Spatial–Temporal Variability of Great Slave Lake Levels From Satellite Altimetry

2010 ◽  
Vol 7 (3) ◽  
pp. 426-429 ◽  
Author(s):  
Sergio E. Sarmiento ◽  
Shuhab D. Khan
Keyword(s):  
Temporal Variability ◽  
Satellite Altimetry ◽  
Lake Levels ◽  
Great Slave Lake

scholarly journals Interannual variability of the lake levels in northwest Russia based on satellite altimetry

2015 ◽  
Vol 365 ◽  
pp. 91-97
Author(s):  
S. A. Lebedev ◽  
Y. I. Troitskaya ◽  
G. V. Rybushkina ◽  
M. N. Dobrovolsky
Keyword(s):  
Water Level ◽  
Interannual Variability ◽  
Temporal Variability ◽  
Satellite Altimetry ◽  
Lake Level ◽  
Lake Ladoga ◽  
Lake Levels ◽  
Lake Onega ◽  
Lake Ilmen ◽  
Altimetric Measurements

Abstract. Variability of the largest lakes levels in northwest Russia, a climatic change parameter, is characterized by alternating periods of rise and fall according to altimetric measurements of the TOPEX/Poseidon and Jason-1/2 satellites. Water level was calculated with the use of a regional adaptive retracking algorithm for the lakes Il’men, Ladoga, Onega and Peipus. Applications of this algorithm considerably increase the quantity of actual data records and significantly improve the accuracy of water level evaluation. According to the results, temporal variability of Lake Ilmen, Lake Ladoga and Lake Piepus levels is characterized by a wave with a period of 4–5 years, and that of Lake Onega level is characterized by a wave with a period of 15 years. During the period from 1993 to 2011, lake level rose at a rate of 1.17±0.95 cm/year for Lake Il’men, 0.24 ± 0.10 cm/year for Lake Ladoga, 1.39 ± 0.18 cm/year for Lake Piepus and 0.18 ± 0.09 cm/year for Lake Onega.

scholarly journals Effect of horizontal divergence on estimates of firn-air content

2020 ◽  
pp. 1-10
Author(s):  
Annika N. Horlings ◽  
Knut Christianson ◽  
Nicholas Holschuh ◽  
C. Max Stevens ◽  
Edwin D. Waddington
Keyword(s):  
Mass Balance ◽  
Temporal Variability ◽  
Satellite Altimetry ◽  
Spatiotemporal Variability ◽  
Accurate Calculation ◽  
Time Step ◽  
Ice Flow ◽  
Air Content ◽  
Ice Sheet Mass Balance ◽  
The Impact

Abstract Ice-sheet mass-balance estimates derived from repeat satellite-altimetry observations require accurate calculation of spatiotemporal variability in firn-air content (FAC). However, firn-compaction models remain a large source of uncertainty within mass-balance estimates. In this study, we investigate one process that is neglected in FAC estimates derived from firn-compaction models: enhanced layer thinning due to horizontal divergence. We incorporate a layer-thinning scheme into the Community Firn Model. At every time step, firn layers first densify according to a firn-compaction model and then thin further due to an imposed horizontal divergence rate without additional density changes. We find that horizontal divergence on Thwaites (THW) and Pine Island Glaciers can reduce local FAC by up to 41% and 18%, respectively. We also assess the impact of temporal variability of horizontal divergence on FAC. We find a 15% decrease in FAC between 2007 and 2016 due to horizontal divergence at a location that is characteristic of lower THW. This decrease accounts for 16% of the observed surface lowering, whereas climate variability alone causes negligible changes in FAC at this location. Omitting transient horizontal divergence in estimates of FAC leads to an overestimation of ice loss via satellite-altimetry methods in regions of dynamic ice flow.

Contemporary monitoring of storm surge activity

2019 ◽  
Vol 44 (3) ◽  
pp. 299-314 ◽  
Author(s):  
Tao Ji ◽  
Guosheng Li
Keyword(s):  
Climate Change ◽  
Storm Surge ◽  
Temporal Variability ◽  
Satellite Altimetry ◽  
Storm Surges ◽  
Spatial And Temporal Variability ◽  
Tide Gauges ◽  
Sea Levels ◽  
Rising Sea Levels

There is growing interest in storm surge activity related to catastrophic events and their unintended consequences in terms of casualties and damage around the world and in increasing populations and issues along coastal areas in the context of global warming and rising sea levels. Accordingly, knowledge on storm surge monitoring has progressed significantly in recent years, and this review, focused on monitoring the spatial and temporal variability of storm surges, responds to the need for a synthesis. Three main components are presented in the review: (1) monitoring storm surges from the viewpoint of three effective approaches; (2) understanding the challenges faced by the three monitoring approaches to increase our awareness of monitoring storm surges; (3) identifying three research priorities and orientations to provide new ideas in future storm surge monitoring. From the perspective of monitoring approaches, recent progress was achieved with respect to tide gauges, satellite altimetry and numerical simulation. Storm surge events can nowadays be identified accurately, and the surge heights can be calculated based on long-term tide gauge observations. The changing frequency and intensity of storm surge activity, combined with statistical analysis and climatology, can be used to enable a better understanding of the possible regional or global long-term trends. Compared with tidal observation data, satellite altimetry has the advantage of providing offshore sea level information to an accuracy of 10 cm. In addition, satellite altimetry can provide more effective observations for studying storm surges, such as transient surge data of the deep ocean. Simultaneously, the study of storm surges via numerical simulation has been further developed, mainly reflected in the gradual improvement of simulation accuracy but also in the refinement of comprehensive factors affecting storm surge activity. However, from the above approaches, storm surge activity monitoring cannot fully reflect the spatial and temporal variability of storm surges, especially the spatial changes at a regional or global scale. In particular, compared to global storm surge, tide gauges and satellite altimeters are relatively sparse, and the spatial distribution is extremely uneven, which often seriously restricts the overall understanding of the spatial distribution features of storm surge activity. Numerical models can be used as a tool to overcome the above-mentioned shortcomings for storm surge monitoring, as they provide real-time spatiotemporal features of storm surge events. But long-term numerical hindcast of tides and surges requires an extremely high computational effort. Considering the shortcomings of the above approaches and the impact of climate change, there is no clear approach to remedy the framework for studying the spatial and temporal characteristics of global or regional storm surge activity at a climatic scale. Therefore, we show how new insights or techniques are useful for the monitoring of future crises. This work is especially important in planning efforts by policymakers, coastal managers, civil protection managers and the general public to adapt to climate change and rising sea levels.

scholarly journals Geostrophic Currents in the northern Nordic Seas from a Combination of Multi-Mission Satellite Altimetry and Ocean Modeling

2019 ◽  
Author(s):  
Felix L. Müller ◽  
Denise Dettmering ◽  
Claudia Wekerle ◽  
Christian Schwatke ◽  
Marcello Passaro ◽  
...  
Keyword(s):  
Sea Ice ◽  
Spatial Patterns ◽  
Temporal Variability ◽  
Satellite Altimetry ◽  
Principal Component ◽  
Ocean Model ◽  
Surface Currents ◽  
Geostrophic Velocity ◽  
Nordic Seas ◽  
Along Track

Abstract. A deeper knowledge about geostrophic ocean surface currents in the northern Nordic Seas supports the understanding of ocean dynamics in an area affected by sea ice and rapidly changing environmental conditions. Monitoring these areas by satellite altimetry results in a fragmented and irregularly distributed data sampling and prevents the computation of homogeneous and highly resolved spatio-temporal datasets. In order to overcome this problem, an ocean model is used to fill in data when altimetry observations are missing. The present study provides a novel dataset based on a combination of along-track satellite altimetry derived dynamic ocean topography (DOT) elevations and simulated differential water heights (DWH) from the Finite Element Sea ice Ocean Model (FESOM). This innovative dataset differs from classical assimilation methods because it substitutes altimetry data with the model output, when altimetry fails or is not available. The combination approach is mainly based on a Principal Component Analysis (PCA) after reducing both quantities by their constant and seasonal signals. In the main step, the most dominant spatial patterns of the modeled differential water heights as provided by the PCA are linked with the temporal variability of the estimated DOT from altimetry by performing a Principal Component Synthesis (PCS). After the combination, the by altimetry obtained annual signal and a constant offset are re-added in order to reference the final data product to the altimetry height level. Surface currents are computed by applying the geostrophic flow equations to the combined topography. The resulting final product is characterized by the spatial resolution of the ocean model around 1 km and the temporal variability of the altimetry along-track derived DOT heights. The combined DOT is compared to an independent DOT product resulting in a positive correlation of about 80 % to provide more detailed information about short periodic and finer spatial structures. The derived geostrophic velocity components are evaluated by in-situ surface drifter observations. Summarizing all drifter observations in equal-sized bins and comparing the velocity components shows good agreement in spatial patterns, magnitude and flow direction. Mean differences of 0.004 m/s in the zonal and 0.02 m/s in the meridional component are observed. A direct pointwise comparison between the drifter trajectories and to the drifter location interpolated combined geostrophic velocity components indicates that about 94 % of all residuals are smaller than 0.15 m/s. The dataset is able to provide surface circulation information within the sea ice area and can be used to support a deeper comprehension of ocean currents in the northern Nordic Seas affected by rapid environmental changes in the 1995–2012 time period. The data is available at https://doi.org/10.1594/PANGAEA.900691 (Müller et al., 2019).

scholarly journals Wind Waves in the Mediterranean Sea: An ERA5 Reanalysis Wind-Based Climatology

2021 ◽  
Vol 8 ◽  
Author(s):  
Francesco Barbariol ◽  
Silvio Davison ◽  
Francesco Marcello Falcieri ◽  
Rossella Ferretti ◽  
Antonio Ricchi ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Wave Height ◽  
Temporal Variability ◽  
Satellite Altimetry ◽  
Wind Waves ◽  
Climate Indices ◽  
Atmospheric Parameter ◽  
Wave Hindcast ◽  
Individual Wave ◽  
The Mediterranean

A climatology of the wind waves in the Mediterranean Sea is presented. The climate patterns, their spatio-temporal variability and change are based on a 40-year (1980–2019) wave hindcast, obtained by combining the ERA5 reanalysis wind forcing with the state-of-the-art WAVEWATCH III spectral wave model and verified against satellite altimetry. Results are presented for the typical (50th percentile) and extreme (99th percentile) significant wave height and, for the first time at the regional Mediterranean Sea scale, for the typical and extreme expected maximum individual wave height of sea states. The climate variability of wind waves is evaluated at seasonal scale by proposing and adopting a definition of seasons for the Mediterranean Sea states that is based on the satellite altimetry wave observations of stormy (winter) and calm (summer) months. The results, initially presented for the four seasons and then for winter and summer only, show the regions of the basin where largest waves occur and those with the largest temporal variability. A possible relationship with the atmospheric parameter anomalies and with teleconnection patterns (through climate indices) that motivates such variability is investigated, with results suggesting that the Scandinavian index variability is the most correlated to the Mediterranean Sea wind-wave variability, especially for typical winter sea states. Finally, a trend analysis shows that the Mediterranean Sea typical and extreme significant and maximum individual wave heights are decreasing during summer and increasing during winter.

scholarly journals Geostrophic currents in the northern Nordic Seas from a combination of multi-mission satellite altimetry and ocean modeling

2019 ◽  
Vol 11 (4) ◽  
pp. 1765-1781 ◽  
Author(s):  
Felix L. Müller ◽  
Denise Dettmering ◽  
Claudia Wekerle ◽  
Christian Schwatke ◽  
Marcello Passaro ◽  
...  
Keyword(s):  
Sea Ice ◽  
Spatial Patterns ◽  
Temporal Variability ◽  
Satellite Altimetry ◽  
Principal Component ◽  
Ocean Model ◽  
Surface Currents ◽  
Geostrophic Velocity ◽  
Nordic Seas ◽  
Along Track

Abstract. A deeper knowledge about geostrophic ocean surface currents in the northern Nordic Seas supports the understanding of ocean dynamics in an area affected by sea ice and rapidly changing environmental conditions. Monitoring these areas by satellite altimetry results in a fragmented and irregularly distributed data sampling and prevents the computation of homogeneous and highly resolved spatio-temporal datasets. In order to overcome this problem, an ocean model is used to fill in data when altimetry observations are missing. The present study provides a novel dataset based on a combination of along-track satellite-altimetry-derived dynamic ocean topography (DOT) elevations and simulated differential water heights (DWHs) from the Finite Element Sea ice Ocean Model (FESOM) version 1.4. This innovative dataset differs from classical assimilation methods because it substitutes altimetry data with the model output when altimetry fails or is not available. The combination approach is mainly based on a principal component analysis (PCA) after reducing both quantities by their constant and seasonal signals. In the main step, the most-dominant spatial patterns of the modeled differential water heights as provided by the PCA are linked with the temporal variability in the estimated DOT from altimetry by performing a principal component synthesis (PCS). After the combination, the annual signal obtained by altimetry and a constant offset are re-added in order to reference the final data product to the altimetry height level. Surface currents are computed by applying the geostrophic flow equations to the combined topography. The resulting final product is characterized by the spatial resolution of the ocean model around 1 km and the temporal variability in the altimetry along-track derived DOT heights. The combined DOT is compared to an independent DOT product, resulting in a positive correlation of about 80 %, to provide more detailed information about short periodic and finer spatial structures. The derived geostrophic velocity components are evaluated by in situ surface drifter observations. Summarizing all drifter observations in equally sized bins and comparing the velocity components shows good agreement in spatial patterns, magnitude and flow direction. Mean differences of 0.004 m s−1 in the zonal and 0.02 m s−1 in the meridional component are observed. A direct pointwise comparison between the combined geostrophic velocity components interpolated onto the drifter locations indicates that about 94 % of all residuals are smaller than 0.15 m s−1. The dataset is able to provide surface circulation information within the sea ice area and can be used to support a deeper comprehension of ocean currents in the northern Nordic Seas affected by rapid environmental changes in the 1995–2012 time period. The data are available at https://doi.org/10.1594/PANGAEA.900691 (Müller et al., 2019).

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