# Presentation: 897107

## Uncertainties in Low Frequency SST Historical Analyses

- Thomas M. Smith
- Richard W. Reynolds
- NOAA’s National Climatic Data Center

## Definitions

- Low Frequency (LF)—decadal or longer variations (15-year smoothed).  Represents changes in the climate base state.
- High Frequency (HF)—everything else, including ENSO and NAO, *etc*.

## The Problem:

- How much LF variation can be reconstructed using EOF modes?
- HF variations like ENSO are resolved over the recent, well-sampled period.  HF modes may be better in historical reconstructions.
- LF variations like trends are not stationary and not consistently sampled.  It’s not clear how well modes reconstruct historical LF variations.
- The problem: without using LF modes more sampling is needed to analyze the LF, and that may give greater uncertainty for the early period.

## Global SSTs and NMATs

- From IPCC 2001

- Global and annual averages
- Differences greatest before 1950—data most sparse
- Smoothed differences indicate uncertainty in the climate base state

## Evaluating LF Uncertainties

- Data used: ERSST.v2, ICOADS, Kaplan *et al.*, and HadISST SST anomalies through 2004
- Different ways to analyze LF anomalies
- ERSST: simple filtering, large scale and 15-years of data
- HadISST: leading EOF of filtered data
- Kaplan et al: stationary set of modes from a later base period
- LF comparisons to show differences
- LF of ERSST EOF-mode reconstructions to show possible EOFs damping

## ERSST-HadISST Comparisons

- Global averages similar and the need for bias adjustments clear
- Magnitude of adjustment validated by C. Folland
- Adjusted data is sometimes more similar than unadjusted data
- HadISST adjustments from a bias model
- ERSST adjustments based on analyzed SST-NMAT differences

- RMS(ERSST-HadISST)

## Analyses and Data LF

- HadISST slightly warmer than ERSST these times:
- 	1915 weaker cools in Pacific
- 	1965 warmer Southern Ocean

**Notes:**
ERSST 15-year medians centered on each year; ICOADS averaging: ≥4 mon/year and ≥ 6 years, on 2o grid;
1915 center year, ERSST and ICOADS LF similar; ERSST smoother, sometimes weaker; Where sampling is poor, ERSST LF is weak

## LF Zonal Averages

- ICOADS much warmer north of 60oN
- few data, Arctic Ocean & N. Atlantic
- analyses filter out most of those strong anomalies
- ICOADS cooler before 1920
- Tropical W. Pacific, sampling too sparse for analyses

## Comparisons: LF of ERSST, ICOADS, & HadISST

- Global Averages of LF SSTA for each
- LF difference
- |ERSST-HadISST| ≤  0.05oC
- RMSD = 0.02oC
- overall similar climate variation
- OS (Kaplan) slightly more damped
- ICOADS differences
- Cooler early (1901-1930)
- Warmer after 1980
- Both analyses may be damping LF anomalies

## Summary of ERSST-HadISST LF Comparisons

- Global variations similar, both before and after bias adjustments
- Differences that occur are due to both bias-adjustment and data-analysis differences
- Global ERSST-HadISST LF absolute differences are 0.05oC or less:
- Both resolve LF about equally well
- Both are damped compared to ICOADS early in the 20th century

## Tests of LF Reconstructions

- Different estimates of the ERSST LF are compared:
- LF ERSST
- LF ERSST reconstructed LF EOFs, based on 1901-2000
- LF ERSST reconstructed LF EOFs, based on 1951-2000
- Both sets of EOFs account for about 90% of the LF variance in their base periods
- Test of historical LF variance lost by EOF reconstruction

## 3 EOF Recon of LF ERSST: Global Averages

- EOFs based on full period reconstructs average with little error
- If you know it, you can get it back
- EOFs based on 2nd half of the period damps variance in the 1st half
- Uncertainty as much as 0.08oC, average 1901-1950 is 0.06oC

## ERSST LF and LF EOF Recons

- LF EOF Recons impose mean patterns from their base, and are
- spatially smoother than the analysis. Details of the patterns
- are not  reproduced by the Recons.

## Global Averages: RMS Differences

- Both ERSST & HadISST LF damped in early 20th century (w.r.t. ICOADS)
- Modes only reconstruct the LF variations they span
- Damping uncertainty may be unavoidable
- Tests & comparison suggest that global LF damping RMSE can be up to about 0.1oC

**Notes:**
Recon = recon of ERSST using 1951-2000 modes
Post-1950 differences between ERSST-ICOADS & ERSST-Recon may represent ICOADS noise
Besides damping, residual LF analysis differences from bias adj, data sources, QC, and analysis methods

## Summary of LF EOF Reconstruction

- In EOF dependent-period reconstructions: global average close to the base average
- In EOF independent-period reconstructions: damping reduces variance
- Actual damping in early 19th century may be less than EOF testing suggest:
- EOF testing suggest RMSE ≈ 0.09oC
- ERSST decadal RMS error estimate for early 20th century ≈ 0.07oC (based on sampling of a trend with observed sampling)
- Some LF variance may project onto HF modes, reducing errors
- LF ERSST-HadISST RMSD = 0.02oC, max difference ≈ 0.05oC
- Both ERSST & HadISST damped, so their difference does not give the full error

## Some Global LF Standard Error Comparisons

- Standard error estimates of ERSST and comparisons for two periods.  ERSST
- estimates from EOF damping & SR decadal estimates, compared to other estimates.

-  Boost modern ERSST variance by 1.15: some ERSST damping.
-  SR ERSST est. from sampling of a trend.
-  Jones *et al.* consistent, based on spatial scale estimates.
-  Folland *et al.* using large-scale modes.  Smaller error estimates may underestimate sampling error.

| Averaging time | Based on 115% ERSST 1951-2000 2 (EOF damping) | Based on SR ERSST est. of decadal error (from sampling of trend) | Jones et al. (1997) decadal error (sampling only) | Folland et al. (2001) OA
(land+sea sampling) |
| --- | --- | --- | --- | --- |
| 1951-2000 | 0.05oC | 0.03oC
 | 0.05oC | <0.01oC |
| 1901-1950 | 0.07oC
 | 0.07oC
 | 0.06oC | 0.01oC |

## Conclusions

- RMS LF global uncertainties are about 0.07oC early in the 20th century, when sampling is most sparse
- For long (interdecadal) time scales, several different methods give similar uncertainty estimates
- Most climate-base changes can be detected through the 20th century
- Errors based only on fits to modes can underestimate sampling error
- Reconstructing LF without using EOFs may better resolve the large-scale variations, but sampling still a problem
- For smaller regions and shorter averaging times, different estimates are less consistent
- Some interannual SST episodes may not be analyzed as reliably early in the 20th century

**Notes:**
Note: for annual averages, global average of SR merged errors are larger than FEA errors