over different periods.

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KAF period p0.10 p0.25 p0.50 p0.75 p0.90 BCTU1

1950-‐1999 57.9 58.0 58.3 58.6 58.8 1981-‐2010 54.8 55.6 57.5 59.7 63.0 2010-‐2039 53.8 56.8 60.1 63.8 66.9 2040-‐2069 54.6 57.5 61.5 67.1 70.3 2070-‐2099 54.1 58.8 64.2 68.3 72.9

BEVU1

1950-‐1999 36.8 37.2 37.5 38.0 38.4 1981-‐2010 33.3 34.7 36.4 39.0 41.2 2010-‐2039 31.4 34.3 37.3 40.5 44.6 2040-‐2069 29.5 32.9 37.3 41.2 45.1 2070-‐2099 29.9 34.1 37.2 42.9 46.3

HATU1

1950-‐1999 77.1 77.8 78.6 80.2 81.8 1981-‐2010 65.4 69.7 76.8 83.4 87.9 2010-‐2039 60.9 69.5 77.6 88.5 100.2 2040-‐2069 54.9 64.8 75.2 89.1 98.3 2070-‐2099 54.3 64.6 76.2 90.8 103.4

LGNU1

1950-‐1999 186.3 187.2 188.5 189.6 190.6 1981-‐2010 174.3 179.5 186.5 192.2 206.1 2010-‐2039 174.2 181.7 193.9 206.8 215.1 2040-‐2069 175.9 184.6 196.6 216.7 231.1 2070-‐2099 175.7 189.7 207.5 221.6 232.4

OAW

U1

1950-‐1999 180.2 180.6 181.3 181.9 182.3 1981-‐2010 171.1 174.5 179.4 186.4 194.8 2010-‐2039 170.8 176.4 187.8 199.4 206.7 2040-‐2069 171.0 179.5 192.9 209.1 220.9 2070-‐2099 169.7 183.0 199.4 213.3 224.0

SFSU1

1950-‐1999 58.7 59.4 60.1 60.7 61.3 1981-‐2010 52.8 54.9 58.1 62.2 68.2 2010-‐2039 47.7 51.2 58.6 64.6 72.4 2040-‐2069 43.1 48.4 57.2 64.4 71.9 2070-‐2099 42.0 47.7 56.0 66.2 76.3

WOOU1

1950-‐1999 153.0 153.6 154.5 155.1 155.6 1981-‐2010 145.6 148.4 152.6 158.9 167.2 2010-‐2039 144.1 150.2 160.3 170.2 176.5 2040-‐2069 144.6 152.9 164.0 178.3 189.4 2070-‐2099 143.3 155.5 169.4 183.4 191.5

WTRU1

1950-‐1999 81.3 81.6 82.3 82.8 83.1 1981-‐2010 75.1 76.8 79.9 84.5 90.3 2010-‐2039 74.6 78.8 85.6 92.4 97.3 2040-‐2069 72.8 78.6 87.9 99.6 108.2 2070-‐2099 72.2 81.0 91.6 101.8 111.1

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DWY period p0.10 p0.25 p0.50 p0.75 p0.90 BCTU1

1950-‐1999 230 231 231 232 233 1981-‐2010 230 232 234 235 236 2010-‐2039 218 222 224 228 230 2040-‐2069 206 212 217 221 227 2070-‐2099 193 203 210 219 225

BEVU1

1950-‐1999 224 225 226 227 227 1981-‐2010 225 227 228 230 232 2010-‐2039 218 221 223 225 228 2040-‐2069 209 212 217 221 225 2070-‐2099 198 206 213 219 225

HATU1

1950-‐1999 208 209 210 210 211 1981-‐2010 208 210 211 213 215 2010-‐2039 200 203 207 209 213 2040-‐2069 193 197 201 205 208 2070-‐2099 184 190 197 203 209

LGNU1

1950-‐1999 230 230 231 231 232 1981-‐2010 231 232 234 235 236 2010-‐2039 221 224 227 230 231 2040-‐2069 211 216 221 225 229 2070-‐2099 200 207 215 223 227

OAW

U1

1950-‐1999 234 235 235 236 236 1981-‐2010 234 235 237 238 240 2010-‐2039 220 225 228 232 235 2040-‐2069 207 213 221 226 230 2070-‐2099 190 202 214 224 230

SFSU1

1950-‐1999 218 219 220 221 221 1981-‐2010 218 220 222 223 225 2010-‐2039 207 211 215 218 221 2040-‐2069 192 202 208 213 217 2070-‐2099 181 190 203 211 216

WOOU1

1950-‐1999 229 230 230 230 231 1981-‐2010 229 231 232 234 235 2010-‐2039 217 221 224 228 230 2040-‐2069 202 211 218 223 226 2070-‐2099 191 199 212 220 225

WTRU1

1950-‐1999 241 242 243 244 244 1981-‐2010 243 244 246 248 249 2010-‐2039 236 239 241 244 246 2040-‐2069 228 232 237 241 243 2070-‐2099 221 226 233 238 242

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4. DELIVERABLES DESCRIPTION

The following deliverables have been prepared to accompany this report.

1. All model code, parameters, input and output data used in the study. 2. The original historical (1), calibrated historical (1), and calibrated future projection

(97) streamflows for each basin, in CSV format. 3. Analyzed outputs in various forms, including period flow averages and center timing

timeseries.

The files associated with these deliverables are described in Table 4.

Table 4. Description of the data files provided with this report.

Filename Description models.tgz Tarred and gzipped collection of model code,

parameters, historical forcing input and run scripts. Full documentation and instructions for model use is beyond the scope of this report.

BASIN.all.month.PERIOD.AF.csv Monthly averages for the BASIN and PERIOD in acre-‐feet, for for periods CY1950-‐1999 and WY 1981-‐2010, 2010-‐2039, 2040-‐2069, 2045-‐2074, and 2070-‐2099.

BASIN.all.doy.csv, BASIN.all.date.csv

Annual time series of center timing of each WY from 1951-‐2010, as day of water year and date

bcsd5.RUN.tgz Tarred and gzipped bundles of files for 97 BCSD5 RUNs, containing center timing files, routing model output flow files (BASIN.year, BASIN.month and BASIN.day) space-‐delimited in CFS units; and directories named fluxes.BASIN/ that contain grid cell water balance output timeseries (daily), with the following variables: surface runoff, baseflow, evapotranspiration (ET), soil moisture (3 layers), snow water equivalent, net radiation, relative humidity, and potential ET for tall and short crops and a free water surface. Units are mm, W/sq-‐m, and %.

BASIN.RUN.CT_date.csv Annual time series of center timing of each WY from 1951-‐2099, including day of water year and date

BASIN.RUN.month.AF.csv, BASIN.RUN.day.AF.csv

Monthly and daily timeseries, in acre-‐feet, for each BASIN and BCSD5 RUN, spanning 1950-‐99.

forcing.BCSD5.tgz Model forcing files for the 97 BCSD5 projections. Tarred and gzipped.

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5. DISCUSSION

The statistical downscaling approach, BCSD, has been used in numerous research and planning studies over the last decade to translate projected climate outputs from global climate models (GCMs) to local watershed scales. Like most downscaling methods, it has strengths and weaknesses that are by now fairly well documented in study reports and academic literature (see, e.g., Harding et al, 2012). Among the strengths, the method corrects monthly biases in GCM precipitation and temperature for a historical base period so that weather inputs generated from the GCM projections can be used in subsequent analyses (such as hydrologic modeling) without creating prohibitive biases in those analyses for the base period. As a result, the GCM-‐based downscaled historical period climate and associated analyses such as streamflow should by design reproduce observed climate and flow well, reducing concerns about systematic biases in future projections of climate and flow at the watershed scale.

Relative to other methods such as dynamical downscaling, which is not statistically constrained, BCSD is relatively successful at this objective. Yet BCSD base period simulations nonetheless often do exhibit residual bias relative to observations. This residual bias arises primarily from two components: (1) hydrology model bias and (2) bias in the downscaled forcings. Poorly measured observed flow records can be another source of bias. Hydrology model calibration is applied in this study to reduce the model bias.

The downscaling bias arises occurs because the BCSD corrections do not comprehensively adjust all features of the GCM climate outputs to bring them fully into line with historically observed climate values. Working only on a monthly level, the corrections do not directly force agreement of features such as seasonal or annual climate distributions, or observed cross-‐correlation between precipitation and temperature, or auto-‐correlation in each. In addition, and particularly in relatively dry locations, the weather generation aspect of BCSD can lead to differences in the downscaled climatology of daily precipitationa and temperature, from the observed climatology. As a result, the historical period analyses from BCSD typically do contain some degree of bias that is associated with the un-‐corrected aspects of the downscaled GCM forcings. In this study, it was found that the base period (1950-‐1999) discharge values had a tendency to be biased low relative to the observed climatology (ie, monthly averages), particularly during the peak runoff period (April-‐June).

The presence of bias in the downscaled BCSD5 base period can be problematic for interpretation of the future projections. Ideally, a faithful simulation of the base period by the BCSD5 projection provides confidence that the multi-‐step analysis sequence captures the basins’ observed water balance, and hence the future climate period water balance sensitivity. For this reason, an effort was made in this study to choose model calibrations that, when combined with BCSD5 base period weather inputs, provided minimal bias in BCSD5 ensemble average flows bias during the base period. That is, the calibrations are

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chosen to accommodate both hydrology model bias and BCSD downscaling bias. As a result, the final calibrations selected in some locations (eg BEVU1) produces base period historical model simulations (forced with observed meteorology) that are more biased than would likely be selected for a different model application, but should best serve the intercomparison and interpretation of past and future BCSD5 hydrologic projections.

6. REFERENCES

Harding, BL, Wood, AW, and Prairie, JR, 2012. The implications of climate change scenario selection for future streamflow projection in the Upper Colorado River Basin, Hydrol. Earth Syst. Sci., 16, 3989-‐4007, doi:10.5194/hess-‐16-‐3989-‐2012.

Liang X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994. A Simple Hydrologically Based Model of Land-‐Surface Water And Energy Fluxes For General-‐Circulation Models. Journal Of Geophysical Research-‐Atmospheres 99 (D7): 14415-‐14428.

Lohmann D., E. Raschke, B. Nijssen and D. P. Lettenmaier, 1998. Regional scale hydrology: I. Formulation of the VIC-‐2L model coupled to a routing model. Hydrological Sciences. 43(1): 131-‐142.

Lohmann, D., R. Nolte-‐Holube, and E. Raschke, 1996. A large Scale horizontal routing model to be coupled to land surface parametrization schemes. Tellus 48A: 708-‐721.

Maurer, E.P., AW Wood, J.C. Adam, D.P. Lettenmaier and B. Nijssen, 2002. A long-‐term hydrologically-‐based data set of land surface fluxes and states for conterminous United States, J. Clim. 15(22), 3237-‐51.

Reclamation, 2013. Downscaled CMIP3 and CMIP5 Climate Projections: Release of Downscaled CMIP5 Climate Projections, Comparison with Preceding Information, and Summary of User Needs. U.S. Department of the Interior, Bureau of Reclamation, Technical Service Center, Denver, Colorado, 116 p., available at: http://gdodcp.ucllnl.org/downscaled_cmip_projections/techmemo/downscaled_climate.pdf

Wood, AW, L.R. Leung, V. Sridhar and D.P. Lettenmaier, 2004, Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs, Clim. Change Vol. 62, 1-‐3, 189-‐216.

Wood, AW, Maurer, E.P., Kumar, A. and D.P. Lettenmaier, 2002. Long Range Experimental Hydrologic Forecasting for the Eastern U.S., J. Geophys. Res., 107(D20), doi:10.1029/2001JD000659.

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Yapo, PO, HV Gupta, and S Sorooshian, Multi-‐objective global optimization for hydrologic models, Journal of Hydrology, Volume 204, Issues 1–4, 30 January 1998, Pages 83-‐97, ISSN 0022-‐1694, http://dx.doi.org/10.1016/S0022-‐1694(97)00107-‐8.

7. APPENDICES

7.1 VIC AND ROUTING MODEL SETUP

The following 8 figures show the configuration of the VIC model grid cells and routing networks. In each figure, the star symbol shows the routing model cell that is the basin outlet, the orange circle shows the gage location, and the major basin streams and boundary are also plotted. The figures do not have individual captions.

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7.2 CALIBRATION RESULTS

The following 8 figures show the results of the VIC model calibration, for each of the study basins. The observed flow is plotted in black. The simulated VIC model flow using the Maurer et al (2002) forcings with default VIC model calibration parameters is plotted in blue. The simulated VIC model flow using the calibrated model parameters is plotted in red. Daily flows for a short period of a few years are shown in the top panel, illustrating the daily features (such as event recession and flashiness) of the simulation. These are followed by longer annual timeseries of monthly flows (middle two panels) to show the interannual characteristics of the simulations. The bottom panel then shows the long term monthly average flows, which reflect the mean water balance. Units are cubic feet per second, which is the model output unit. The figures do not have individual captions.

These plots show only the 30-‐year calibration period for each plot, although the longer period (1950-‐2010) flows were generated and included in the data deliverables. The calibration was found to be sufficient to estimate model parameters. A split-‐sample calibration and validation was not used, but the good performance of the simulations for the 1950-‐1999 base period (shown in Figures 1-‐8), which has 20 additional years, gives some insight into the stability of the calibration.

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