Depth Time Series Research Articles

Predicting Raw Milk Price Based on Depth Time Series Features for Consumer Behavior Analysis

The dairy industry has a long supply chain that involves dairy farmers, enterprises, consumers, and the government. The stable growth of consumer groups is the driving force for the sustainable development of the dairy industry. However, in recent years, sustainable development of the dairy industry has faced great challenges due to the constant changes in the global climate environment and the increasing uncertainty of the international economic environment. Therefore, it is essential to systematically monitor and accurately predict the consumption market of dairy products to ensure that the government, dairy enterprises, and dairy farmers can share information in a timely manner and take effective measures to cope with the changes in the dairy consumption market without disturbing the normal pricing mechanism of the dairy market. The purpose of the conducted research is to systematically monitor and accurately predict the dairy product consumption market while consistently delivering dependable forecasts of consumer behavior in the dairy industry. In this paper, we proposed a raw milk price prediction framework (RMP-CPR) to analyze consumer behavior based on the relationship between milk price and dairy consumption. This study concludes that dairy consumption behavior can be predicted accurately by predicting the price of raw milk based on the proposed framework (RMP-CPR). Our research explores a new angle for studying consumer behavior. The results can assist dairy enterprises in developing accurate marketing strategies based on the forecast results of dairy consumption, thereby enhancing their competitiveness in the market. Policymakers can also use the forecast results of the development trend of the dairy consumption market to adjust corresponding policies in a timely manner. This can help to balance the interests among consumers, dairy enterprises, dairy farmers, and other relevant stakeholders and effectively maintain the sustainable and healthy development of the dairy market.

Traveling Planetary-scale Waves Cause Cloud Variability on Tidally Locked Aquaplanets

Cloud cover at the planetary limb of water-rich Earth-like planets is likely to weaken chemical signatures in transmission spectra, impeding attempts to characterize these atmospheres. However, based on observations of Earth and Solar System worlds, exoplanets with atmospheres should have both short-term weather and long-term climate variability, implying that cloud cover may be less during some observing periods. We identify and describe a mechanism driving periodic clear sky events at the terminators in simulations of tidally locked Earth-like planets. A feedback between dayside cloud–radiative effects, incoming stellar radiation and heating, and the dynamical state of the atmosphere, especially the zonal wavenumber 1 Rossby wave identified in past work on tidally locked planets, leads to oscillations in Rossby wave phase speeds and in the position of Rossby gyres, and this results in advection of clouds to or away from the planet’s eastern terminator. We study this oscillation in simulations of Proxima Centauri b, TRAPPIST-1e, and rapidly rotating versions of these worlds located at the inner edge of their stars’ habitable zones. We simulate time series of the transit depths of the 1.4 μm water feature and 2.7 μm carbon dioxide feature. The impact of atmospheric variability on the transmission spectra is sensitive to the structure of the dayside cloud cover and the location of the Rossby gyres, but none of our simulations have variability significant enough to be detectable with current methods.

Assessing 1D Hydrodynamic Modeling of Júcar River Behavior in Mancha Oriental Aquifer Domain (SE Spain)

In times of population growth, climate change, and increasing water scarcity around the world, it is important to take an objective look at water, a fundamental resource for life. Hydrodynamic modeling makes possible the research of different aspects of the water cycle and the evaluation of different hydrological and hydrogeological forecasting scenarios in the short and medium terms. The present research offers a more detailed scope at the hydrodynamic processes and their space-time distributions on a UE pilot in the Júcar River Basin, providing a calibrated and validated hydrodynamic model of 121 km river reach for 45 years period (1974–2019) on a daily scale. The obtained information is about discharge and water depths along the Júcar River reach within the hydrogeological boundaries of the Mancha Oriental Aquifer (MOA). The river–aquifer interactions have been represented as dynamic boundary conditions expressed as a difference between observed discharges measured in 3 gauging stations. The obtained calibration error performance evaluations of observed and simulated values cover two periods, according to observed data availability from gauging station 08036 with resulting R2 for both discharges and water depths over 0.96. The model validation results were obtained for a different gauge 08132 and the determination coefficients R2 also perform very well with value of 0.90. The model developed might be useful for decision making in water resources management and can be used to generate simulated time series of water depths, levels, discharges, and velocities in reaches where gauging measurements are not available with a desired space-time resolution (from meter/second to kilometer/month). Estimation of critical discharge value (1.973 m3s−1) for system equilibrium, based on the balance between losing and gaining sub-reaches of the river, is also made with a statistical significance at 95% for hydrologic years 2007–2010, period influenced by restrictions in groundwater withdrawals. The results of the present research are important for the proper and objective management of the scarce water resources on a watershed scale in Júcar River Basin, a complex case study representing semiarid climate, growing anthropogenic pressures, and complex river–aquifer interactions. The used approach of dynamic representation of the river–aquifer interactions as distributed source boundary condition in the one-dimensional hydrodynamic model might be applied in another study case on similar scale.

Gradual versus episodic lateral saltmarsh cliff erosion: Evidence from Terrestrial Laser Scans (TLS) and Surface Elevation Dynamics (SED) sensors

As lateral erosion can threaten valuable saltmarsh habitats and their capacity to protect the hinterland from waves and floods, there is a need to understand the mechanisms of erosion. We monitored lateral saltmarsh erosion at high spatiotemporal resolution during a 2.5 year period. We performed terrestrial laser scans (TLS) with centimetric spatial resolution, ca monthly, as well as before and after 2 wind events to assess morphological change of a saltmarsh cliff (<0.8 m in height), and deployed surface elevation dynamics (SED) sensors at 3 locations to obtain daily measurements of the cliff edge position with 2 mm resolution. This was complemented by wind data, and a pressure transducer on the mudflat to obtain time-series of local inundation duration, water depth, wave height, period, power and energy. TLS shows gradual lateral erosion of the marsh edge and surface, and occasional local slumping, with substantial local variation. SED sensor data also reveal that lateral erosion was mostly continuous, with episodes with stronger and weaker local erosion, at all 3 locations, often correlated in space. Correlations between changes in total marsh area and sediment volume of the mudflat-saltmarsh interface from TLS with particularly inundation duration and wind velocity were discussed. At plot level, correlations were not consistent; correlations between the local lateral erosion rates and hydrodynamics/winds were not significant. Results emphasize the importance of common low magnitude events for long-term lateral erosion.

A Novel Groundwater Burial Depth Prediction Model Based on Two-Stage Modal Decomposition and Deep Learning.

The variability of groundwater burial depths is critical to regional water management. In order to reduce the impact of high-frequency eigenmodal functions (IMF) generated by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) on the prediction results, variational modal decomposition (VMD) is performed on the high frequency IMF components after the primary modal decomposition. A convolutional neural network-gated recurrent unit prediction model (CNN-GRU) is proposed to address the shortcomings of traditional machine learning which cannot handle correlation information and temporal correlation between time series. The CNN-GRU model can extract the implicit features of the coupling relationship between groundwater burial depth and time series and further predict the groundwater burial depth time series. By comparing the prediction results with GRU, CEEMDAN-GRU, and CEEMDAN-CNN-GRU models, we found that the CEEMDAN-VMD-CNN-GRU prediction model outperformed the other prediction models, with a prediction accuracy of 94.29%, good prediction results, and high model confidence.

A stochastic approach to simulate realistic continuous snow depth time series

We propose a stochastic approach for simulation of realistic continuous snow depth time series using a snow depth estimation model and a stochastic weather generation model. The snow depth estimation model consists of three steps: defining the precipitation type, estimating the snow ratio, and estimating the decreased snow depth. First, air temperature and relative humidity are used as indices to determine the type of precipitation when precipitation occurs. When the type is identified as snow, the snow ratio is estimated, converting the precipitation depth into depth of fresh snow. Here, the snow ratio is estimated through sigmoidal relationship with the air temperature. Lastly, the amount of decreased snow depth was estimated using a novel temperature index snowmelt equation that can consider depth-dependent melting of snowpack. The model was applied to four meteorological stations of Korea and yielded high Nash Sutcliffe efficiency values which ranged between 0.745 and 0.875 for calibration, and ranged between 0.432 and 0.753 for validation. This calibrated snow depth estimation model was then applied to synthetic weather data (precipitation, temperature, and relative humidity) that was generated by stochastic weather generation model to simulate continuous snow depth time series. The simulated snow depth data accurately reproduced standard and extreme value statistics of the observed data, the latter of which were consistent with the current Korean Building Code. This model can be widely used not only in the field of snow related risk analysis, but also in data simulation for ungauged areas and future trend study using the climate projection.

Coupled Hydro-Climatic Signals in the Radial Growth of Oaks Benefitting from Groundwater Availability

Lowland forests benefiting from groundwater availability are important ecosystems in Central Europe, both from ecological and economic perspectives. Besides a great reduction in their extent in the historical times and further shifts in the land use and water management regimes intensified during the industrial era, continuing changes in the groundwater and overall hydro-climatic conditions can pose significant challenges to them. Although tree-ring analyses serve as widely used tools to assess the climatic impact on tree growth and vitality, few studies have attempted to investigate the effects of subsurface hydrology on interannual fluctuations in xylem production. In this study, we compared the tree-ring width series of pedunculate oak (Quercus robur L.) from a forested area in southwestern Hungary with the time series of monthly groundwater depth and climatic variables over the period of 1920–2017 with a specific focus on 1961–2017. The radial growth of the studied trees showed the strongest relationship with late winter and early spring groundwater and drought conditions preceding the growing season, differing from the commonly reported climatic signals marked by early summer meteorological conditions of the vegetation season. The results suggest that the groundwater recharge during the dormant period preceding the vegetation season and the groundwater levels in early spring were among the key limiting factors on tree growth in the study area. In the growing years starting with a sufficiently high groundwater table, even scarce summer precipitation did not seem to limit radial growth drastically. However, unfavorable shifts in climatic conditions during the past few decades and the associated uncertainties in the future groundwater regime imply that additional active measures aimed at maintaining and restoring groundwater conditions may well be highly beneficial for sustaining groundwater-dependent forest ecosystems and their productivity.

Performance Evaluation of Force Transducer for the Observation of Sediment Entrainment in Rapidly Varied Flows

Abstract Direct measurement of forces within the rough bed layer have been limited by previous spatial-averaging shear force studies. A highly sensitive force transducer assembled with a target sphere was used to measure and record the instantaneous three-dimensional forces of sediment at incipient motion. In the current study, a laser Doppler anemometer, ultrasonic displacement meter, and a force transducer accompanied by video recordings were used to experimentally investigate the incipient motion of sediment. The developed experimental setup have the potential to resolve and improve fundamental classical hypotheses regarding the incipient sediment motion. Experiments conducted in a large recirculating flume verified that the force transducer detects instantaneous forces at incipient motion under varies hydrodynamic conditions. Depth time series, instantaneous horizontal, vertical, and lateral forces are presented for dam-break and tidal breaking bores. Evidence suggests that the uplift vertical force plays an important role in destabilizing and in the incipient motion of particles. A sudden decrease in horizontal force was observed in tidal breaking bore due to flow reversal; however, a rapid rise was observed due to initial impact of dam-break bore. Bore velocity seems to have a larger effect on dam-break force than bore height. Furthermore, lateral force has the least influence during tidal breaking bore, while sediment particles are subjected to additional lateral force during dam-break bore.

Empirically testing the influence of light regime on diel activity patterns in a marine predator reveals complex interacting factors shaping behaviour

Abstract Diel cycles in marine predator diving behaviour centre around the light‐mediated diel vertical migration (DVM) of prey, and are considered critical for optimizing foraging and limiting competition across global seascapes. Yet, our understanding of predator diel behaviour is based primarily on examining relative depth usage between constant day/night cycles with no formal investigation of how varying light regimes interact with abiotic factors to shape diel activity. The extreme seasonal light regimes (midnight sun, polar night, day/night cycle) in the Arctic provide a unique natural experimental setting to empirically investigate the occurrence and intensity of diel behaviour in marine predators relative to changing light levels while concomitantly assessing interacting abiotic factors. Depth time series data from satellite‐linked tags deployed on six beluga whales (Delphinapterus leucas) for up to 12 months were used to quantify diel behaviour by calculating dissimilarity in time‐at‐depth between periods of low and high solar altitude on each day. Generalized additive mixed effects models were used to examine the influence of hours of daylight across extreme light cycles, coupled with bathymetry and sea ice concentration; focal diel patterns were further examined relative to the thermal structure of the water column. As predicted, belugas exhibited cathemerality during the midnight sun, and initiated diel behaviour with the onset of the fall day/night cycle, with a marked increase in its intensity with the progression to equal day/night length. Occurrence of diel patterns, however, was complex; ceasing in regions with seafloor depths &lt;700 m, and occurring with greatest intensity when the water column was thermally homogeneous within the upper 150 m. Through empirical investigation, this study demonstrates that the onset of day/night light cycles and presumably associated prey DVM can modulate predator diel dive behaviour under certain circumstances, but highlights how the complex interaction of abiotic factors with light regime shape dynamic spatiotemporal patterns. These findings, building on a body of recent work, emphasize that the traditional view of the ubiquitous occurrence of diel behaviour tied to DVM at the base of the food web oversimplifies vertical predator–prey interactions, identifying the need for more structured investigation. Read the free Plain Language Summary for this article on the Journal blog.

Pygmy Blue Whale Diving Behaviour Reflects Song Structure

Passive acoustic monitoring is increasingly employed to monitor whales, their population size, habitat usage, and behaviour. However, in the case of the eastern Indian Ocean pygmy blue whale (EIOPB whale), its applicability is limited by our lack of understanding of the behavioural context of sound production. This study explored the context of singing behaviour using a 7.6-day biotelemetry dataset from a single EIOPB whale moving north from 31.5° S to 28.5° S along the Western Australian coast and a simultaneously collected, but separate, acoustic recording. Diving behaviour was classified using an automated classification schema. Singing was identified in the depth, pitch, and fluking time series of the dive profile. The EIOPB whale sang profusely as it migrated, spending more time singing during the day (76.8%) than at night (64.9%), and most during twilight periods (83.3%). The EIOPB whale almost exclusively produced the three-unit (P3) song while milling. It sang the two-unit (P2) song in similar proportions to the P3 song while travelling, except at night when P3 was sung 2.7 times more than P2. A correlation between singing depth, migration duration, and water temperature provides a biological basis to explain depth preferences for sound production, which may contribute to the cause of intra- and inter-annual sound frequency trends.

Australian wildfires cause the largest stratospheric warming since Pinatubo and extends the lifetime of the Antarctic ozone hole

Global mean lower stratosphere temperatures rose abruptly in January 2020 reaching values not experienced since the early 1990s. Anomalously high lower stratospheric temperatures were recorded for 4 months at highly statistically significant levels. Here, we use a combination of satellite and surface-based remote sensing observations to derive a time-series of stratospheric biomass burning aerosol optical depths originating from intense SouthEastern Australian wildfires and use these aerosol optical depths in a state-of-the-art climate model. We show that the S.E. Australian wildfires are the cause of this lower stratospheric warming. We also investigate the radiatively-driven dynamical response to the observed stratospheric ozone perturbation and find a significant strengthening of the springtime Antarctic polar vortex suggesting that biomass burning aerosols play a significant role in the observed anomalous longevity of the ozone hole in 2020.

Volcanic stratospheric sulfur injections and aerosol optical depth during the Holocene (past 11 500 years) from a bipolar ice-core array

Abstract. The injection of sulfur into the stratosphere by volcanic eruptions is the dominant driver of natural climate variability on interannual to multidecadal timescales. Based on a set of continuous sulfate and sulfur records from a suite of ice cores from Greenland and Antarctica, the HolVol v.1.0 database includes estimates of the magnitudes and approximate source latitudes of major volcanic stratospheric sulfur injection (VSSI) events for the Holocene (from 9500 BCE or 11 500 years BP to 1900 CE), constituting an extension of the previous record by 7000 years. The database incorporates new-generation ice-core aerosol records with a sub-annual temporal resolution and a demonstrated sub-decadal dating accuracy and precision. By tightly aligning and stacking the ice-core records on the WD2014 chronology from Antarctica, we resolve long-standing inconsistencies in the dating of ancient volcanic eruptions that arise from biased (i.e., dated too old) ice-core chronologies over the Holocene for Greenland. We reconstruct a total of 850 volcanic eruptions with injections in excess of 1 teragram of sulfur (Tg S); of these eruptions, 329 (39 %) are located in the low latitudes with bipolar sulfate deposition, 426 (50 %) are located in the Northern Hemisphere extratropics (NHET) and 88 (10 %) are located in the Southern Hemisphere extratropics (SHET). The spatial distribution of the reconstructed eruption locations is in agreement with prior reconstructions for the past 2500 years. In total, these eruptions injected 7410 Tg S into the stratosphere: 70 % from tropical eruptions and 25 % from NH extratropical eruptions. A long-term latitudinally and monthly resolved stratospheric aerosol optical depth (SAOD) time series is reconstructed from the HolVol VSSI estimates, representing the first Holocene-scale reconstruction constrained by Greenland and Antarctica ice cores. These new long-term reconstructions of past VSSI and SAOD variability confirm evidence from regional volcanic eruption chronologies (e.g., from Iceland) in showing that the Early Holocene (9500–7000 BCE) experienced a higher number of volcanic eruptions (+16 %) and cumulative VSSI (+86 %) compared with the past 2500 years. This increase coincides with the rapid retreat of ice sheets during deglaciation, providing context for potential future increases in volcanic activity in regions under projected glacier melting in the 21st century. The reconstructed VSSI and SAOD data are available at https://doi.org/10.1594/PANGAEA.928646 (Sigl et al., 2021).

A quantile‐based approach to improve homogenization of snow depth time series

AbstractAustrian observations of snow depth date back to 1895 and are thus among the longest available quantitative snow information from hydrometeorological networks worldwide. It is well known that such long‐term observations are prone to inhomogeneities, which may not only affect climatologies and trends, but derived products used in research or practice. While the reliability of available methods for detecting breaks in snow time series has been shown before and could also be confirmed by our work, we focused on improving the adjustment method. Conventional methods often refer to the median of difference or quotient series (INTERP), whereas our proposed method also uses a quantile‐wise adjustment (InterpQM), which is useful to minimize a bias on the tails of the frequency distribution. We demonstrated the success of the new method by using Swiss parallel snow depth observations. Errors of the analysed indicators could be reduced in 68% of the cases when compared with INTERP. The results were best for large snow depths, being up to 19% better. Overall, InterpQM was better in 75% of validation cases for the daily large, 72% of all observations and 56% of mean seasonal snow depth cases. We describe the performed homogenization procedure in detail, including quality control, gap filling, homogeneity testing, break detection, calculation of and improvements to the adjustment method. Our results show that snow depth time series generally have a lower number of breaks compared with station data of other climate variables. This underlines their high quality, even if measuring snow presents challenges. Using Austrian snow depth series as an example, the effects of the new adjustment method on trends were analysed using the Mann–Kendall and Sen's Slope. Homogenization may have a significant effect on derived trends: Two of the six adjusted series were changed from nonsignificant to significant and one vice versa.

Comparison of CML Rainfall Data against Rain Gauges and Disdrometers in a Mountainous Environment.

Despite the several sources of inaccuracy, commercial microwave links (CML) have been recently exploited to estimate the average rainfall intensity along the radio path from signal attenuation. Validating these measurements against “ground truth” from conventional rainfall sensors, as rain gauges, is a challenging issue due to the different spatial sampling involved. Here, we assess the performance of a network of CML as opportunistic rainfall sensors in a challenging mountainous environment located in Northern Italy. The benchmark dataset was provided by an operational network of rain gauges and by three disdrometers. Moreover, disdrometer data were used to establish an accurate relationship between path attenuation and rainfall intensity. A new method was developed for assessing CML: time series of rainfall occurrence and rainfall depth, representative of CML radio path, were derived from the nearby rain gauges and disdrometers and compared with the same quantities gathered from the CML. It turns out that, over the very short integration times considered (10 min), CML perform well in detecting rainfall, whereas quantitative rainfall estimates may have large discrepancies.

Laboratory modelling of urban flooding

This paper presents two datasets obtained from laboratory experiments of urban flooding in a street network performed at the University of Liège. The experimental model represents a part of a synthetic urban district that consists of three inlets, three outlets and several three- and four- branches crossroads. The following experimental data was produced: (i) dataset 1: time-series of flow depths at model inlets and time-series of discharges at model outlets for a two-branch junction model, a two-branch bifurcation model and a district model. The datasets were generated by varying the upstream and downstream boundary conditions, i.e. flooding conditions; (ii) dataset 2 includes the same data type as dataset 1 complemented by 2D surface velocity measured using the non-intrusive LSPIV technique for eight urban form configurations in the district model. The collected data enable improving the understanding of the effect of urban forms on the urban flood processes. These two datasets are valuable for validating and improving numerical or analytical models of urban flooding and may contribute to flood risk management and flood-resilient urban design.

Trends of lake temperature, mixing depth and ice cover thickness of European lakes during the last four decades

Lakes are particularly vulnerable ecosystems to global warming. Surface temperature of most lakes in the world has significantly increased. Here, we analysed time-series of water temperature, mixing-depth, and ice depth of 51 European lakes over the last four decades. We used data of surface temperature, total layer water temperature, mix-layer temperature, mix-layer depth, and ice cover depth obtained from the ERA5-Land reanalysis dataset. Our main objectives were a) to identify significant changes of the examined variables that have occurred from 1981 to 2019 and b) to assess the variability of changes in relation with geographical and lake morphological gradients. To this end, time series analysis was conducted using generalized additive models (GAMs). In addition, we quantified the magnitude of change by estimating the Sen's slopes for each variable and then we examined the variability of these slopes to geographical and lake morphological parameters using GAMs. Our results confirmed that water temperature parameters (surface, total-layer and mix-layer temperature) have significantly increased for all lakes during the last four decades. We also found significant changes of the mixing depth for 14 lakes. In addition, the lake ice depth has significantly decreased in all fifteen lakes of the subarctic climate region. Finally, we showed that the Sen's slopes depend on the geographic coordinates and the elevation of the lakes, whereas lake morphometry (e.g. depth) has a smaller effect on the magnitude of changes. These findings hint that lake ecosystems of Europe have substantially changed over the last forty years and urge the need to take precautionary measures to prevent future implications for the freshwater biota.

A 30-Year Climatology (1990–2020) of Aerosol Optical Depth and Total Column Water Vapor and Ozone over Texas

Abstract A 30-yr time series (4 February 1990–4 February 2020) of aerosol optical depth (AOD) of the atmosphere, total precipitable water (TPW), and total column ozone has been conducted in central Texas using simple, highly stable instruments. All three parameters in this ongoing measurement series exhibited robust annual cycles. They also responded to many atmospheric events, including the historic volcanic eruption of Mount Pinatubo (1991), a record El Niño (1998), an unprecedented biomass smoke event (1998), and La Niña that caused the driest drought in recorded Texas history (2011). Reduced air pollution caused mean AOD to decline from 0.175 to 0.14. The AOD trend measured for 30 years by a light-emitting diode (LED) sun photometer, the first of its kind, parallels the trend from 20 years of measurements by a modified Microtops II. While TPW responded to El Niño–Southern Oscillation conditions, TPW exhibited no trend over the 30 years. The TPW data compare favorably with 4.5 years of simultaneous measurements by a nearby NOAA GPS (r2 = 0.78). The 30 years of ozone measurements compare favorably with those from a series of NASA ozone satellites (r2 = 0.78). In 2016, 194 comparisons of Microtops II and world standard ozone instrument Dobson 83 at the Mauna Loa Observatory agreed within 1.9% (r2 = 0.81). The paper concludes by observing that students and citizen scientists can collect scientifically useful atmospheric data with simple sun photometers that use one or more LEDs as spectrally selective photodiodes.

Observation and modelling of snow and sea ice mass balance and its sensitivity to atmospheric forcing during spring and summer 2007 in the Central

Snow depth and sea ice thickness were observed applying an ice mass balance buoy (IMB) in the drifting ice station Tara during the International Polar Year in 2007. Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August. For this study, the operational analyses and short-term forecasts from two numerical weather prediction (NWP) models (ECMWF and HIRLAM) were extracted for the Tara drift trajectory. We compared the IMB, meteorological and surface flux observations against the NWP products, also applying a one-dimensional thermodynamic sea ice model (HIGHTSI) to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing. The modelled snow depth time series, controlled by NWP-based precipitation, was in line with the observed one. HIGHTSI reproduced well the snowmelt onset, the progress of the melt, and the first date of snow-free conditions. HIGHTSI performed well also in the late August freezing season. Challenges remain to model the “false bottom” observed during the melting season. The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results. During the melting period, the nonlinear ice temperature profile was successfully modelled with both forcing options. During spring and the melting season, total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation, followed by the downward shortwave radiation, air temperature, and wind speed. Citation : Cheng B, Vihma T, Palo T, et al. Observation and modelling of snow and sea ice mass balance and its sensitivity to atmospheric forcing during spring and summer 2007 in the Central Arctic. Adv Polar Sci, 2021, 32(4): 309-323, doi: 10.13679/j.advps.2021.0047

Snow Depth Retrieval on Arctic Sea Ice Using Under-Ice Hyperspectral Radiation Measurements

Radiation transmitted through sea ice and snow has an important impact on the energy partitioning at the atmosphere-ice-ocean interface. Snow depth and ice thickness are crucial in determining its temporal and spatial variations. Under-ice surveys using autonomous robotic vehicles to measure transmitted radiation often lack coincident snow depth and ice thickness measurements so that direct relationships cannot be investigated. Snow and ice imprint distinct features on the spectral shape of transmitted radiation. Here, we use those features to retrieve snow depth. Transmitted radiance was measured underneath landfast level first-year ice using a remotely operated vehicle in the Lincoln Sea in spring 2018. Colocated measurements of snow depth and ice thickness were acquired. Constant ice thickness, clear water conditions, and low in-ice biomass allowed us to separate the spectral features of snow. We successfully retrieved snow depth using two inverse methods based on under-ice optical spectra with 1) normalized difference indices and 2) an idealized two-layer radiative transfer model including spectral snow and sea ice extinction coefficients. The retrieved extinction coefficients were in agreement with previous studies. We then applied the methods to continuous time series of transmittance and snow depth from the landfast first-year ice and from drifting, melt-pond covered multiyear ice in the Central Arctic in autumn 2018. Both methods allow snow depth retrieval accuracies of approximately 5 cm. Our results show that atmospheric variations and absolute light levels have an influence on the snow depth retrieval.

Movement patterns of a Critically Endangered elasmobranch (Dipturus intermedius) in a Marine Protected Area

Abstract Marine Protected Areas (MPAs) are widely used in marine management, but for mobile species understanding the spatio‐temporal scale of management measures that is required to deliver conservation benefits depends on a detailed knowledge of species’ movements that is often lacking. This is especially the case for species of skate (Rajidae) for which relatively few movement studies have been conducted. In Scotland, the Loch Sunart to the Sound of Jura MPA covering 741 km2 has been designated for the conservation of the Critically Endangered flapper skate (Dipturus intermedius), but fine‐scale movements within this area remain poorly understood. A passive acoustic telemetry study which coupled acoustic tagging of 42 individuals and a static array of 58 receivers was conducted from March 2016 to June 2017. Using acoustic detection time series, angler capture–recapture data and depth time series from archival tags, fine‐scale movements of individuals were investigated. Overall, 33 of the 42 tagged individuals were detected. Residency, site fidelity and transiency were documented. Residency around receivers, lasting from 3 to more than 12 months, was documented in 16 acoustically detected individuals (48%) and all life‐history categories, but was most noticeable among females. Acoustic detections were associated with depth, salinity and season, but there was no evidence that individuals formed close‐knit groups in the areas in which they were detected. Taken together with historical occurrence records of flapper skate, the prevalence and scale of residency documented here suggest that the MPA is sufficiently large to benefit a notable percentage (38 [24–52]%) of skate found in the study area over monthly and seasonal timescales. This result strengthens the case for the use of MPAs to support the conservation of flapper skate and other skate species that display similar movement patterns in areas of high local abundance.