Remote sensing of groundwater storage change - past, present and future

2020 ◽  
Author(s):  
Susanna Werth ◽  
Manoochehr Shirzaei ◽  
Grace Carlson ◽  
Chandrakanta Ojha
Keyword(s):  
High Resolution ◽  
Surface Deformation ◽  
Central Valley ◽  
Groundwater Depletion ◽  
High Temporal Resolution ◽  
Hydrological Models ◽  
Groundwater Storage ◽  
Aquifer System ◽  
Vertical Land Motion ◽  
The Impact

<p>Groundwater remains one of the least comprehensively monitored storage components in the hydrological cycle, because it's flow and storage processes are strongly linked to geology of the underground and because direct observations from well sites provide only point observations of complex and partly deep aquifer systems.</p><p>In recent years, geodetic methods have become increasingly available to complement ground-based observations and to expand investigations of the impact of climate extremes or human water use on groundwater storage variability. Satellite gravimetry from the Gravity Recovery And Climate Experiment (GRACE/FO) has been shown to be sensitive to groundwater depletion at large spatial scales (> 300km) and relatively high temporal resolution (monthly). These data provide a valuable boundary condition for regional studies, and they have been applied widely to improve parameter and structure of hydrological models.</p><p>Moreover, changes in groundwater stocks cause surface deformation associated with regional elastic loading of the Earth’s crust and localized poroelastic compaction of the aquifer skeleton, which are detectable by GPS and InSAR. The loading signal is typically much smaller than the land subsidence due to poroelastic compaction and thus masks out the loading signal adjacent to the aquifer system. However, the poroelastic signal can be used to estimate groundwater volume change in confined aquifer units and provides insight into the mechanical properties of the aquifer system. Also, the deformation sensors provide spatial resolutions of tens of meters (e.g., InSAR) to several kilometers (e.g., GPS) that can be used to solve for the volume of fluid removed from the aquifer system.</p><p>In this presentation, we demonstrate and discuss the applicability of poroelastic modeling, by applying GPS and InSAR based observations of vertical land motion, to quantify groundwater storage changes. Using the Central Valley in California as an example, we will show when this approach is applicable and when it is not, depending on the type of aquifer and observed deformation compared to water level changes. Using a 1-D poroelastic calculation based on deformation data, we find a groundwater loss of 21.3±7.2 km<sup>3</sup> for the entire Central Valley during 2007-2010 and of 29.3±8.7 km<sup>3</sup> for the San Joaquin Valley during 2012-2015. These loss estimates during drought are consistent with that of GRACE-based estimates considering uncertainty ranges.</p><p>Finally, we will discuss the increased availability of high-resolution radar data from Sentinel 1A/B as well as the upcoming radar mission NASA-ISRO SAR Mission (NISAR), to be launched in 2022, and how this will allow for high-resolution monitoring of vertical land motion and with that of compaction in confined aquifers around the world. The availability of these datasets increases the capability of geodetic methods for groundwater monitoring at higher spatial resolution than GRACE data, hence, providing the potential to apply these datasets to further improve parameterization and formulation of groundwater routines in regional to large-scale hydrological models.</p>

Lumped hydrological model for reasonable, long- term predictions of groundwater storage and depletion

2020 ◽  
Author(s):  
Fahad Ejaz ◽  
Thomas Wöhling ◽  
Nowak Wolfgang
Keyword(s):  
River Discharge ◽  
Groundwater Depletion ◽  
Hydrological Models ◽  
Proof Of Concept ◽  
Groundwater Storage ◽  
Discharge Data ◽  
Aquifer Storage ◽  
Lumped Models ◽  
The Impact

<p>Excessive groundwater pumping due to immense agricultural, industrial and municipal demand poses a major threat of aquifer depletion in many areas around the world. The impact of climate change on the global hydrological cycle has further exacerbated the situation. Accurate and reliable prediction of long-term aquifer balance terms is a key prerequisite to manage groundwater sustainably. To deal with uncertainties of such predictions, lumped (conceptual) hydrological models could help with their computational speed that allows for Monte-Carlo simulation. Compared to more complex models, lumped models are fast, lean on data requirement and capable to quantify uncertainty. However, lumped models are mainly designed to simulate river discharge only, not aquifer storage. Even the standard practice for calibrating lumped hydrological models only includes river discharge, as data on groundwater storage is not directly accessible. In this study, we hypothesize that we can extend the HBV model by additional water budget and groundwater storage terms, and calibrated it on both groundwater storage data and discharge data. Then, we test whether its predictions of groundwater storage levels withstand validation tests. To avoid problems with unavailability of data for calibration and validation in a first proof of concept, we build a virtual reality with a MODFLOW-based model, driven with synthetic weather data over a period of more than 50 years. For rigorous testing, we cast calibration into the framework of Bayesian parameter inference, and validate with metrics that assess the appropriateness of the Bayesian prediction distribution of groundwater storage. We test our idea in the Wairau Plain aquifer, New Zealand. Poor understanding of recharge mechanisms and hence declining groundwater levels are the major hindrance for sustainable groundwater management in our study area. We pay specific attention to river-groundwater exchange processes, to the forecast of aquifer storage dynamics, and to groundwater depletion in a hypothetical, persistent draught. The purpose is to provide a proof of concept whether lumped models can be adapted and made suitable to predict declining groundwater resources up to full depletion, as an uncertainty-aware decision support system for sustainable management.</p><p> </p>

scholarly journals Anthropogenic drought dominates groundwater depletion in Iran

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Samaneh Ashraf ◽  
Ali Nazemi ◽  
Amir AghaKouchak
Keyword(s):  
Economic Security ◽  
Groundwater Depletion ◽  
Groundwater Storage ◽  
Rates Of Change ◽  
Level Data ◽  
Basin Scale ◽  
Storage Basin ◽  
Groundwater Reserves ◽  
The Impact ◽  
Hydrological Droughts

AbstractUsing publicly-available average monthly groundwater level data in 478 sub-basins and 30 basins in Iran, we quantify country-wide groundwater depletion in Iran. Natural and anthropogenic elements affecting the dynamics of groundwater storage are taken into account and quantified during the period of 2002–2015. We estimate that the total groundwater depletion in Iran to be ~ 74 km3 during this period with highly localized and variable rates of change at basin and sub-basin scales. The impact of depletion in Iran’s groundwater reserves is already manifested by extreme overdrafts in ~ 77% of Iran’s land area, a growing soil salinity across the entire country, and increasing frequency and extent of land subsidence in Iran’s planes. While meteorological/hydrological droughts act as triggers and intensify the rate of depletion in country-wide groundwater storage, basin-scale groundwater depletions in Iran are mainly caused by extensive human water withdrawals. We warn that continuation of unsustainable groundwater management in Iran can lead to potentially irreversible impacts on land and environment, threatening country’s water, food, socio-economic security.

scholarly journals Evaluating the impact of spatial resolution on tropospheric NO<sub>2</sub> column comparisons within urban areas using high-resolution airborne data

2019 ◽  
Vol 12 (11) ◽  
pp. 6091-6111 ◽  
Author(s):  
Laura M. Judd ◽  
Jassim A. Al-Saadi ◽  
Scott J. Janz ◽  
Matthew G. Kowalewski ◽  
R. Bradley Pierce ◽  
...  
Keyword(s):  
High Resolution ◽  
Los Angeles ◽  
Spatial Heterogeneity ◽  
Spatial Resolution ◽  
Urban Areas ◽  
High Temporal Resolution ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
The Impact

Abstract. NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88; TROPOMI scale =0.77; OMI scale =0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

scholarly journals Indications for Protracted Groundwater Depletion after Drought over the Central Valley of California*,+

2016 ◽  
Vol 17 (3) ◽  
pp. 947-955 ◽  
Author(s):  
S.-Y. Simon Wang ◽  
Yen-Heng Lin ◽  
Robert R. Gillies ◽  
Kirsti Hakala
Keyword(s):  
El Nino ◽  
Central Valley ◽  
The State ◽  
First Century ◽  
Groundwater Depletion ◽  
Groundwater Storage ◽  
Twenty First Century ◽  
Agricultural Regions ◽  
California's Central Valley ◽  
California’S Central Valley

Abstract Ongoing (2014–16) drought in the state of California has played a major role in the depletion of groundwater. Within California’s Central Valley, home to one of the world’s most productive agricultural regions, drought and increased groundwater depletion occurs almost hand in hand, but this relationship appears to have changed over the last decade. Data derived from 497 wells have revealed a continued depletion of groundwater lasting a full year after drought, a phenomenon that was not observed in earlier records before the twenty-first century. Possible causes include 1) lengthening of drought associated with amplification in the 4–6-yr drought and El Niño frequency since the late 1990s and 2) intensification of drought and increased pumping that enhances depletion. Altogether, the implication is that current groundwater storage in the Central Valley will likely continue to diminish even further in 2016, regardless of the drought status.

Seasonal variation in water storage, vertical land motion and well levels: Implications for groundwater storage change in Central Valley

2020 ◽  
Author(s):  
Susanna Werth ◽  
Manoochehr Shirzaei
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Central Valley ◽  
Groundwater Storage ◽  
Resources Management ◽  
Groundwater Levels ◽  
Climate Research ◽  
Vertical Land Motion ◽  
Storage Change ◽  
Insight Into

&lt;p&gt;The establishment of the Inter-Commission Committee on &quot;Geodesy for Climate Research&quot; (ICCC) of the International Association of Geodesy (IAG) emphasizes on the usefulness of geodetic sensors for estimating high-resolution water mass variation, which is due to broad applications of geodetic tools ranging from water cycle studies to water resources management. As such, data from both GRACE missions continue to provide insight into the alarming rates of groundwater depletion in large aquifers worldwide. Observations of vertical land motion (VLM) from GPS and InSAR may reflect elastic responses of the Earth's crust to changes in mass load, including those in aquifers. However, above confined aquifers, VLM observations are dominated by poroelastic deformation processes. In previous works, Ojha et al. 2018 and 2019 show that GRACE-based estimates of groundwater storage change in the Central Valley, California, are consistent with those obtained by utilizing measurements of surface deformation. These studies also show that annual variations in VLM correlate well in time with groundwater levels.&lt;/p&gt;&lt;p&gt;Here, we investigate seasonal variations in groundwater storage by identifying how their effect is manifested in geodetic and hydrological datasets. Groundwater well observations in the Central Valley indicate maximum groundwater levels at the beginning of the year between February to April and lowest water levels in the middle of the year about July to October. Meanwhile, GRACE groundwater storage estimates peak about four months later. To get insight into the mechanisms leading to this discrepancy, we perform a Wavelet multi-resolution analysis of GRACE TWS variations and complementary groundwater, snowcap, soil moisture, and reservoir level variations. We show that the majority of the differences between wavelet spectrums at seasonal frequencies occur during drought periods when there is no supply of precipitation in the high elevations. We employ a 1D diffusion model to demonstrate that the variations in groundwater levels across the Central Valley are due to the propagation of the pressure front at recharge sites due to gradual snowmelt. Such a model could explain the different timing of peaks in groundwater time series based on satellite gravimetry compared to deformation and well observations. We also discuss that winter rains are not able to directly contribute to recharging deep aquifers in the Central Valley, whereas most of the recharge must source from lateral flow caused by differential pressure at the sites of snow-melt in the Sierra Nevada as well as from agricultural return flows.&lt;/p&gt;&lt;p&gt;This analysis addresses the question of how well the different geodetic signals that reflect groundwater discharge and recharge processes agree with one another and what are the possible causes of disagreements. We emphasize the need for interdisciplinary efforts for the successful integration of available geodetic and hydrological datasets to improve our ability to utilizing geodetic sensors for climate research and water resources management.&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;Ojha, C., Werth, S., &amp; Shirzaei, M. (2019). JGR, https://doi.org/10.1029/2018JB016083.&lt;/p&gt;&lt;p&gt;Ojha, C., M. Shirzaei, S. Werth, D. F. Argus, and T. G. Farr (2018), WRR, https://doi.org/10.1029/2017WR022250.&lt;/p&gt;

scholarly journals The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

2021 ◽  
Author(s):  
Alberto Caldas-Alvarez ◽  
Samiro Khodayar ◽  
Peter Knippertz
Keyword(s):  
High Resolution ◽  
Temporal Resolution ◽  
Hydrological Cycle ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Small Scale ◽  
High Temporal Resolution ◽  
The Impact

Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System-Zenith Total Delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ~700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 h to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological Cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the COnsortium for Small scale MOdelling (COSMO) model assimilating GPS, high- and low vertical resolution radiosoundings in model resolutions of 7 km, 2.8 km and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity, but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nimes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent three hours. This precipitation increase is brought about by the moistening of the 700  hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type, however the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. In follow-up experiments the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its numerical and physics updates, compared to its predecessor COSMO, are able to improve the quality of the simulations.

A conceptual analytical framework to assess the large-scale effects of groundwater withdrawal on groundwater storage and surface water flow

2021 ◽  
Author(s):  
Marc F.P. Bierkens ◽  
Edwin H. Sutanudjaja ◽  
Niko Wanders
Keyword(s):  
Surface Water ◽  
Scale Effects ◽  
Analytical Framework ◽  
Groundwater Withdrawal ◽  
Irrigated Agriculture ◽  
Groundwater Depletion ◽  
Steady Increase ◽  
Groundwater Storage ◽  
The Impact ◽  
Streamflow Depletion

&lt;p&gt;To meet increasing food demands, irrigated agriculture has expanded into semi-arid areas with limited precipitation and surface water availability. This has greatly intensified the dependence of irrigated crops on groundwater withdrawal and caused a steady increase of non-renewable groundwater use. One of the effects of groundwater pumping is the reduction in streamflow through capture of groundwater recharge, with detrimental effects on aquatic ecosystems. The degree to which groundwater withdrawal affects streamflow or groundwater storage depends on the nature of the groundwater-surface water interaction (GWSI). So far, analytical solutions that have been derived to calculate the impact of groundwater on streamflow depletion involve single wells and streams and do not allow the GWSI to shift from connected to disconnected, i.e. from a situation with two-way interaction to one with a one-way interaction between groundwater and surface water. Including this shift and also analyse the effects of many wells, requires numerical groundwater models that are expensive to setup. Here, we introduce a simple conceptual analytical framework that allows to estimate to what extent groundwater withdrawal affects groundwater heads and streamflow. It allows for a shift in GWSI, calculates at which critical withdrawal rate such a shift is expected and when it is likely to occur after withdrawal commences. It also provides estimates of streamflow depletion and which part of the groundwater withdrawal comes out of groundwater storage and which parts from a reduction in streamflow. The framework is used to provide global maps of critical withdrawal rates and timing, the areas where current withdrawal exceeds critical limits, and maps of groundwater depletion and streamflow depletion rates that result from groundwater withdrawal. The resulting global depletion rates are similar to those obtained from global hydrological models and satellites. The analytical framework is particularly useful for performing first-order sensitivity studies and for supporting hydroeconomic models that require simple relationships between groundwater withdrawal rates and the evolution of pumping costs and environmental externalities.&lt;/p&gt;

scholarly journals Large-scale sensitivities of groundwater and surface water to groundwater withdrawal

2020 ◽  
Author(s):  
Marc F. P. Bierkens ◽  
Edwin H. Sutanudjaja ◽  
Niko Wanders
Keyword(s):  
Surface Water ◽  
Analytical Framework ◽  
Groundwater Withdrawal ◽  
Irrigated Agriculture ◽  
Groundwater Depletion ◽  
Steady Increase ◽  
Groundwater Storage ◽  
Aquifer Storage ◽  
The Impact ◽  
Streamflow Depletion

Abstract. Increasing population, economic growth and changes in diet have dramatically increased the demand for food and water over the last decades. To meet increasing demands, irrigated agriculture has expanded into semi-arid areas with limited precipitation and surface water availability. This has greatly intensified the dependence of irrigated crops on groundwater withdrawal and caused a steady increase of non-renewable groundwater use, i.e. groundwater taken out of aquifer storage that will not be replenished in human time scales. One of the effects of groundwater pumping is the reduction in streamflow through capture of groundwater recharge, with detrimental effects on aquatic ecosystems. The degree to which groundwater withdrawal affects streamflow or groundwater storage depends on the nature of the groundwater-surface water interaction (GWSI). So far, analytical solutions that have been derived to calculate the impact of groundwater on streamflow depletion involve single wells and streams and do not allow the GWSI to shift from connected to disconnected, i.e. from a situation with two-way interaction to one with a one-way interaction between groundwater and surface water. Including this shift and also analyse the effects of many wells, requires numerical groundwater models that are expensive to setup. Here, we introduce a simple conceptual analytical framework that allows to estimate to what extent groundwater withdrawal affects groundwater heads and streamflow. It allows for a shift in GWSI, calculates at which critical withdrawal rate such a shift is expected and when it is likely to occur after withdrawal commences. It also provides estimates of streamflow depletion and which part of the groundwater withdrawal comes out of groundwater storage and which parts from a reduction in streamflow. After a local sensitivity analysis, the framework is used to provide global maps of critical withdrawal rates and timing, the areas where current withdrawal exceeds critical limits, and maps of groundwater depletion and streamflow depletion rates that result from groundwater withdrawal. The resulting global depletion rates are similar to those obtained from global hydrological models and satellites. The analytical framework is particularly useful for performing first-order sensitivity studies and for supporting hydroeconomic models that require simple relationships between groundwater withdrawal rates and the evolution of pumping costs and environmental externalities.

scholarly journals The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

2021 ◽  
Vol 2 (3) ◽  
pp. 561-580
Author(s):  
Alberto Caldas-Alvarez ◽  
Samiro Khodayar ◽  
Peter Knippertz
Keyword(s):  
High Resolution ◽  
Temporal Resolution ◽  
Hydrological Cycle ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Small Scale ◽  
High Temporal Resolution ◽  
The Impact

Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation, and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System (GPS)-derived zenith total delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ∼ 700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the Consortium for Small-scale Modeling (COSMO) model assimilating GPS, high- and low-vertical-resolution radiosoundings in model resolutions of 7 km, 2.8 km, and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate for errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nîmes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent 3 h. This precipitation increase is brought about by the moistening of the 700 hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type; however, the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. Future work will aim at a generalization of these conclusions, investigating further cases of the autumn 2012, and the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its updates are able to improve the quality of the simulations.

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