Non-Stationarity of Wintertime Atmospheric Circulation Regimes in the Euro-Atlantic Sector

<p>Atmospheric circulation regimes can be used to study links between regional weather and other climate processes, like sudden stratospheric warmings. For these studies it is important to know whether there is any background non-stationarity in the regimes themselves. To identify regime non-stationarity model ensemble data is needed to have sufficient data. However, models are noisy in their representation of circulation regimes making obtaining the signal difficult. We propose a new method, in the form of a constraint on the ensemble-member similarity in the clustering method, to identify the signal of the non-stationary regime dynamics.</p><p>We use ECMWF SEAS5 hindcast data to identify six wintertime circulation regimes over the Euro-Atlantic sector (NAO+/-, Atlantic Ridge (AR) +/- and Scandinavian Blocking (SB) +/-), which has been found to be the optimal number of regimes in a previous study. Implementing the constraint leads to more robust regimes and the identification of a stronger inter-annual signal in the regime occurrence rates than without the constraint. The clearest signal on inter-annual timescales is found during strong El Niño years. During those years the NAO+ becomes less frequent, while the SB- occurs more often. The signal in the occurrence rate of the NAO- is weaker than for the NAO+. Without the implementation of the constraint this difference in the strength of the signal between the two phases of the NAO cannot be detected. Thus, the constraint on the ensemble-member similarity allows for identifying a non-stationary signal that otherwise is more difficult to obtain.</p>

Separation of geophysical signals in the LAGEOS geocentre motion based on singular spectrum analysis

SUMMARY We recompute the 26-yr weekly Geocentre Motion (GCM) time-series from 1994 to 2020 through the network shift approach using Satellite Laser Ranging (SLR) observations to LAGEOS1/2. Then the Singular Spectrum Analysis (SSA) is applied for the first time to separate and investigate the geophysical signals from the GCM time-series. The Principal Components (PCs) of the embedded covariance matrix of SSA from the GCM time-series are determined based on the w-correlation criterion and two PCs with large w-correlation are regarded as one periodic signal pair. The results indicate that the annual signal in all three coordinate components and semi-annual signal in both X and Z components are detected. The annual signal from this study agrees well in both amplitude and phase with those derived by the Astronomical Institute of the University of Bern and the Center for Space Research, especially for the Y and Z components. Besides, the other periodic signals with the periods of (1043.6, 85, 28), (570, 280, 222.7) and (14.1, 15.3) days are also quantitatively explored for the first time from the GCM time-series by using SSA, interpreting the corresponding geophysical and astrodynamic sources of aliasing effects of K1/O1, T2 and Mm tides, draconitic effects, and overlapping effects of the ground-track repeatability of LAGEOS1/2.

Seasonal Variation of GPS-Derived the Principal Ocean Tidal Constituents’ Loading Displacement Parameters Based on Moving Harmonic Analysis in Hong Kong

The classical harmonic analysis (CHA) method only can be used to obtain the harmonic constants (amplitude and phase) of ocean tide loading displacement (OTLD). In fact, there are significant seasonal variations in the harmonic constants of OTLD. A moving harmonic analysis (MHA) method is proposed, which can effectively capture the seasonal variation of OTLD parameters. Based on 5 years of kinematic coordinate time series in direction U of six Global Positioning System (GPS) stations in Hong Kong, the MHA method is used to explore the seasonal variation of the OTLD parameters of the 6 principal tidal constituents (M2, S2, N2, K1, O1, Q1). The influence of mass loading on the seasonal variation of OTLD parameters is analyzed. The results show that there are obviously seasonal variations in OTLD parameters of the 6 principal tidal constituents in Hong Kong. The OTLD’s amplitude’s changes of the 6 principal tidal constituents are around 4–25.1% and the oscillation ranges of OTLD’s phase parameters vary from 8.8° to 20.4°. Among the seasonal variations of OTLD parameters, the annual signal, the semi-annual signal, and the ter-annual signal are the most significant. By analyzing the influence of atmospheric loading on the seasonal variation of OTLD parameters, it is found that atmospheric loading has certain contribution to the seasonal variation of OTLD parameters. Hydrological loading and non-tidal ocean loading have little influence on the seasonal variation of OTLD parameters.

Application of singular spectrum analysis in reconstruction of the annual signal from GRACE

The mixture effect of the long-term variations is a main challenge in single channel singular spectrum analysis (SSA) for the reconstruction of the annual signal from GRACE data. In this paper, a nonlinear long-term variations deduction method is used to improve the accuracy of annual signal reconstructed from GRACE data using SSA. Our method can identify and eliminate the nonlinear long-term variations of the equivalent water height time series recovered from GRACE. Therefore the mixture effect of the long-term variations can be avoided in the annual modes of SSA. For the global terrestrial water recovered from GRACE, the peak to peak value of the annual signal is between 1.4 cm and 126.9 cm, with an average of 11.7 cm. After the long-term and the annual term have been deducted, the standard deviation of residual time series is between 0.9 cm and 9.9 cm, with an average of 2.1 cm. Compared with the traditional least squares fitting method, our method can reflect the dynamic change of the annual signal in global terrestrial water, more accurately with an uncertainty of between 0.3 cm and 2.9 cm.

An analysis of terrestrial water and groundwater storage changes in North America using recent GRACE products

<p>In this study, we use temporal solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission to study the surface mass variations of hydrological origin in North America. The most recent release (RL06) of GRACE Level 2 data from three processing centers (CSR, JPL, GFZ) and mascon products are used in a combination scheme to produce estimates of terrestrial water storage (TWS) changes for the period 2002–2016. The land hydrology signal is isolated from GRACE data by removing the contribution of two major non-hydrologic processes, i.e., the glacial isostatic adjustment (GIA) and the ice mass melting from the glaciated areas of Alaska, Greenland and the Canadian Arctic.</p><p>The examination of long-term TWS trends revealed strong signatures of the 2011–2015 droughts in California and Texas, as well as accumulation of TWS in the central part of North America. Negative long-term TWS trends associated with ice melting were found around the Hudson Bay region. The TWS changes are dominated by a strong annual and semi-annual signal with higher magnitude in Alaska and along the west coast of North America.</p><p>An additional study on the estimation of groundwater storage (GWS) changes is performed using the Global Land Data Assimilation System (GLDAS) model. The GLDAS data are pre-filtered using the same strategy as GRACE data to ensure spectral consistency between them. The general behavior of GWS agrees well with the TWS, especially in terms of positive long-term GWS trends in central North America and strong annual signal in Alaska. Positive GWS trends are also identified in the east US coast.</p>

Dynamic ocean topography of the northern Nordic seas: a comparison between satellite altimetry and ocean modeling

The dynamic ocean topography (DOT) of the polar seas can be described by satellite altimetry sea surface height observations combined with geoid information as well as by ocean models. The altimetry observations are characterized by an irregular sampling and seasonal sea ice coverage complicating reliable DOT estimations. Models display various spatiotemporal resolutions but are limited to their computational and mathematical context and introduced forcing models. In the present paper, ALES+ retracked altimetry ranges and derived along-track DOT heights of ESA's Envisat and water heights of the Finite Element Sea Ice-Ocean Model (FESOM) are compared to investigate similarities and discrepancies. The goal of the present paper is to identify to what extent pattern and variability of the northern Nordic seas derived from measurements and model agree with each other, respectively. The study period covers the years 2003–2009. An assessment analysis regarding seasonal DOT variabilities shows good agreement and confirms the dominant impact of the annual signal in both datasets. A comparison based on estimated regional annual signal components shows 2–3 times stronger amplitudes of the observations but good agreement of the phase. Reducing both datasets by constant offsets and the annual signal reveals small regional residuals and highly correlated DOT time series (Pearson linear correlation coefficient of at least 0.67). The highest correlations can be found in areas that are ice-free and affected by ocean currents. However, differences are visible in sea-ice-covered shelf regions. Furthermore, remaining constant artificial elevations in the observational data can be attributed to an insufficient representation of the used geoid. In general, the comparison results in good agreement between simulated and altimetry-based descriptions of the DOT in the northern Nordic seas.

Dynamic Ocean Topography of the Greenland Sea: A comparison between satellite altimetry and ocean modeling

The dynamic ocean topography (DOT) in the polar seas can be described by satellite altimetry sea surface height observations combined with geoid information and by ocean models. The altimetry observations are characterized by an irregular sampling and seasonal sea-ice coverage complicating reliable DOT estimations. Models display various spatio-temporal resolutions, but are limited to their computational and mathematical context and introduced forcing models. In the present paper, ALES+ retracked altimetry ranges and derived along-track DOT heights of ESA's Envisat and water heights of the Finite Element Sea-ice Ocean Model (FESOM) are compared to investigate similarities and discrepancies. The study period covers the years 2003–2009. An assessment analysis regarding seasonal DOT variabilities shows good accordance and confirms the most dominant impact of the annual signal in both datasets. A comparison based on estimated regional annual signal components shows 2–3 times stronger amplitudes of the observations but good agreement of the phase. Reducing both datasets by constant offsets and the annual signal reveals small regional residuals and highly correlated DOT time series (correlation coefficient at least 0.67). The highest correlations can be found in areas that are ice-free and affected by ocean currents. However, differences are visible in sea-ice covered shelf regions. Furthermore, remaining constant artificial elevations in the observational data can be addressed to an insufficient representation of the used geoid. In general, the comparison results in good accordance between simulated and altimetry based description of the DOT in the Greenland Sea. Furthermore, the investigation shows that combining both datasets and exploiting the advantages of along-track altimetry observations and those of homogeneous modeled DOT representations leads to a deeper comprehension of the Arctic Ocean's DOT.

Reduction of the 59-day error signal in the Mean Sea Level derived from TOPEX/Poseidon, Jason-1 and Jason-2 data with the latest FES and GOT ocean tide models

Mean sea level (MSL) is a prominent indicator of climatic change (Ablain et al., 2015; Cazenave et al., 2014; Leuliette and Willis, 2011), and is therefore of great scientific and societal interest. Since the beginning of the altimeter mission TOPEX/Poseidon, followed by Jason-1 and Jason-2 on similar orbits, and many other missions on different orbits (ERS, EnviSat, etc.), MSL products became essential to the comprehension of Global ocean circulation. Since early in the TOPEX/Poseidon mission (Nerem, 1995) a suspicious signal, having period near 59 days and amplitude of roughly 5 mm, was apparent in the GMSL record. Compared with the 4–5 mm amplitude of the annual signal (Minster et al., 1999), the suspicious 59-day signal has understandably attracted attention. Moreover, the same signal has been subsequently detected in Jason-1 and later Jason-2 MSLs. In 2010, it was the subject of a dedicated session at the Ocean Surface Topography Science Team (OSTST) meeting in Lisbon. The conclusions were this signal is the aliasing of a higher frequency error inherited from the tide model correction: the semi-diurnal wave S2. The source of this error was mainly attributed to TOPEX measurements which are assimilated in ocean tide models. When these models are used in the computation of TOPEX/Poseidon MSL, most of the error cancels. However, this error is communicated to Jason-1 and Jason-2 MSLs. Since 2010, considerable efforts have been undertaken within the ocean tide community in order to correct ocean tide S2-waves from this error, particularly in the Goddard Ocean Tide (GOT) and Finite Element Solution (FES) latest versions. The present paper aims at assessing, quantifying and characterizing the reduction of the 58.77-day error thanks to the latest releases.

A novel pollen-based method to detect seasonality in ice cores: a case study from the Ortles glacier, South Tyrol, Italy

We present novel results of pollen analyses performed on a 10 m firn core retrieved from Alto dell’Ortles glacier (3840 m a.s.l.), Eastern Italian Alps, in 2009. The objective was to identify and quantify pollen grains retained in the ice to detect annual and interannual variations in the pollen spectra, thus enabling construction of an accurate pollen-based timescale. Up to now, this has been achieved by pollen diagram interpretation. Here we present a statistical approach developed to extract the seasonal/annual signal contained in the pollen spectra of an ice core. The method is based on principal component analyses of pollen assemblages obtained by high-level taxonomical identification. We apply this approach to the Ortles samples, demonstrating that seasonal and yearly variations of the pollen spectra are easily detectable and provide valuable information that can help improve the chronological model of the firn core. This approach can potentially be used for deeper cores as well as other types of archives (e.g. varved sediments), allowing faster, more objective estimation of yearly and seasonal variations than with classical percentage pollen diagrams.