Elena Tanase National Institute of Hydrology and Water Management, Bucharest ROMANIA

1. BALWOIS 2006 The Spectral Analysis Method For The Evidence Of Teleconnection Phreatic Levels And North Atlantic Oscillation In The Frame Of Regional Impact Of Natural Variability In The NW Part Of Romania. Elena Tanase National Institute of Hydrology and Water Management, Bucharest ROMANIA

2. The spectral analysis method • The spectral analysis method was applied in various papers for the study of variability of precipitation, runoff, temperature in the N Hemisphere. • Natural processes presents spectrum with periodicities attributed to the • Solar cycle (11 year ) in particular years • North Atlantic Oscillation (cvasi-biennal & cvsi-decadal oscillations) • Interest in modeling the red noise spectrum with autoregressive models of first order for detection the significance of peaks (usual method). • Detection and attribution of the climate signal is a challenge.

3. NW Romania Location in a plain area and distribution of the 96 drills (symbol ● for 26 Somes River Basin drills and Δ for70 Crisuri River Basin drills) of type II in the NW part in Romania. The drills of type II have a regime not influenced by rivers. Latitude N Longitude E

4. The NAO signal • In the context of the global warming, the changes in the temperature values over the past 100 years show an increasing trend for the reference period 1961-1990 with 0.3 to 0.6 0 C with different warming dependent on the location and local changes in the precipitation field. • NAO signal early alert of drought in winter for Europe • Precipitation anomalies associated to NAO, the E-P balance for DJFM index (high-low index years) show for Romania E-P >0 (mm/day). Hurrell, J.W, 1995: Decadal trends in the North Atlantic Oscillation: regional temperatures and precipitation, Science, 269, 676-679

5. NAO spectrum (1866-2000) • The NAO spectrum is a natural process spectrum of red type, the variance is increasing with period . • L.Gimeno, et al., 2005 Characteristic peaks at 9-7 years, 5.8 years, 2-4 years, 2.2 years, the manifestation of the 8 years oscillations is realized during the positive NAO phase.

6. Atmospheric Circulation NAOI P Phreatic levels P NAO+ DJFM T depth Data and conceptual model • 96 drills situated away from rivers in a plain area in NW Romania • seasonal regime (Dec-Mar), interannual variations • 1979-1993 • the water supply of the phreatic is from precipitation (not from rivers) • Positive phase of NAO (NAO+) means reducing winter precipitation, increasing temperature, increasing depth of phreatic levels. • h • NAOI • P

7. Autocorrelation plot for phreatic levels • Significant autocorrelation peaks at 99% CL: 4, 6, 8, 11 years. • The position of the peaks on ACF graph is indicating the position of the peaks in the spectral analysis plots (spectral power, spectral coherency plots). • In literature the periodicities of ACF are called return periods()

8. The EOF Analysis >> EOF is a filtering , denoising method, is utilized in spatial and temporal pattern detection >> Data are constituted in a input matrix X(t) = [Xi(t)], i=1, 2…I, n=15, I=96 and are standardized >>a linear transformation give a new set of variables Y1, Y2, … (named Principal Components or PCs). Y1 = a11X1 + a21X2 + ... + ap1Xp >>the correlation matrix (DATAPLOT) is the base of computing in EOF. The mains steps of the methods are: • Compute eigenvectors for matrix X (obtain the Empirical Orthogonal Functions EOFs, or aij) • The projections of initial X on the EOF is leading to the PCs.

9. 72.15% ~ JF months variance Power spectrum for main component of phreatic levels • The midle latitudes NW Romania pattern of spectrum has a variance contribution of JF months in winter, during particular years. • At middle latitudes the power spectrum of main component of phreatic levels (which explain 72.15% of variance) presents both cvsi-biennal &cvasi-decadal characteristic oscillations.

10. ~ 6-8 y ~ T2 ~ 2.2-2.4 y Spectral Coherence for main component of phreatic levels • Spectral coherence better isolates the main characteristic oscillations than the power spectrum. • Specific feature of natural processes spectrum is present: variances are increasing with period (decreasing with increasing frequency). • The spectral coherency plot shows cvasi-biennal and cvasi-decadal oscillations at ~6-8 years, ~2.2-2.4 years.

11. AR(1) The red noise spectrum • The theoretical red noise spectrum is modeled by autoregressive ordin 1 AR(1) model:  y(t)=Φy(t-1)+ε(t), where Φ=0.064 is computed, Φ< 1, ε (t) is a random number, i.e mean is zero , variance is unity: Φmean=0, σ=1. The spectrum of the red noise signal is computed with the formula: S(f)=(1- Φ2) / (1+ Φ2 – 2Φcos 2πf) , f is the frequency. • Statistical significance of peaks is assured , the peaks spectrum exceed the red noise limit.

12. Conclusions • The spectrum of main component of phreatic levels is analyzed with the coherence plot and spectral amplitude plot • In the NW Romania in winter the solar cycle (11 years) modulates the North Atlantic influence of the phreatic regime through the JF months . • The detection and attribution to NAO of cvsi-biennal and cvasi-decadal periodicities (at 6-8 years and ~2.2 years) for the phreatic levels spectrum at the type II drills is a net result of the EOF method. • The peaks of main component of phreatic levels during winter season exceed the red noise spectrum, statistic significance is assured .