Validating GIA models based on an ensemble of 3D Earth structures with present-day GPS uplift rates

2021 ◽  
Author(s):  
Volker Klemann ◽  
Eva Boergens ◽  
Meike Bagge
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Absolute Error ◽  
Global Climate Models ◽  
Delayed Response ◽  
Earth Structure ◽  
Isostatic Adjustment ◽  
Uplift Rates ◽  
Earth Structures ◽  
Mean Square Errors

<p>Glacial-isostatic adjustment (GIA) models simulate the viscoelastic response of the solid earth due to loading. During the last glacial maximum, large areas in the northern and southern hemisphere were covered by km-thick ice sheets. Although most of the ice has been melted already 8,000 year ago, the time-delayed response of the viscoelastic earth is still a significant contribution to present-day uplift rates. The implementation of GIA models in global climate models is an essential part of the current research. Hereby, the choice of an appropriate earth structure in the GIA model plays an important role and has to be constrained by observational data.</p><p>Here, we apply present-day uplift data to constrain a set of GIA models that differ in 3D earth structure. To this end, these different GIA models are validated against GPS uplift rates provided by Schumacher et al. (2019). The GPS stations are globally distributed and not necessarily clustered in regions with strong GIA signal. For validation, regions with the largest gradient present in the GIA signal are most crucial. Thus, we use a weighting scheme, where those GPS stations get a higher weight that are less correlated to all other stations. Additionally, uncertainties in the GPS rates appear due to the length of the GPS time series and due to station specifics such as the used GPS receiver, and are provided together with the rates as standard deviations. Thence, the weighting used for the validation is the sum of the correlation derived weights and the uncertainty derived weights.</p><p>With this weighting in place, different GIA models can be validated against present day uplift rates by means of root mean square errors or mean absolute error.</p>

scholarly journals Comparison of CMIP6 and CMIP5 Model Performance in Simulating Historical Precipitation and Temperature in Bangladesh: A Preliminary Study

2021 ◽  
Author(s):  
Mohammad Kamruzzaman ◽  
Shamsuddin Shahid ◽  
ARM Towfiqul Islam ◽  
Syewoon Hwang ◽  
Jaepil Cho ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Model Performance ◽  
Coupled Model ◽  
Skill Score ◽  
Global Climate Models ◽  
Added Value ◽  
Lower Performance ◽  
Mean Square Errors ◽  
Cmip5 Gcms

Abstract The relative performance of global climate models (GCMs) of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively) was assessed in this study based on their ability to simulate annual and seasonal mean rainfall and temperature over Bangladesh for the period 1977–2005. The multiple statistical metrics were used to measure the performance of the GCMs at 30 meteorological observation stations. Two robust multi-criteria decision analysis methods were used to integrate the results obtained using different metrics for an unbiased ranking of the GCMs. The results revealed MIROC5 as the most skilful among CMIP5 GCMs and ACCESS-CM2 among CMIP6 GCMs. Overall, a significant improvement in CMIP6 MME compared to CMIP5 MME was noticed in simulating rainfall over Bangladesh at annual and seasonal scales. CMIP6 MME also showed significant reduction in maximum and minimum temperature biases over Bangladesh. However, systematic wet and cold biases still exist in CMIP6 models for Bangladesh. CMIP6 GCMs showed higher spatial correlation with observed data compared to CMIP5 GCMs, but higher difference in terms of standard deviations and centered root mean square errors, indicating better performance in simulating geographical distribution but lower performance in simulating spatial variability of most of the climate variables for different timescales. In terms of Taylor skill score, the CMIP6 MME showed higher performance in simulating rainfall but lower performance in simulating temperature compared to CMIP5 MME for most of the timeframes. The findings of this study suggest that the added value of rainfall and temperature simulations in CMIP6 models is incompatible with the climate models used in this research.

scholarly journals Effectiveness of using representative subsets of global climate models in future crop yield projections

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Budong Qian ◽  
Qi Jing ◽  
Alex J. Cannon ◽  
Ward Smith ◽  
Brian Grant ◽  
...  
Keyword(s):  
Spring Wheat ◽  
Climate Models ◽  
Crop Yields ◽  
Global Climate ◽  
Simulation Models ◽  
Absolute Error ◽  
Global Climate Models ◽  
Climate Projections ◽  
Crop Simulation Models ◽  
Change Impact

AbstractRepresentative subsets of global climate models (GCMs) are often used in climate change impact studies to account for uncertainty in ensemble climate projections. However, the effectiveness of such subsets has seldom been assessed for the estimations of either the mean or the spread of the full ensembles. We assessed two different approaches that were employed to select 5 GCMs from a 20-member ensemble of GCMs from the CMIP5 ensemble for projecting canola and spring wheat yields across Canada under RCP 4.5 and 8.5 emission scenarios in the periods 2040–2069 and 2070–2099, based on crop simulation models. Averages and spreads of the simulated crop yields using the 5-GCM subsets selected by T&P and KKZ approaches were compared with the full 20-GCM ensemble. Our results showed that the 5-GCM subsets selected by the two approaches could produce full-ensemble means with a relative absolute error of 2.9–4.7% for canola and 1.5–2.2% for spring wheat, and covers 61.8–91.1% and 66.1–80.8% of the full-ensemble spread for canola and spring wheat, respectively. Our results also demonstrated that both approaches were very likely to outperform a subset of randomly selected 5 GCMs in terms of a smaller error and a larger range.

scholarly journals A Multiple 1D Earth Approach (M1DEA) to account for lateral viscosity variations in solutions of the sea level equation: An application for glacial isostatic adjustment by Antarctic deglaciation

2020 ◽  
Author(s):  
Robert Hartmann ◽  
Jörg Ebbing ◽  
Clinton P. Conrad
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Earth Structure ◽  
Glacial Isostatic Adjustment ◽  
Isostatic Adjustment ◽  
Time Period ◽  
Uplift Rates ◽  
Earth Structures ◽  
Load Component ◽  
Lateral Variations

<p>The pseudo-spectral form of the sea level equation (SLE) requires the approximation of a radially-symmetric visco-elastic Earth. Thus, the resulting predictions of sea level change (SLC) and glacial isostatic adjustment (GIA) often ignore lateral variations in the Earth structure. Here, we assess the capabilities of a Multiple 1D Earth Approach (M1DEA) applied to large-scale ice load components with different Earth structures to account for these variations. In this approach the total SLC and GIA responses result from the superposition of individual responses from each load component, each computed globally assuming locally-appropriate 1D Earth structures. We apply the M1DEA to three separate regions (East Antarctica, West Antarctica, and outside Antarctica) to analyze uplift rates for a range of Earth structures and different ice loads at various distances. We find that the uplift response is mostly sensitive to the local Earth structure, which supports the usefulness of the M1DEA. However, stresses transmitted across rheological boundaries (e.g., producing peripheral bulges) present challenges for the M1DEA, but can be minimized under two conditions: (1) If the considered time period of ice loading for each component is consistent with the relaxation time of the local Earth structure. (2) If the load components can be subdivided according to the scale of the lateral variations in Earth structure. Overall, our results indicate that M1DEA could be a computationally much cheaper alternative to 3D finite element models, but further work is needed to quantify the relative accuracy of both methods for different resolutions, loads, and Earth structure variations.</p>

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

scholarly journals Regions of intensification of extreme snowfall under future warming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Observational Data ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Average Intensity ◽  
High Latitudes ◽  
Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

scholarly journals Reassessing Existing Reservoir Supply Capacity and Management Resilience under Climate Change and Sediment Deposition

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1819
Author(s):  
Eleni S. Bekri ◽  
Polychronis Economou ◽  
Panayotis C. Yannopoulos ◽  
Alexander C. Demetracopoulos
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Vital Role ◽  
Sediment Deposition ◽  
Global Climate Models ◽  
Exceedance Probability ◽  
Climate Change Effects ◽  
Management Scenario ◽  
Supply Capacity

Freshwater resources are limited and seasonally and spatially unevenly distributed. Thus, in water resources management plans, storage reservoirs play a vital role in safeguarding drinking, irrigation, hydropower and livestock water supply. In the last decades, the dams’ negative effects, such as fragmentation of water flow and sediment transport, are considered in decision-making, for achieving an optimal balance between human needs and healthy riverine and coastal ecosystems. Currently, operation of existing reservoirs is challenged by increasing water demand, climate change effects and active storage reduction due to sediment deposition, jeopardizing their supply capacity. This paper proposes a methodological framework to reassess supply capacity and management resilience for an existing reservoir under these challenges. Future projections are derived by plausible climate scenarios and global climate models and by stochastic simulation of historic data. An alternative basic reservoir management scenario with a very low exceedance probability is derived. Excess water volumes are investigated under a probabilistic prism for enabling multiple-purpose water demands. Finally, this method is showcased to the Ladhon Reservoir (Greece). The probable total benefit from water allocated to the various water uses is estimated to assist decision makers in examining the tradeoffs between the probable additional benefit and risk of exceedance.

scholarly journals Projecting heat-related excess mortality under climate change scenarios in China

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Excess Mortality ◽  
Climate Models ◽  
Global Climate ◽  
Specific Effect ◽  
Northern China ◽  
The Elderly ◽  
Population Ageing ◽  
Global Climate Models ◽  
Climate Change Scenarios

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

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