Annual Temperature Signal Research Articles

Opportunities to Improve Marine Power Cable Ratings with Ocean Bottom Temperature Models

Determining reliable cable ampacities for marine High Voltage Cables is currently the subject of significant industry and academic reassessment in order to optimize (maximizing load while maintaining safe operating temperatures) design and reduce costs. Ampacity models can be elaborate, and inaccuracies are increasingly predicated on the uncertainty in environmental inputs. A stark example is the role of ambient temperature at cable depth, which, due to the scale of cables and the inaccessibility of the seafloor, is commonly estimated at 15 °C. Oceanographic models incorporating ocean bottom temperature are increasingly available, and they achieve coverage and spatiotemporal resolutions for cable applications without the requirement for project specific measurements. Here, a rudimental validation of the AMM15 and AMM7 mean monthly ocean bottom temperature models for the NW European Shelf indicates encouraging accuracies (MBE ≤ 1.48 °C; RMSE ≤ 2.2 °C). A series of cable case studies are used to demonstrate that cable ratings can change between −4.1% and +7.8% relative to ratings based on a common static (15 °C) ambient temperature value. Consideration of such variations can result in both significant ratings (and hence capital expenditure and operating costs) gains and/or the avoidance of cable overheating. Consequently, validated modelled ocean bottom temperatures are deemed sufficiently accurate, providing incomparable coverage and spatiotemporal resolutions of the whole annual temperature signal, thereby facilitating much more robust ambient temperatures and drastically improving ampacity estimates.

Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams

Abstract. In mountain headwater streams, the quality and resilience of summer cold-water habitat is generally regulated by stream discharge, longitudinal stream channel connectivity and groundwater exchange. These critical hydrologic processes are thought to be influenced by the stream corridor bedrock contact depth (sediment thickness), a parameter often inferred from sparse hillslope borehole information, piezometer refusal and remotely sensed data. To investigate how local bedrock depth might control summer stream temperature and channel disconnection (dewatering) patterns, we measured stream corridor bedrock depth by collecting and interpreting 191 passive seismic datasets along eight headwater streams in Shenandoah National Park (Virginia, USA). In addition, we used multi-year stream temperature and streamflow records to calculate several baseflow-related metrics along and among the study streams. Finally, comprehensive visual surveys of stream channel dewatering were conducted in 2016, 2019 and 2021 during summer low flow conditions (124 total km of stream length). We found that measured bedrock depths along the study streams were not well-characterized by soils maps or an existing global-scale geologic dataset where the latter overpredicted measured depths by 12.2 m (mean) or approximately four times the average bedrock depth of 2.9 m. Half of the eight study stream corridors had an average bedrock depth of less than 2 m. Of the eight study streams, Staunton River had the deepest average bedrock depth (3.4 m), the coldest summer temperature profiles and substantially higher summer baseflow indices compared to the other study steams. Staunton River also exhibited paired air and water annual temperature signals suggesting deeper groundwater influence, and the stream channel did not dewater in lower sections during any baseflow survey. In contrast, Paine Run and Piney River did show pronounced, patchy channel dewatering, with Paine Run having dozens of discrete dry channel sections ranging from 1 to greater than 300 m in length. Stream dewatering patterns were apparently influenced by a combination of discrete deep bedrock (20+ m) features and more subtle sediment thickness variation (1–4 m) depending on local stream valley hydrogeology. In combination, these unique datasets show the first large-scale empirical support for existing conceptual models of headwater stream disconnection based on spatially variable underflow capacity and shallow groundwater supply.

Agreement of Analytical and Simulation‐Based Estimates of the Required Land Depth in Climate Models

AbstractPrevious analytical and simulation‐based analyses suggest that deeper land surface models are needed to realistically simulate the terrestrial thermal state in climate models, with implications for land‐atmosphere interactions. Analytical approaches mainly focused on the subsurface propagation of harmonics such as the annual temperature signal, and a direct comparison with climate‐change model output has been elusive. This study addresses the propagation of a harmonic pulse fitted to represent the timescale and amplitude of anthropogenic warming. Its comparison to land model simulations with stepwise increased bottom boundary depth leads to an agreement between the simulation‐based and analytical frameworks for long‐term climate trends. Any depth increase gradually decreases the relative error in the subsurface thermodynamics, and a minimum depth of 170 m is recommended to simulate the ground climate adequately. The approach provides an accurate estimate of the required land‐model depth for climate‐change simulations and assesses the relative bias in insufficiently deep land models.

Millennial‐scale deglaciation across the European Alps at the transition between the Younger Dryas and the Early Holocene – evidence from a new cosmogenic nuclide chronology

Reconstructing the spatial and temporal response of mountain glaciers to rapid climate change in the past provides access to the effects of current climate change. Yet, the spatial and temporal variability of past glacier fluctuations is not fully understood. In this study, we focus on the timing of glacier fluctuations in the European Alps during the Younger Dryas/Early Holocene (YD/EH) transition. In an effort to elucidate whether glacier fluctuations were synchronous during this period, we present a new chronology of the Alpine Talèfre glacier, based on 14 new 10Be ages of moraines and roches moutonnées. The retreat of Talèfre glacier was initiated during the mid‐YD (~12.4 ka), then it experienced a gradual retreat punctuated by at least three oscillations until ∼11 ka before shrinking substantially within its Little Ice Age limits (13th−19th centuries). Comparison of our findings with published glacier chronologies in the Alpine region highlights broadly synchronous behaviour of glaciers across the Alps between 12 and 10 ka. The coeval glacier fluctuations at a regional scale suggest that common regional climate conditions had a major impact on Alpine glacier variations during the YD/EH transition. The similarity of glacier behaviour and independent temperature records in both the Alpine region and the northern high latitudes suggests a teleconnection between these regions, but differences in the amplitude of the mean annual temperature signals relative to summer temperature indicate pronounced changes in seasonality between the YD and the EH.

A Fourier Spectral Method to Measure the Thermal Diffusivity of Soil

Abstract It is well established that amplitude decays and phase shifts as a function of depth, frequency, and thermal diffusivity when a periodic surface temperature signal conducts into the ground. In historical practice, this principle has often been employed to estimate soil thermal diffusivity using observations of the dominant diurnal and annual temperature signals. We describe and demonstrate a method to infer thermal diffusivity over a broad bandwidth in the frequency domain using high fidelity time-series ground temperature records. We draw information from thermal signals generated by meteorological events over weeks and months, as well as the dominant diurnal signal. Both the decay in amplitude and shift in phase of each frequency band contribute points to plots that define linear functions relative to a parameter that incorporates frequency and depth. Linear regression through the points gives the magnitude and uncertainty of the slope of the function, where the slope is equal to the inverse square root of the average thermal diffusivity over the sampled time-period and depth interval. This allows statistical quantification of the uncertainty in the thermal diffusivity estimate. Furthermore, our method delineates depth intervals where nonconductive processes significantly affect heat transfer. Examples are presented for a dry desert soil in South Australia and the floor of a tropical alpine forest in Mexico.

Paired air-water annual temperature patterns reveal hydrogeological controls on stream thermal regimes at watershed to continental scales

Despite decades of research into air and stream temperature dynamics, paired air-water annual temperature signals have been underutilized to characterize watershed processes. Annual stream temperature dynamics are useful in classifying fundamental thermal regimes and can enhance process-based interpretation of stream temperature controls, including deep and shallow groundwater discharge, when paired with air signals. In this study, we investigated multi-scale variability in annual paired air-water temperature patterns using sine-wave linear regressions of multi-year daily temperature data from streams of various sizes. A total of 311 sites from two spatially intensive regional datasets (Shenandoah National Park and Olympic Experimental State Forest) and a spatially extensive national dataset spanning the contiguous United States (U.S. Geological Survey gages) were evaluated. We calculated three annual air-water thermal metrics (mean ratio, phase lag, and amplitude ratio) to deduce the influence of groundwater and other watershed processes on stream thermal regimes at multiple spatial scales. Site-specific values of the three annual air-water thermal metrics ranged from 0.69 to 5.29 (mean ratio), −9 to 40 days (phase lag), and 0.29 to 1.12 (amplitude ratio). Regional patterns in the annual thermal metrics revealed persistent yet spatially variable influences of shallow groundwater discharge and high levels of thermal variability within watersheds, indicating the importance of local hydrogeological controls on stream temperature. Furthermore, annual thermal metric patterns from the regional datasets were generally concordant with the national dataset suggesting the utility of these annual thermal metrics for analysis at multiple scales. Analysis of the national dataset showed that previously defined thermal regimes based on water temperature alone could be further refined using air-water metrics and these metrics were related to physiographic watershed characteristics such as contributing area, elevation, and slope. This research demonstrates the importance of spatial scale and heterogeneity for inferring hydrological process in streams and provides guidance for the interpretation of annual air-water temperature metrics that can be efficiently applied to the growing database of multi-year temperature records. Results from this research can aid in the prediction of future thermal habitat suitability for coldwater-adapted species at ecologically and management-relevant spatial scales with readily available data.

Inferring watershed hydraulics and cold-water habitat persistence using multi-year air and stream temperature signals

Streams strongly influenced by groundwater discharge may serve as “climate refugia” for sensitive species in regions of increasingly marginal thermal conditions. The main goal of this study is to develop paired air and stream water annual temperature signal analysis techniques to elucidate the relative groundwater contribution to stream water and the effective groundwater flowpath depth. Groundwater discharge to streams attenuates surface water temperature signals, and this attenuation can be diagnostic of groundwater gaining systems. Additionally, discharge from shallow groundwater flowpaths can theoretically transfer lagged annual temperature signals from aquifer to stream water. Here we explore this concept using multi-year temperature records from 120 stream sites located across 18 mountain watersheds of Shenandoah National Park, VA, USA and a coastal watershed in Massachusetts, USA. Both areas constitute important cold-water habitat for native brook trout (Salvelinus fontinalis). Observed annual temperature signals indicate a dominance of shallow groundwater discharge to streams in the National Park, in contrast to the coastal watershed that has strong, apparently deeper, groundwater influence. The average phase lag from air to stream signals in Shenandoah National Park is 11 d; however, extended lags of approximately 1 month were observed in a subset of streams. In contrast, the coastal stream has pronounced attenuation of annual temperature signals without notable phase lag. To better understand these observed differences in signal characteristics, analytical and numerical models are used to quantify mixing of the annual temperature signals of surface and groundwater. Simulations using a total heat budget numerical model indicate groundwater-induced annual temperature signal phase lags are likely to show greater downstream propagation than the related signal amplitude attenuation. The measurement of multi-seasonal paired air and water temperatures offers great promise toward understanding catchment processes and informing current cold-water habitat management at ecologically-relevant scales.

Reliability of temperature signal in various climate indicators from northern Europe.

We collected relevant observational and measured annual-resolution time series dealing with climate in northern Europe, focusing in Finland. We analysed these series for the reliability of their temperature signal at annual and seasonal resolutions. Importantly, we analysed all of the indicators within the same statistical framework, which allows for their meaningful comparison. In this framework, we employed a cross-validation procedure designed to reduce the adverse effects of estimation bias that may inflate the reliability of various temperature indicators, especially when several indicators are used in a multiple regression model. In our data sets, timing of phenological observations and ice break-up were connected with spring, tree ring characteristics (width, density, carbon isotopic composition) with summer and ice formation with autumn temperatures. Baltic Sea ice extent and the duration of ice cover in different watercourses were good indicators of winter temperatures. Using combinations of various temperature indicator series resulted in reliable temperature signals for each of the four seasons, as well as a reliable annual temperature signal. The results hence demonstrated that we can obtain reliable temperature information over different seasons, using a careful selection of indicators, combining the results with regression analysis, and by determining the reliability of the obtained indicator.

Deriving temperature estimates from Southern Hemisphere leaves

The percentage of woody dicots with entire-margined leaves in a flora is known to be positively correlated with mean annual temperature (Leaf Margin Analysis — LMA) but this relationship is not globally uniform. In particular the floras of Australia and New Zealand have been regarded as displaying a different physiognomic relationship to climate than floras seen in the Northern Hemisphere. This difference is more marked in New Zealand where the LMA relationship appears entirely absent. Here we amass data for both Northern and Southern hemispheres using standard protocols and show that regional variations in the leaf margin–mean annual temperature relationship are real but become less significant when other characters are included. Even New Zealand falls into line and most of the mean annual temperature signal in New Zealand floras is encoded in non-margin features. We introduce a new CLAMP (Climate Leaf Analysis Multivariate Program) calibration dataset for the Southern Hemisphere, comprising leaf physiognomic data from Argentina, Bolivia, South Africa, Australia, New Zealand and other Pacific Islands that offers comparable precision for climate prediction to similar datasets derived from the Northern Hemisphere.

Air‐ground temperature coupling and subsurface propagation of annual temperature signals

Borehole‐based reconstructions of ground surface temperature (GST) have been widely used as indicators of paleoclimate. These reconstructions assume that heat transport within the subsurface is conductive. Climatic interpretations of GST reconstructions also assume that GST is strongly coupled to surface air temperature (SAT) on timescales of decades and longer. We examine these two assumptions using records of SAT and subsurface temperature time series from Fargo, North Dakota; Prague, Czech Republic; Cape Henlopen State Park, Delaware; and Cape Hatteras National Seashore, North Carolina. The characteristics of downward propagating annual temperature signals at each site clearly indicate that heat transport can be described as one‐dimensional conduction in a homogeneous medium. Extrapolations of subsurface observations to the ground surface yield estimates of annual GST signals and allow comparisons to annual SAT signals. All annual GST signals are modestly attenuated and negligibly phase shifted relative to SAT. The four sites collectively demonstrate that differences between annual GST and SAT signals arise in both summer and winter seasons, in amounts dependent on the climatic setting of each site.

Changes in Antarctic temperature, wind and precipitation in response to the Antarctic Oscillation

AbstractOutput of a 14 year integration with a high-resolution (55 km ×55 km) regional atmospheric climate model is used to study the response of Antarctic near-surface climate to the Antarctic Oscillation (AAO), the periodical strengthening and weakening of the circumpolar vortex in the Southern Hemisphere. In spite of the relatively short record, wind, temperature and precipitation show widespread and significant AAO-related signals. When the vortex is strong (high AAO index), northwesterly flow anomalies cause warming over the Antarctic Peninsula (AP) and adjacent regions in West Antarctica and the Weddell Sea. In contrast, cooling occurs in East Antarctica, the eastern Ross Ice Shelf and parts of Marie Byrd Land. Most of the annual temperature signal stems from the months March–August. The spatial distribution of the precipitation response to changes in the AAO does not mirror temperature changes but is in first order determined by the direction of flow anomalies with respect to the Antarctic topography. When the vortex is strong (high AAO index), the western AP becomes wetter, while the Ross Ice Shelf, parts of West Antarctica and the Lambert Glacier basin, East Antarctica, become drier.

Conduction‐dominated heat transport of the annual temperature signal in soil

Conductive heat transport of temperature signals into the subsurface is a central assumption of ground surface temperature (GST) reconstructions derived from present‐day temperatures in deep boreholes. Here we test this assumption and its implications for annual relationships between GST and surface air temperature (SAT) by analyzing two decades of shallow soil temperature (0.01–11.7 m) and SAT time series measured at Fargo, North Dakota. We spectrally decompose each of these temperature time series to determine the amplitude and phase of the annual signal at each depth. Conductive heat transport of a harmonic temperature signal in a homogeneous medium is characterized theoretically by exponential amplitude attenuation and linear phase shift with depth. We show that transport of the annual signal in the soil at Fargo follows these theoretical characterizations of conduction closely: the depth dependence of both the natural logarithm of the amplitude and the phase shift are highly linear. Interval wave velocities and thermal diffusivities calculated as functions of depth suggest a diffusivity gradient in the upper meter of the soil. We estimate the annual signal at the ground surface by extrapolating amplitude and phase shift regression lines upward to the surface. We compare this estimate of the annual signal at the ground surface to the annual signal contained in the SAT and show the ground surface signal to be attenuated ∼20% and negligibly phase shifted relative to the SAT.