Dominant Time Scales Research Articles

Variability in the Deep Overflow through the Heng-Chun Ridge of the Luzon Strait

AbstractThe deep water overflow at three gaps in the Heng-Chun Ridge of the Luzon Strait is investigated based on long-term continuous mooring observations. For the first time, these observations enable us to assess the detailed structure and variability in the deep water overflow directly spilling into the South China Sea (SCS). The strong bottom-intensified flows at moorings WG2 and WG3 intrude into the deep SCS with maximum along-stream velocities of 19.2 ± 9.9 and 15.2 ± 6.8 cm s−1, respectively, at approximately 50 m above the bottom. At mooring WG1, the bottom current revealed spillage into the Luzon Trough from the SCS. The volume transport estimates are 0.73 ± 0.08 Sv at WG2 and 0.45 ± 0.02 Sv at WG3, suggesting that WG2 is the main entrance for the deep water overflow crossing the Heng-Chun Ridge into the SCS. By including the long-term observational results from previous studies, the pathway of the deep water overflow through the Luzon Strait is also presented. In addition, significant intraseasonal variations with dominant time scales of approximately 26 days at WG2 and WG3 have been revealed, which tend to be enhanced in spring and may reverse the deep water overflow.

Spatio-temporal variability of the wet component of the troposphere – Application to satellite altimetry

Due to the presence of water vapour and cloud liquid water in the atmosphere, the wet component of the troposphere is responsible for a delay in the propagation of the altimeter signals, the Wet Path Delay (WPD). The high space–time variability of the water vapour distribution makes the modelling of WPD difficult, its effect still being one of the main error sources in satellite altimetry applications, e.g. in the estimation of Mean Sea Level (MSL). The understanding and the quantification of the WPD variability on various spatial and temporal scales are the main purposes of this study, in view to improve the MSL error budget. The dominant timescales of WPD variability and its correlation with Sea Level Anomaly (SLA) are examined. In these analyses, the atmospheric reanalysis ERA-Interim model from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to derive a global dataset of daily grids of WPD, spanning a 28-year period from January 1988 to December 2015. The Seasonal-Trend decomposition procedure based on Loess (STL) is used to extract precise WPD annual and interannual signals. Linear trends have been derived from the interannual time series and the contribution of each STL component was mapped globally, allowing the understanding of the WPD variability in spatial terms. The correlation between SLA and WPD is mapped and decomposed into seasons using monthly mean grids, for a period of 21-years, from January 1993 to December 2013.Aiming at inspecting the sensitivity of the results to the used data set, the WPD temporal analysis is extended to the data set provided by the Special Sensor Microwave Imager (SSM/I) and SSM/I Sounder (SSM/IS) Sensors. The WPD from SSM/I(S) is compared against those from the ERA-Interim and from the National Centers for Environmental Prediction (NCEP).Results show that climate phenomena, especially the El Niño Southern Oscillation (ENSO) are the cause for this high variability, since they affect the water vapour and temperature. The observed trends from ERA-Interim, computed globally and over ocean regions only, allow concluding that WPD is increasing with time by approximately 0.1 mm per year, and the maximum trends are observed for the Pacific North and Indian Oceans. High correlation between WPD and SLA is found over the western tropical Pacific.The comparison between WPD from SSM/I(S) and from ERA-Interim and NCEP, allows concluding that the trends computed using only the SSM/I(S) measurement points are substantially larger.

Interannual and decadal variability of the North Equatorial Undercurrents in an eddy-resolving ocean model

In the present study, the mean states of the North Equatorial Undercurrents (NEUCs) simulated in an eddy-resolving ocean model are evaluated, and the variability of the three NEUC jets is analyzed. This analysis provides a reference for future observations regarding how long the in-situ observations should be conducted to obtain a complete picture of NEUCs. We show that the primary features of the three eastward NEUC jets are fairly well reproduced by the high-resolution model of LICOM, such as the locations, tilting directions and widths of the three jets. However, the simulated NEUCs have slightly weaker magnitude and are located at shallower depths. In addition, two dominant time scales on interannual (2–7 years) and decadal (12–19 years) time scales for all three NEUC jets are found in a 39-year high-resolution LICOM simulation, although the latter is not statistically significant. The variation of these jets is related to the remarkable interannual and decadal variability in the Pacific Ocean. Our decomposition analysis indicates that both the small- and large-scale currents contribute to the total variation. Furthermore, the low-pass temporal filter of zonal velocity shows that the quasi-steady cross-basin NEUC jets can only emerge on time scales longer than the interannual periodicity.

Evolution of IOD-ENSO relationship at multiple time scales

Both El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are important indicators of the potential impact of climate at the global scale. The IOD-ENSO relationship at different timescales is temporally non-uniform, which is important to understand in order to evaluate its socioeconomic impacts. Here, we developed and applied a wavelet cross-correlation analysis approach for investigating the evolution of the IOD-ENSO relationship over a 150-year period. We found that the IOD-ENSO relationship was statistically significant at the dominant timescales of 1.5, 3, and 24 year, with the correlation degree varying with time. The hysteresis effect between IOD and ENSO and the evolution of their relationship obviously differ at the three dominant timescales. The positive (negative) IOD and El Nino (La Nina) events were mainly determined by the variability of IOD and ENSO at the timescale < 3 year. Strong positive IOD events in the September-October-November period would more likely be related to El Nino events 2 months later and La Nina events 14 months later, but negative IOD events would rarely co-occur with El Nino or La Nina events. The result achieved in this study can serve as a useful guide for the long-term forecast of IOD and ENSO.

Stripped-envelope supernova SN 2004dk is now interacting with hydrogen-rich circumstellar material

The dominant mechanism and time scales over which stripped-envelope supernovae (SNe) progenitor stars shed their hydrogen envelopes are uncertain. Observations of Type Ib and Ic SNe at late phases could reveal the optical signatures of interaction with distant circumstellar material (CSM) providing important clues on the origin of the necessary pre-SN mass loss. We report deep late-time optical spectroscopy of the Type Ib explosion SN 2004dk 4684 days (13 years) after discovery. Prominent intermediate-width H-alpha emission is detected, signaling that the SN blast wave has caught up with the hydrogen-rich CSM lost by the progenitor system. The line luminosity is the highest ever reported for a SN at this late stage. Prominent emission features of He, Fe, and Ca are also detected. The spectral characteristics are consistent with CSM energized by the forward shock, and resemble the late-time spectra of the persistently interacting Type IIn SNe 2005ip and 1988Z. We suggest that the onset of interaction with H-rich CSM was associated with a previously reported radio rebrightening at ~1700 days. The data indicate that the mode of pre-SN mass loss was a relatively slow dense wind that persisted millennia before the SN, followed by a short-lived Wolf-Rayet phase that preceded core-collapse and created a cavity within an extended distribution of CSM. We also present new spectra of SNe 2014C, PTF11iqb, and 2009ip, all of which also exhibit continued interaction with extended CSM distributions.

Diverse responses of vegetation growth to meteorological drought across climate zones and land biomes in northern China from 1981 to 2014

Improving our understanding of present and future impacts of drought on the vegetation in northern China is heightened by expectations that drought would increase its vulnerability and subsequently accelerate land degradation. The response of vegetation activity to drought and the underlying mechanisms are not well known. By using the third-generation Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation Evapotranspiration Index (SPEI), we investigated the relationship between NDVI and SPEI, across different climate regimes and land cover types, and determined the dominant time-scales at which different biome types respond to drought during the period of 1981–2014. Our results showed that biome response is coupled with drought trends in most regions of northern China. The highest correlation between monthly NDVI and SPEI at different time scales (1–48 months) assessed the impact of drought on vegetation, and the time scales resulting in the highest correlation were an effective indicator of drought resistance, which was related to the interactive roles of mean water balance and divergent drought survival traits and strategies. Diverse responses of vegetation to drought were critically dependent on characteristic drought time-scales and different growing environments. This study highlighted the most susceptible ecosystem types to drought occurrence under current climate, including temperate steppes, temperate desert steppes, warm shrubs and dry forests. Given that drought will be more frequent and severe under future climate scenarios, it may threaten the survival of mesic ecosystems, such as temperate meadows, alpine grasslands, dwarf shrubs, and moist forests not normally considered at drought risk. We propose that future research should be focused on arid and semi-arid ecosystems, where the strongest impact of drought on vegetation is occurring and the need for an early warning drought system is increasingly urgent.

Randomness representation of Turbulence in an alluvial channel affected by downward seepage

In the present work, experimental investigations have been done to study the flow turbulence in an alluvial channel with and without seepage. Turbulence is generally depicted as flow randomness or irregularity. The inherent randomness of turbulence in seepage affected channel has been quantified through Kolmogorov complexity (KC) and the Kolmogorov complexity spectrum. The measures have been used in analysis of the velocity time series data of alluvial channel to compare the degree of turbulence with and without seepage. The result concludes that the value of the KC is higher with seepage flow which indicates that higher level of randomness has been observed in seepage flow. Also, the frequency analysis of velocity time series was carried out with the help of Hilbert–Huang transform, which shows that dominant time scale for seepage flow is lower, indicates increased rate of sediment transport. Spectral analysis of velocity time series also suggests more randomness in channel with seepage.

Linear dynamical modes as new variables for data-driven ENSO forecast

A new data-driven model for analysis and prediction of spatially distributed time series is proposed. The model is based on a linear dynamical mode (LDM) decomposition of the observed data which is derived from a recently developed nonlinear dimensionality reduction approach. The key point of this approach is its ability to take into account simple dynamical properties of the observed system by means of revealing the system’s dominant time scales. The LDMs are used as new variables for empirical construction of a nonlinear stochastic evolution operator. The method is applied to the sea surface temperature anomaly field in the tropical belt where the El Nino Southern Oscillation (ENSO) is the main mode of variability. The advantage of LDMs versus traditionally used empirical orthogonal function decomposition is demonstrated for this data. Specifically, it is shown that the new model has a competitive ENSO forecast skill in comparison with the other existing ENSO models.

Time Scales and Sources of European Temperature Variability

AbstractSkillful predictions of continental climate would be of great practical benefit for society and stakeholders. It nevertheless remains fundamentally unresolved to what extent climate is predictable, for what features, at what time scales, and by which mechanisms. Here we identify the dominant time scales and sources of European surface air temperature (SAT) variability during the cold season using a coupled climate reanalysis, and a statistical method that estimates SAT variability due to atmospheric circulation anomalies. We find that eastern Europe is dominated by subdecadal SAT variability associated with the North Atlantic Oscillation, whereas interdecadal and multidecadal SAT variability over northern and southern Europe are thermodynamically driven by ocean temperature anomalies. Our results provide evidence that temperature anomalies in the North Atlantic Ocean are advected over land by the mean westerly winds and, hence, provide a mechanism through which ocean temperature controls the variability and provides predictability of European SAT.

Transport Time Scales in Soil Erosion Modeling

Core Ideas Erosion timescales inherent in the Hairsine–Rose soil erosion are exposed. Both fast and slow timescales are isolated and can be estimated a priori. The maximum sediment settling rate controls the possible range of timescales. In practice, the full range of erosion timescales are not seen in flume experiments. Unlike sediment transport in rivers, erosion of agricultural soil must overcome its cohesive strength to move soil particles into suspension. Soil particle size variability also leads to fall velocities covering many orders of magnitude, and hence to different suspended travel distances in overland flow. Consequently, there is a large range of inherent timescales involved in transport of eroded soil. For conditions where there is a constant rainfall rate and detachment is the dominant erosion mechanism, we use the Hairsine–Rose (HR) model to analyze these timescales, to determine their magnitude (bounds) and to provide simple approximations for them. We show that each particle size produces both fast and slow timescales. The fast timescale controls the rapid adjustment away from experimental initial conditions—this happens so quickly that it cannot be measured in practice. The slow timescales control the subsequent transition to steady state and are so large that true steady state is rarely achieved in laboratory experiments. Both the fastest and slowest timescales are governed by the largest particle size class. Physically, these correspond to the rate of vertical movement between suspension and the soil bed and the time to achieve steady state, respectively. For typical distributions of size classes, we also find that there is often a single dominant timescale that governs the growth in the total mass of sediment in the non‐cohesive deposited layer. This finding allows a considerable simplification of the HR model, leading to analytical expressions for the evolution of suspended and deposited layer concentrations.

Nonlinear reconstruction of global climate leading modes on decadal scales

A nonlinear decomposition method is applied to the analysis of global sea surface temperature (SST) time series in different epochs related to the Pacific Decadal Oscillation (PDO) since the end of 19th century to present time. This method allows one to extract an optimal (small) number of global nonlinear teleconnection patterns associated with distinct dominant time scales from the original high-dimensional spatially extended data set. In particular, it enables us to reveal ENSO teleconnection patterns corresponding to different PDO cycles during the last 145 years, to uncover four climate shifts connected with PDO phase changes and to reconstruct the corresponding global PDO patterns. We find that SST teleconnections between the ENSO region, extra-tropical Pacific regions and the Indian ocean became fundamentally nonlinear since the second half of 20th century.

Simulations of three natural decadal climate variability phenomena in CMIP5 experiments with the UKMO HadCM3, GFDL-CM2.1, NCAR-CCSM4, and MIROC5 global earth system models

The ability of four Earth System Models (ESMs) to simulate major attributes of sea-surface temperature (SST) manifestations of the Pacific Decadal Oscillation (PDO), the tropical Atlantic SST gradient (TAG) variability, and the West Pacific Warm Pool (WPWP) SST variability was assessed. Data from simulation experiments conducted under the CMIP5 with the CM2.1, HadCM3, MIROC5, and CCSM4 ESMs from 1861 to 2005 were used. A Multi-Model Ensemble was also formed by combining data from the four ESMs. Aerosol optical depths and solar radiation were specified in these experiments. The simulation of PDO spatial pattern, annual cycle, and preferred timescales is the closest to observed attributes in these ESMs. The simulated and observed TAG SST patterns are generally similar, but their average annual cycles are very different and simulated TAG variability does not have a preferred decadal timescale unlike observed variability. No one of the ESMs is able to simulate the WPWP SST pattern. Simulated and observed average annual cycles of the WPWP SST are similar, and the dominant timescale of WPWP variability is close to 8 years in all ESMs and observations. Simulation skills of the three phenomena fluctuate from decade to decade in all ESMs. Major volcanic eruptions substantially influence observed and simulated indices and simulation skills of the three phenomena. The mixing of net surface heat flux anomalies to 200 m depth in the tropical and mid-latitude Pacific, and the WPWP region causes a delayed and multiyear response of the PDO and WPWP indices to volcanic eruptions.

Spatio‐temporal pattern of meteorological droughts and its possible linkage with climate variability

ABSTRACTSpatial pattern of meteorological droughts is a critical element for investigating drought condition. Empirical orthogonal function (EOF) and rotated EOF (REOF) methods are widely used to discriminate dominant patterns. Previous works focused on case applications but left the associated physical meanings unexplored. This study employs the EOF, wavelet analysis, and stepwise regression methods to distinguish spatio‐temporal patterns of meteorological droughts with pattern interpretation. For this purpose, monthly precipitation data were used from 73 meteorological stations in the Poyang Lake basin of China for the period of 1960–2007. Standardized Precipitation Index (SPI) was applied to quantify meteorological droughts. Our results identified four leading EOF/REOF patterns at the basin scale. Seasonal SPI series showed more dominant periods than monthly SPI series, indicating periodic complexity of regional droughts. The dominant periods coincided with those of the EOF/REOF time coefficients. The four leading EOF/REOFs were significantly related to the dominant time scales of 2, 3, 6, 11, 16, and 17 years, except for the fifth EOF/REOF. Stepwise regression analysis further indicated that the four leading EOF/REOFs be likely the superposition of SPI variation from inter‐annual and inter‐decadal scales. The SPI series at different time scales (1–36 months) showed significant correlations with climate teleconnection modes, confirming the existence of identified spatio‐temporal pattern. The Niño3.4 and Southern Oscillation were the primary teleconnection modes that influenced the variability of meteorological droughts over the basin. The Pacific Decadal Oscillation and the North Atlantic Oscillation also contributed to the regional dry/wet alternation. The findings provide important implications for understanding spatial and temporal variation of regional droughts.

Transition Manifolds of Complex Metastable Systems

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Gas versus solid-phase deuterated chemistry: HDCO and D2CO in massive star-forming regions

The formation of deuterated molecules is favoured at low temperatures and high densities. Therefore, the deuteration fraction D$_{frac}$ is expected to be enhanced in cold, dense prestellar cores and to decrease after protostellar birth. Previous studies have shown that the deuterated forms of species such as N2H+ (formed in the gas phase) and CH3OH (formed on grain surfaces) can be used as evolutionary indicators and to constrain their dominant formation processes and time-scales. Formaldehyde (H2CO) and its deuterated forms can be produced both in the gas phase and on grain surfaces. However, the relative importance of these two chemical pathways is unclear. Comparison of the deuteration fraction of H2CO with respect to that of N2H+, NH3 and CH3OH can help us to understand its formation processes and time-scales. With the new SEPIA Band 5 receiver on APEX, we have observed the J=3-2 rotational lines of HDCO and D2CO at 193 GHz and 175 GHz toward three massive star forming regions hosting objects at different evolutionary stages: two High-mass Starless Cores (HMSC), two High-mass Protostellar Objects (HMPOs), and one Ultracompact HII region (UCHII). By using previously obtained H2CO J=3-2 data, the deuteration fractions HDCO/H2CO and D2CO/HDCO are estimated. Our observations show that singly-deuterated H2CO is detected toward all sources and that the deuteration fraction of H2CO increases from the HMSC to the HMPO phase and then sharply decreases in the latest evolutionary stage (UCHII). The doubly-deuterated form of H2CO is detected only in the earlier evolutionary stages with D2CO/H2CO showing a pattern that is qualitatively consistent with that of HDCO/H2CO, within current uncertainties. Our initial results show that H2CO may display a similar D$_{frac}$ pattern as that of CH3OH in massive young stellar objects. This finding suggests that solid state reactions dominate its formation.

Dominant Covarying Climate Signals in the Southern Ocean and Antarctic Sea Ice Influence during the Last Three Decades

A composite dataset (comprising geopotential height, sea surface temperature, zonal and meridional surface winds, precipitation, cloud cover, surface air temperature, latent plus sensible heat fluxes, and sea ice concentration) has been investigated with the aim of revealing the dominant time scales of variability from 1982 to 2013. Three covarying climate signals associated with variations in the sea ice distribution around Antarctica have been detected through the application of the multiple-taper method with singular value decomposition (MTM-SVD). Features of the established patterns of variation over the Southern Hemisphere extratropics have been identified in each of these three climate signals in the form of coupled or individual oscillations. The climate patterns considered here are the southern annular mode (SAM), the Pacific–South American (PSA) teleconnection, the semiannual oscillation (SAO), and the zonal wavenumber-3 (ZW3) mode. It is shown that most of the sea ice temporal variance is concentrated at the quasi-triennial scale resulting from the constructive superposition of the PSA and ZW3 patterns. In addition, the combination of the SAM and SAO patterns is found to promote the interannual sea ice variations underlying a general change in the Southern Ocean atmospheric and oceanic circulations. These two modes of variability are also found to be consistent with the occurrence of the positive SAM/negative PSA (SAM+/PSA−) or negative SAM/positive PSA (SAM−/PSA+) combinations, which could have favored the cooling of the sub-Antarctic region and important changes in the Antarctic sea ice distribution since 2000.

Statistical database analysis of the role of loop dynamics for protein-protein complex formation and allostery.

Protein loops show rich conformational dynamics properties on a wide range of timescales as they play an essential role for many cellular functions during protein-protein interactions and recognition processes. However, little is known about the detail behavior of loops upon protein binding including allostery. We report the loop motions and their dominant timescales for a library of 230 proteins that form protein-protein complexes using the ToeLoop predictor of loop dynamics. We applied the analysis to proteins in both their complex and free state and relate specific loop properties to their role in protein recognition. We observe a strong tendency of loops that move on relatively slow timescales of tens of ns to sub-μs to be directly involved in binding and recognition processes. Complex formation leads to a significant reduction in loop flexibility at the binding interface, but in a number of cases it can also trigger increased flexibility in distal loops in response to allosteric conformational changes. The importance of loop dynamics and allostery is highlighted by a case study of an antibody-antigen complex. Furthermore, we explored the relationship between loop dynamics and experimental binding affinities and found that a prevalence of high loop rigidity at the binding interface is an indicator of increased binding strength. http://spin.ccic.ohio-state.edu/index.php/toeloopppi. bruschweiler.1@osu.edu. Supplementary data are available at Bioinformatics online.

ACCRETION AND MAGNETIC RECONNECTION IN THE CLASSICAL T TAURI BINARY DQ TAU

ABSTRACT The theory of binary star formation predicts that close binaries (a &lt; 100 au) will experience periodic pulsed accretion events as streams of material form at the inner edge of a circumbinary disk (CBD), cross a dynamically cleared gap, and feed circumstellar disks or accrete directly onto the stars. The archetype for the pulsed accretion theory is the eccentric, short-period, classical T Tauri binary DQ Tau. Low-cadence (∼daily) broadband photometry has shown brightening events near most periastron passages, just as numerical simulations would predict for an eccentric binary. Magnetic reconnection events (flares) during the collision of stellar magnetospheres near periastron could, however, produce the same periodic, broadband behavior when observed at a one-day cadence. To reveal the dominant physical mechanism seen in DQ Tau’s low-cadence observations, we have obtained continuous, moderate-cadence, multiband photometry over 10 orbital periods, supplemented with 27 nights of minute-cadence photometry centered on four separate periastron passages. While both accretion and stellar flares are present, the dominant timescale and morphology of brightening events are characteristic of accretion. On average, the mass accretion rate increases by a factor of five near periastron, in good agreement with recent models. Large variability is observed in the morphology and amplitude of accretion events from orbit to orbit. We argue that this is due to the absence of stable circumstellar disks around each star, compounded by inhomogeneities at the inner edge of the CBD and within the accretion streams themselves. Quasiperiodic apastron accretion events are also observed, which are not predicted by binary accretion theory.

Structural relaxation, viscosity, and network connectivity in a hydrogen bonding liquid.

In liquids, the ability of neighboring molecules to rearrange and jostle past each other is directly related to viscosity, the property which describes the propensity to flow. The presence of hydrogen bonds (H-bonds) complicates the molecular scale picture of viscosity. H-Bonds are attractive, directional interactions between molecules which, in some cases, result in transient network structures. In this work, we use experimental and computational methods to demonstrate that the timescale of H-bond network reorganization is the dominant dynamical timescale associated with viscosity for the case of the model H-bonding liquid n-methylacetamide (NMA). This molecule is a peptide analog which forms a transient linear H-bond network. Individual H-bond lifetimes and dynamical fluctuations were observed on the timescale of 1.5 ps, while collective motions and the longest lived population of H-bond partner lifetimes were observed on the order of 20 ps, in agreement with the Maxwell relaxation time. This identifies a mechanism which may aid in understanding the emergence of various complex phenomena arising from transient molecular structures, with implications ranging from the internal dynamics of proteins, to the glass transition, to better understanding the origins of the unique properties of H-bonding liquids.

Dominant Time Scales of Potentially Predictable Precipitation Variations across the Continental United States

Abstract While low-frequency variations in precipitation amount, occurrence counts (hereafter “occurrence”), and intensity can take place on seasonal to multidecadal time scales, it is often unclear at which time scales these precipitation variations can be ascribed to potentially predictable, climate-induced changes versus simple, stochastic (i.e., random) precipitation event evolutions. This paper seeks to isolate the dominant time scales at which potentially predictable changes in observed precipitation characteristics occur over the continental United States and analyze sources of revealed potentially predictable precipitation variations for particular regions. The results highlight that at interannual time scales (here defined as those shorter than 7 years), the potential for predicting annual precipitation amounts tends to be higher than for annual event occurrence or intensity, with interannual potential predictability highest in both relatively dry and wet locations and lowest in transition regions. By contrast, at time scales greater than 7 years the potential for predicting annual event occurrence tends to be higher than amount or intensity, with &amp;gt;20-yr time scale potential predictability highest in relatively wet locations and lowest in relatively dry locations. To highlight the utility of this type of analysis, two robust signals are selected for further investigation, including 1) approximately 10-yr time scale variations in potentially predictable annual amounts over the northwestern United States and 2) 20–60-yr time scale variations in potentially predictable annual event occurrence over the southwestern United States. While mechanistic drivers for these observed variations are still being investigated, concurrent and precursor climate-state estimates in the atmosphere and ocean—principally over the Pacific sector—are provided, the monitoring of which may help realize the potential for predicting precipitation variations in these regions.