Model estimates of sea-level change due to anthropogenic impacts on terrestrial water storage

2012 ◽  
Vol 5 (6) ◽  
pp. 389-392 ◽  
Author(s):  
Yadu N. Pokhrel ◽  
Naota Hanasaki ◽  
Pat J-F. Yeh ◽  
Tomohito J. Yamada ◽  
Shinjiro Kanae ◽  
...  
Keyword(s):  
Sea Level ◽  
Anthropogenic Impacts ◽  
Water Storage ◽  
Sea Level Change ◽  
Terrestrial Water Storage ◽  
Level Change ◽  
Terrestrial Water

Emerging instability in global terrestrial water storage since 2010

2020 ◽  
Author(s):  
Shuang Yi ◽  
Nico Sneeuw
Keyword(s):  
Sea Level ◽  
Water Storage ◽  
Precipitation Trend ◽  
Terrestrial Water Storage ◽  
Level Change ◽  
Before And After ◽  
Terrestrial Water ◽  
Global Sea Level ◽  
The Stability ◽  
Global Precipitation

<p>Global terrestrial water storage (TWS) is an indicator of the integrated impact of climate variability on the environment. Accurate assessments of global TWS also facilitate the understanding of disturbances in global sea level rise. Gravity satellite GRACE has proved to be an effective tool in monitoring global TWS changes. With the latest observations of GRACE and GRACE Follow-on, we estimated the global TWS from April 2002 to October 2019, and found contrasting variations in global TWS before and after 2010. Before 2010, the global TWS was almost stable with variations that contribute only a few millimeters of sea level change; while the stability is ceased after the 2010/11 La Nina and three drastic fluctuations of up to 10 millimeters sea level contribution have occurred since then. We find these TWS changes have a good linear relationship with the global precipitation trend, rather than the accumulation of net precipitation, indicating that the precipitation trend is the main driving force of the recent global TWS instability. We further investigate the sensitivities of TWS to precipitation in basins.</p>

Data assimilation of GRACE terrestrial water storage to improve sea level rise estimates and isolate anthropogenic influences

2021 ◽  
Author(s):  
Ann Scheliga ◽  
Manuela Girotto
Keyword(s):  
Data Assimilation ◽  
Sea Level Rise ◽  
Sea Level ◽  
Land Surface ◽  
Water Budget ◽  
Water Storage ◽  
Surface Model ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Land Hydrology

<p>Sea level rise (SLR) projections rely on the accurate and precise closure of Earth’s water budget. The Gravity Recovery and Climate Experiment (GRACE) mission has provided global-coverage observations of terrestrial water storage (TWS) anomalies that improve accounting of ice and land hydrology changes and how these changes contribute to sea level rise. The contribution of land hydrology TWS changes to sea level rise is much smaller and less certain than contributions from glacial melt and thermal expansion. Although land hydrology TWS plays a smaller role, it is still important to investigate to improve the precision of the overall global water budget. This study analyzes how data assimilation techniques improve estimates of the land hydrology contribution to sea level rise. To achieve this, three global TWS datasets were analyzed: (1) GRACE TWS observations alone, (2) TWS estimates from the model-only simulation using Catchment Land Surface Model, and (3) TWS estimates from a data assimilation product of (1) and (2). We compared the data assimilation product with the GRACE observations alone and the model-only simulation to isolate the contribution to sea level rise from anthropogenic activities. We assumed a balanced water budget between land hydrology and the ocean, thus changes in global TWS are considered equal and opposite to sea level rise contribution.  Over the period of 2003-2016, we found sea level rise contributions from each dataset of +0.35 mm SLR eq/yr for GRACE, -0.34 mm SLR eq/yr for model-only, and a +0.09 mm SLR eq/yr for DA (reported as the mean linear trend). Our results indicate that the model-only simulation is not capturing important hydrologic processes. These are likely anthropogenic driven, indicating direct anthropogenic and climate-driven TWS changes play a substantial role in TWS contribution to SLR.</p>

Terrestrial Water-Storage Contributions to Sea-Level Rise and Variability

2010 ◽  
pp. 226-255 ◽  
Author(s):  
P. C. D. Chris Milly ◽  
Anny Cazenave ◽  
James S. Famiglietti ◽  
Vivien Gornitz ◽  
Katia Laval ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Terrestrial Water

scholarly journals The Influence of Water Storage in Marine Sediment on Sea‐Level Change

2018 ◽  
Vol 45 (5) ◽  
pp. 2444-2454 ◽  
Author(s):  
Ken L. Ferrier ◽  
Qi Li ◽  
Tamara Pico ◽  
Jacqueline Austermann
Keyword(s):  
Sea Level ◽  
Marine Sediment ◽  
Water Storage ◽  
Sea Level Change ◽  
Level Change ◽  
Influence Of Water

Predicting elastic deformations of the crust induced by environmental loading on time-scales from days to decades

2021 ◽  
Author(s):  
Robert Dill ◽  
Henryk Dobslaw ◽  
Anna Klos
Keyword(s):  
Mass Balance ◽  
Sea Level ◽  
Surface Pressure ◽  
Water Storage ◽  
Ocean Dynamics ◽  
Terrestrial Water Storage ◽  
Environmental Loading ◽  
Variable Surface ◽  
Terrestrial Water ◽  
Sea Level Variations

<p>Earth’s surface is elastically deformed by time-variable surface mass loads such as variations in atmospheric surface pressure, ocean bottom pressure, and terrestrial water storage. We look at the individual environmental loading contributions from the three different subsystems (atmosphere, terrestrial water storage, ocean) as well as from sea-level variations induced by the global water mass balance between land and ocean. Dividing the contributions into a set of period bands by means of a Wavelet decomposition, we show that non-tidal atmospheric surface loading (NTAL) by far dominates non-tidal ocean (NTOL) and hydrospheric loading (HYDL) for periods as long as a few months. The contribution of terrestrial water storage is continuously growing for increasingly longer periods and dominates atmospheric pressure at periods of 300 days and above. Ocean dynamics including sea-level variations due to the seasonal global mass balance are only important in the immediate vicinity of the coast.</p><p>In representative regions, we compare different environmental loading estimates, e.g. ESMGFZ based on ECMWF operational atmospheric data, NTAL and NTOL based on ECMWF ERA5, HYDL based on GRACE/GRACE-FO. Depending on the geographical location and considered frequency range, different estimates for NTOL and HYDL can exhibit large differences. In contrast, all latest loading models show a very consistent picture of atmospheric surface pressure loading deformations.  To evaluate the ability of different GNSS solutions to confirm the vertical deformations predicted by the geophysical fluid models, we compared at selected sites vertical station coordinates from six GNSS solutions with loading model predictions. In many cases, GNSS-derived variations heavily dependent on subjective choices within the GNSS data processing.</p>

scholarly journals Radar Altimetry as a Proxy for Determining Terrestrial Water Storage Variability in Tropical Basins

2019 ◽  
Vol 11 (21) ◽  
pp. 2487 ◽  
Author(s):  
Melo ◽  
Getirana
Keyword(s):  
Time Series ◽  
Amazon Basin ◽  
Anthropogenic Impacts ◽  
Water Storage ◽  
Principal Component ◽  
Water Levels ◽  
Terrestrial Water Storage ◽  
Validation Experiment ◽  
Physically Based ◽  
Terrestrial Water

The Gravity Recovery and Climate Experiment (GRACE) mission has provided us with unforeseen information on terrestrial water-storage (TWS) variability, contributing to our understanding of global hydrological processes, including hydrological extreme events and anthropogenic impacts on water storage. Attempts to decompose GRACE-based TWS signals into its different water storage layers, i.e., surface water storage (SWS), soil moisture, groundwater and snow, have shown that SWS is a principal component, particularly in the tropics, where major rivers flow over arid regions at high latitudes. Here, we demonstrate that water levels, measured with radar altimeters at a limited number of locations, can be used to reconstruct gridded GRACE-based TWS signals in the Amazon basin, at spatial resolutions ranging from 0.5 to 3, with mean absolute errors (MAE) as low as 2.5 cm and correlations as high as 0.98. We show that, at 3 spatial resolution, spatially-distributed TWS time series can be precisely reconstructed with as few as 41 water-level time series located within the basin. The proposed approach is competitive when compared to existing TWS estimates derived from physically based and computationally expensive methods. Also, a validation experiment indicates that TWS estimates can be extrapolated to periods beyond that of the model regression with low errors. The approach is robust, based on regression models and interpolation techniques, and offers a new possibility to reproduce spatially and temporally distributed TWS that could be used to fill inter-mission gaps and to extend GRACE-based TWS time series beyond its timespan.

Regional patterns of ocean mass sea-level change over the satellite altimetry era (1993-2017)

2021 ◽  
Author(s):  
Carolina M. L. Camargo ◽  
Riccardo E. M. Riva ◽  
Aimée B. A. Slangen
Keyword(s):  
Sea Level ◽  
Ice Sheets ◽  
Sea Level Change ◽  
Satellite Mission ◽  
Regional Patterns ◽  
Level Change ◽  
Ocean Mass ◽  
Terrestrial Water ◽  
The Individual ◽  
The Antarctic

<p>Ocean mass variation is one of the main drivers of present-day sea-level change (SLC). Also known as barystatic SLC, those fluctuations are due to the melting of continental ice from glaciers and ice sheets, and variations in landwater storage. While a large number of studies have quantified the contribution of barystatic SLC to global mean SLC, fewer works have looked into how much ocean mass has contributed to regional SLC. Besides, most of the regional studies have focused only on the effect of one of the components (e.g., melt from Antarctica), or on the period and results of the GRACE satellite mission (since 2002). This work aims at providing a comprehensive analysis of global and regional barystatic SLC since 1993. For that, we collect a suite of estimates of the individual freshwater sources, namely the Antarctic and Greenland ice sheets, glaciers and terrestrial water storage. We then use them as input on the sea-level equation to obtain regional patters (fingerprints) of barystatic SLC, and validate our results by comparing the individual estimates with the values obtained from GRACE products. We finalize our analysis by looking into trend uncertainty patterns related to each contribution.</p>

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