National scale climate change impact assessment – investigating long-term variations in the climate change signal for groundwater levels across geologies and aquifers

Mapping Intimacies ◽

10.5194/egusphere-egu2020-4741 ◽

2020 ◽

Author(s):

Ida Bjørnholt Karlsson ◽

Luc Taliesin Eisenbruchner ◽

Jacob Kidmose ◽

Anker Lajer Højberg

Keyword(s):

Climate Change ◽

Hydrological Model ◽

Climate Model ◽

Climate Change Signal ◽

Special Focus ◽

Groundwater System ◽

Phreatic Surface ◽

Near Surface ◽

Marine Sand

The effect of climate change on groundwater system is still not extensively understood. Studies often focuses on changes in recharge to the groundwater system but rarely investigate the resulting impacts on hydraulic head levels especially the spatial distribution of the change across larger domains.Only few countries in the world have access to a detailed national hydrological model, and fewer still have done nationwide climate change assessments. This study applies a combination of the newest updated national hydrological model for the entire Denmark (the DK-model 2019, http://dk.vandmodel.dk/in-english/) and 20 climate model projections from the Euro-Cordex project (Jacob et al., 2014) for the RCP4.5 and the RCP8.5 emission scenario (4 and 16 runs respectively). The climate dataset are bias-corrected for the Danish area using double Gamma distribution-based scaling for temperature and precipitation (Pasten-Zapata et al., 2019).This large dataset is used to evaluate the distribution of the magnitude and direction of changes with special focus on the phreatic surface and the main water-bearing groundwater layers for drinking water consumption in Denmark. The spatial variations in the near-surface impact signal across the entire country is also analyzed, as different Quaternary geology is represented from sandy layers in the west to moraine clay tills in the east and marine sand and clay to the north. The climate dataset is a successive time series from 1970ties to the end of the century and thus also enables an analysis of long-term changes in the state of the groundwater system and aquifers.&#160;&#160;&#160;Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., D&#233;qu&#233;, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kr&#246;ner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: new high-resolution climate change projections for European impact research, Regional Environmental Change, 14, 563-578, 10.1007/s10113-013-0499-2, 2014.Pasten-Zapata, E., Sonnenborg, T. O., and Refsgaard, J. C.: Climate change: Sources of uncertainty in precipitation and temperature projections for Denmark, Geological Survey of Denmark and Greenland Bulletin 43, e2019430102-2019430101-e2019430102-2019430106, https://doi.org/10.34194/GEUSB-201943-01-02 2019.&#160;

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Uncertainty of Hydrological Model Components in Climate Change Studies over Two Nordic Quebec Catchments

Journal of Hydrometeorology ◽

10.1175/jhm-d-17-0002.1 ◽

2018 ◽

Vol 19 (1) ◽

pp. 27-46 ◽

Cited By ~ 8

Author(s):

Magali Troin ◽

Richard Arsenault ◽

Jean-Luc Martel ◽

François Brissette

Keyword(s):

Climate Change ◽

Climate Variability ◽

Hydrological Model ◽

Climate Model ◽

Global Climate Model ◽

Substantial Contribution ◽

Climate Change Signal ◽

Natural Climate Variability ◽

Degree Day ◽

Natural Climate

Abstract Projected climate change effects on hydrology are investigated for the 2041–60 horizon under the A2 emission scenarios using a multimodel approach over two snowmelt-dominated catchments in Canada. An ensemble of 105 members was obtained by combining seven snow models (SMs), five potential evapotranspiration (PET) methods, and three hydrological model (HM) structures. The study was performed using high-resolution simulations from the Canadian Regional Climate Model (CRCM–15 km) driven by two members of the third-generation Canadian Coupled Global Climate Model (CGCM3). This study aims to compare various combinations of SM–PET–HM in terms of their ability to simulate streamflows under the current climate and to evaluate how they affect the assessment of the climate change–induced hydrological impacts at the catchment scale. The variability of streamflow response caused by the use of different SMs (degree-day versus degree-day/energy balance), PET methods (temperature-based versus radiation-based methods), and HM structures is evaluated, as well as the uncertainty due to the natural climate variability (CRCM intermember variability). The hydroclimatic simulations cover 1961–90 in the present period and 2041–60 in the future period. The ensemble spread of the climate change signal on streamflow is large and varies with catchments. Using the variance decomposition on three hydrologic indicators, the HM structure was found to make the most substantial contribution to uncertainty, followed by the choice of the PET methods or natural climate variability, depending on the hydrologic indicator and the catchment. Snow models played a minor, almost negligible role in the assessment of the climate change impacts on streamflow for the study catchments.

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A study of long-term climate change in a simple seasonal nonlinear climate model

Climate Dynamics ◽

10.1007/bf00210580 ◽

1991 ◽

Vol 6 (1) ◽

pp. 35-41 ◽

Cited By ~ 2

Author(s):

R Q Lin ◽

H Kreiss ◽

W J Kuang ◽

L Y Leung

Keyword(s):

Climate Change ◽

Climate Model

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On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

Climate Dynamics ◽

10.1007/s00382-017-3547-7 ◽

2017 ◽

Vol 49 (11-12) ◽

pp. 3813-3838 ◽

Cited By ~ 24

Author(s):

Thierry C. Fotso-Nguemo ◽

Derbetini A. Vondou ◽

Wilfried M. Pokam ◽

Zéphirin Yepdo Djomou ◽

Ismaïla Diallo ◽

...

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Central Africa ◽

Added Value ◽

Climate Change Signal

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Evaluating quantile-based bias adjustment methods for climate change scenarios

10.5194/hess-2021-498 ◽

2021 ◽

Author(s):

Fabian Lehner ◽

Imran Nadeem ◽

Herbert Formayer

Keyword(s):

Climate Change ◽

Climate Models ◽

Climate Model ◽

Meteorological Data ◽

Climate Change Signal ◽

Historical Period ◽

Climate Change Scenarios ◽

Statistical Bias ◽

Bias Adjustment ◽

Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

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Hydrological impacts of climate change on small ungauged catchments – results from a global climate model–regional climate model–hydrologic model chain

Natural Hazards and Earth System Science ◽

10.5194/nhess-20-2133-2020 ◽

2020 ◽

Vol 20 (8) ◽

pp. 2133-2155

Author(s):

Aynalem T. Tsegaw ◽

Marie Pontoppidan ◽

Erle Kristvik ◽

Knut Alfredsen ◽

Tone M. Muthanna

Keyword(s):

Climate Change ◽

Hydrological Model ◽

Climate Model ◽

Regional Climate ◽

Reference Period ◽

Future Period ◽

The Mean ◽

Model Chain ◽

Small Catchments ◽

Impacts Of Climate Change

Abstract. Climate change is one of the greatest threats currently facing the world's environment. In Norway, a change in climate will strongly affect the pattern, frequency, and magnitudes of stream flows. However, it is challenging to quantify to what extent the change will affect the flow patterns and floods from small rural catchments due to the unavailability or inadequacy of hydro-meteorological data for the calibration of hydrological models and due to the tailoring of methods to a small-scale level. To provide meaningful climate impact studies at the level of small catchments, it is therefore beneficial to use high-spatial- and high-temporal-resolution climate projections as input to a high-resolution hydrological model. In this study, we used such a model chain to assess the impacts of climate change on the flow patterns and frequency of floods in small ungauged rural catchments in western Norway. We used a new high-resolution regional climate projection, with improved performance regarding the precipitation distribution, and a regionalized hydrological model (distance distribution dynamics) between a reference period (1981–2011) and a future period (2070–2100). The flow-duration curves for all study catchments show more wet periods in the future than during the reference period. The results also show that in the future period, the mean annual flow increases by 16 % to 33 %. The mean annual maximum floods increase by 29 % to 38 %, and floods of 2- to 200-year return periods increase by 16 % to 43 %. The results are based on the RCP8.5 scenario from a single climate model simulation tailored to the Bergen region in western Norway, and the results should be interpreted in this context. The results should therefore be seen in consideration of other scenarios for the region to address the uncertainty. Nevertheless, the study increases our knowledge and understanding of the hydrological impacts of climate change on small catchments in the Bergen area in the western part of Norway.

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Estimation of Water Storage Changes in Small Endorheic Lakes in Northern Kazakhstan; The Effect of Climate Change and Anthropogenic Influences

10.20944/preprints201712.0045.v1 ◽

2017 ◽

Author(s):

Vadim Yapiyev ◽

Kanat Samarkhanov ◽

Dauren Zhumabayev ◽

Nazym Tulegenova ◽

Saltanat Jumassultanova ◽

...

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Water Resources ◽

Water Balance ◽

Climate Model ◽

Human Impacts ◽

Water Storage ◽

Minor Importance ◽

Climatic Data

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.

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Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

10.21203/rs.3.rs-725819/v1 ◽

2021 ◽

Author(s):

Antoine Doury ◽

Samuel Somot ◽

Sébastien Gadat ◽

Aurélien Ribes ◽

Lola Corre

Keyword(s):

Climate Change ◽

Network Architecture ◽

Large Scale ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Future Climate ◽

Near Surface ◽

The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

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The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

Geoscientific Model Development ◽

10.5194/gmd-9-3461-2016 ◽

2016 ◽

Vol 9 (9) ◽

pp. 3461-3482 ◽

Cited By ~ 251

Author(s):

Brian C. O'Neill ◽

Claudia Tebaldi ◽

Detlef P. van Vuuren ◽

Veronika Eyring ◽

Pierre Friedlingstein ◽

...

Keyword(s):

Climate Change ◽

Land Use ◽

21St Century ◽

Integrated Assessment ◽

Climate Model ◽

Model Intercomparison ◽

Wide Range ◽

Scenario Model ◽

Intercomparison Project

Abstract. Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.

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Space-based geoengineering: Challenges and requirements

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1243/09544062jmes1439 ◽

2009 ◽

Vol 224 (3) ◽

pp. 571-580 ◽

Cited By ~ 18

Author(s):

C R McInnes

Keyword(s):

Climate Change ◽

Carbon Dioxide ◽

Large Scale ◽

Climate Model ◽

Carbon Dioxide Concentration ◽

Complex Solution ◽

Lagrange Point ◽

Simple Climate Model ◽

Earth’S Climate

The prospect of engineering the Earth's climate (geoengineering) raises a multitude of issues associated with climatology, engineering on macroscopic scales, and indeed the ethics of such ventures. Depending on personal views, such large-scale engineering is either an obvious necessity for the deep future, or yet another example of human conceit. In this article a simple climate model will be used to estimate requirements for engineering the Earth's climate, principally using space-based geoengineering. Active cooling of the climate to mitigate anthropogenic climate change due to a doubling of the carbon dioxide concentration in the Earth's atmosphere is considered. This representative scenario will allow the scale of the engineering challenge to be determined. It will be argued that simple occulting discs at the interior Lagrange point may represent a less complex solution than concepts for highly engineered refracting discs proposed recently. While engineering on macroscopic scales can appear formidable, emerging capabilities may allow such ventures to be seriously considered in the long term. This article is not an exhaustive review of geoengineering, but aims to provide a foretaste of the future opportunities, challenges, and requirements for space-based geoengineering ventures.

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