scholarly journals Projected increases in surface melt and ice loss for the Northern and Southern Patagonian Icefields

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Claudio Bravo ◽  
Deniz Bozkurt ◽  
Andrew N. Ross ◽  
Duncan J. Quincey
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Historical Period ◽  
Emission Scenarios ◽  
Recent Past ◽  
Model Data ◽  
Surface Mass ◽  
The Mean ◽  
Surface Melt ◽  
Frontal Ablation

AbstractThe Northern Patagonian Icefield (NPI) and the Southern Patagonian Icefield (SPI) have increased their ice mass loss in recent decades. In view of the impacts of glacier shrinkage in Patagonia, an assessment of the potential future surface mass balance (SMB) of the icefields is critical. We seek to provide this assessment by modelling the SMB between 1976 and 2050 for both icefields, using regional climate model data (RegCM4.6) and a range of emission scenarios. For the NPI, reductions between 1.5 m w.e. (RCP2.6) and 1.9 m w.e. (RCP8.5) were estimated in the mean SMB during the period 2005–2050 compared to the historical period (1976–2005). For the SPI, the estimated reductions were between 1.1 m w.e. (RCP2.6) and 1.5 m w.e. (RCP8.5). Recently frontal ablation estimates suggest that mean SMB in the SPI is positively biased by 1.5 m w.e., probably due to accumulation overestimation. If it is assumed that frontal ablation rates of the recent past will continue, ice loss and sea-level rise contribution will increase. The trend towards lower SMB is mostly explained by an increase in surface melt. Positive ice loss feedbacks linked to increasing in meltwater availability are expected for calving glaciers.

scholarly journals Evidence and analysis of 2012 Greenland records from spaceborne observations, a regional climate model and reanalysis data

2012 ◽  
Vol 6 (6) ◽  
pp. 4939-4976 ◽  
Author(s):  
M. Tedesco ◽  
X. Fettweis ◽  
T. Mote ◽  
J. Wahr ◽  
P. Alexander ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Reanalysis Data ◽  
Surface Mass Balance ◽  
Near Surface ◽  
Surface Mass ◽  
The Mean

Abstract. A combined analysis of remote sensing observations, regional climate model (RCM) outputs and reanalysis data over the Greenland ice sheet provides evidence that multiple records were set during summer 2012. Melt extent was the largest in the satellite era (extending up to ~ 97% of the ice sheet) and melting lasted up to ~ two months longer than the 1979–2011 mean. Model results indicate that near surface temperature was ~ 3 standard deviations (σ) above the 1958–2011 mean, while surface mass balance was ~ 3σ below the mean and runoff was 3.9σ above the mean over the same period. Albedo, exposure of bare ice and surface mass balance also set new records, as did the total mass balance with summer and annual mass changes of, respectively, −627 Gt and −574 Gt, 2σ below the 2003–2012 mean. We identify persistent anticyclonic conditions over Greenland associated with anomalies in the North Atlantic Oscillation (NAO), changes in surface conditions (e.g. albedo) and pre-conditioning of surface properties from recent extreme melting as major driving mechanisms for the 2012 records. Because of self-amplifying positive feedbacks, less positive if not increasingly negative SMB will likely occur should large-scale atmospheric circulation and induced surface characteristics observed over the past decade persist. Since the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) do not simulate the abnormal anticyclonic circulation resulting from extremely negative NAO conditions as observed over recent years, contribution to sea level rise projected under different warming scenarios will be underestimated should the trend in NAO summer values continue.

scholarly journals Evidence and analysis of 2012 Greenland records from spaceborne observations, a regional climate model and reanalysis data

2013 ◽  
Vol 7 (2) ◽  
pp. 615-630 ◽  
Author(s):  
M. Tedesco ◽  
X. Fettweis ◽  
T. Mote ◽  
J. Wahr ◽  
P. Alexander ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Regional Climate Model ◽  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Reanalysis Data ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
The Mean

Abstract. A combined analysis of remote sensing observations, regional climate model (RCM) outputs and reanalysis data over the Greenland ice sheet provides evidence that multiple records were set during summer 2012. Melt extent was the largest in the satellite era (extending up to ∼97% of the ice sheet) and melting lasted up to ∼2 months longer than the 1979–2011 mean. Model results indicate that near surface temperature was ∼3 standard deviations (σ) above the 1958–2011 mean, while surface mass balance (SMB) was ∼3σ below the mean and runoff was 3.9σ above the mean over the same period. Albedo, exposure of bare ice and surface mass balance also set new records, as did the total mass balance with summer and annual mass changes of, respectively, −627 Gt and −574 Gt, 2σ below the 2003–2012 mean. We identify persistent anticyclonic conditions over Greenland associated with anomalies in the North Atlantic Oscillation (NAO), changes in surface conditions (e.g., albedo, surface temperature) and preconditioning of surface properties from recent extreme melting as major driving mechanisms for the 2012 records. Less positive if not increasingly negative SMB will likely occur should these characteristics persist.

scholarly journals Observationally constrained surface mass balance of Larsen C ice shelf, Antarctica

2017 ◽  
Vol 11 (6) ◽  
pp. 2411-2426 ◽  
Author(s):  
Peter Kuipers Munneke ◽  
Daniel McGrath ◽  
Brooke Medley ◽  
Adrian Luckman ◽  
Suzanne Bevan ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Snow Accumulation ◽  
Airborne Radar ◽  
Surface Mass Balance ◽  
Spatial And Temporal Patterns ◽  
Ice Shelf ◽  
The West ◽  
Surface Mass

Abstract. The surface mass balance (SMB) of the Larsen C ice shelf (LCIS), Antarctica, is poorly constrained due to a dearth of in situ observations. Combining several geophysical techniques, we reconstruct spatial and temporal patterns of SMB over the LCIS. Continuous time series of snow height (2.5–6 years) at five locations allow for multi-year estimates of seasonal and annual SMB over the LCIS. There is high interannual variability in SMB as well as spatial variability: in the north, SMB is 0.40 ± 0.06 to 0.41 ± 0.04 m w.e. year−1, while farther south, SMB is up to 0.50 ± 0.05 m w.e. year−1. This difference between north and south is corroborated by winter snow accumulation derived from an airborne radar survey from 2009, which showed an average snow thickness of 0.34 m w.e. north of 66° S, and 0.40 m w.e. south of 68° S. Analysis of ground-penetrating radar from several field campaigns allows for a longer-term perspective of spatial variations in SMB: a particularly strong and coherent reflection horizon below 25–44 m of water-equivalent ice and firn is observed in radargrams collected across the shelf. We propose that this horizon was formed synchronously across the ice shelf. Combining snow height observations, ground and airborne radar, and SMB output from a regional climate model yields a gridded estimate of SMB over the LCIS. It confirms that SMB increases from north to south, overprinted by a gradient of increasing SMB to the west, modulated in the west by föhn-induced sublimation. Previous observations show a strong decrease in firn air content toward the west, which we attribute to spatial patterns of melt, refreezing, and densification rather than SMB.

scholarly journals Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R<sup>2</sup>D<sup>2</sup>) bias correction

2018 ◽  
Vol 22 (6) ◽  
pp. 3175-3196 ◽  
Author(s):  
Mathieu Vrac
Keyword(s):  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Grid Cell ◽  
Dependence Structure ◽  
Historical Period ◽  
Temporal Properties ◽  
Temperature And Precipitation ◽  
Climate Simulations ◽  
Site Dependence

Abstract. Climate simulations often suffer from statistical biases with respect to observations or reanalyses. It is therefore common to correct (or adjust) those simulations before using them as inputs into impact models. However, most bias correction (BC) methods are univariate and so do not account for the statistical dependences linking the different locations and/or physical variables of interest. In addition, they are often deterministic, and stochasticity is frequently needed to investigate climate uncertainty and to add constrained randomness to climate simulations that do not possess a realistic variability. This study presents a multivariate method of rank resampling for distributions and dependences (R2D2) bias correction allowing one to adjust not only the univariate distributions but also their inter-variable and inter-site dependence structures. Moreover, the proposed R2D2 method provides some stochasticity since it can generate as many multivariate corrected outputs as the number of statistical dimensions (i.e., number of grid cell  ×  number of climate variables) of the simulations to be corrected. It is based on an assumption of stability in time of the dependence structure – making it possible to deal with a high number of statistical dimensions – that lets the climate model drive the temporal properties and their changes in time. R2D2 is applied on temperature and precipitation reanalysis time series with respect to high-resolution reference data over the southeast of France (1506 grid cell). Bivariate, 1506-dimensional and 3012-dimensional versions of R2D2 are tested over a historical period and compared to a univariate BC. How the different BC methods behave in a climate change context is also illustrated with an application to regional climate simulations over the 2071–2100 period. The results indicate that the 1d-BC basically reproduces the climate model multivariate properties, 2d-R2D2 is only satisfying in the inter-variable context, 1506d-R2D2 strongly improves inter-site properties and 3012d-R2D2 is able to account for both. Applications of the proposed R2D2 method to various climate datasets are relevant for many impact studies. The perspectives of improvements are numerous, such as introducing stochasticity in the dependence itself, questioning its stability assumption, and accounting for temporal properties adjustment while including more physics in the adjustment procedures.

scholarly journals Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 262 ◽  
Author(s):  
Coraline Wyard ◽  
Sébastien Doutreloup ◽  
Alexandre Belleflamme ◽  
Martin Wild ◽  
Xavier Fettweis
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Radiative Flux ◽  
Added Value ◽  
Historical Trends ◽  
The Mean

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

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

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.

scholarly journals Impact of updated radiative transfer scheme in RACMO2.3p3 on the surface mass and energy budget of the Greenland ice sheet

2020 ◽  
Author(s):  
Christiaan T. van Dalum ◽  
Willem Jan van de Berg ◽  
Michiel R. van den Broeke
Keyword(s):  
Radiative Transfer ◽  
Energy Budget ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Melt ◽  
Transfer Scheme ◽  
Surface Mass ◽  
The Impact

Abstract. This study evaluates the impact of a new snow and ice albedo and radiative transfer scheme on the surface mass and energy budget for the Greenland ice sheet in the latest version of the regional climate model RACMO2, version 2.3p3. We also evaluate the modeled (sub)surface temperature and snow melt, as subsurface heating by radiation penetration now occurs. The results are compared to the previous model version and are evaluated against stake measurements and automatic weather station data of the K-transect and PROMICE projects. In addition, subsurface snow temperature profiles are compared at the K-transect, Summit and southeast Greenland. The surface mass balance is in good agreement with observations, and only changes considerably with respect to the previous RACMO2 version around the ice margins and in the percolation zone. Snow melt and refreezing, on the other hand, are changed more substantially in various regions due to the changed albedo representation, subsurface energy absorption and melt water percolation. Internal heating leads to considerably higher snow temperatures in summer, in agreement with observations, and introduces a shallow layer of subsurface melt.

scholarly journals PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

2021 ◽  
Author(s):  
Charles Pelletier ◽  
Thierry Fichefet ◽  
Hugues Goosse ◽  
Konstanze Haubner ◽  
Samuel Helsen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Horizontal Resolution ◽  
Fine Tuning ◽  
Polar Regions ◽  
Surface Mass ◽  
The Impact ◽  
Fully Coupled

Abstract. We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

The Mesoscale Response to Global Warming over the Pacific Northwest Evaluated Using a Regional Climate Model Ensemble

2021 ◽  
pp. 1-56
Keyword(s):  
Global Warming ◽  
Pacific Northwest ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Regional Climate Models ◽  
Winter Precipitation ◽  
Historical Period ◽  
Continental Interior

This paper describes the downscaling of an ensemble of twelve GCMs using the WRF model at 12-km grid spacing over the period 1970-2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP 8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. April 1 snowpack declines are large over the lower to middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCM’s producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the 21st century.

Decomposition of Future Moisture Flux Changes over the Tibetan Plateau Projected by Global and Regional Climate Models

2019 ◽  
Vol 32 (20) ◽  
pp. 7037-7053
Author(s):  
Hongwen Zhang ◽  
Yanhong Gao ◽  
Jianwei Xu ◽  
Yu Xu ◽  
Yingsha Jiang
Keyword(s):  
Tibetan Plateau ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Moisture Flux ◽  
Historical Period ◽  
The Tibetan Plateau ◽  
Dynamic Component ◽  
Coarse Resolution ◽  
The Future

Abstract To meet the requirement of high-resolution datasets for many applications, a dynamical downscaling approach using a regional climate model (the WRF Model) driven by a global climate model (CCSM4) has been adopted. This study focuses on projections of future moisture flux changes over the Tibetan Plateau (TP). First, the downscaling results for the historical period (1980–2005) are evaluated for precipitation P, evaporation E, and precipitation minus evaporation P − E against Global Land Data Assimilation System (GLDAS) data. The mechanism of P − E changes is analyzed by decomposition into dynamic, thermodynamic, and transient eddy components. Whether the historical period changes and mechanisms continue into the future (2010–2100) is investigated using the WRF and CCSM model projections under the RCP4.5 and RCP8.5 scenarios. Compared with coarse-resolution forcing, downscaling was found to better reproduce the historical spatial patterns and seasonal mean of annual average P, E, and P − E over the TP. WRF projects a diverse spatial variation of P − E changes, with an increase in the northern TP and a decrease in the southern TP, compared with the uniform increase in CCSM. The dynamic component dominates P − E changes for the historical period in both the CCSM and WRF projections. In the future, however, the thermodynamic component in CCSM dominates P − E changes under RCP4.5 and RCP8.5 from the near-term (2010–39) to the long-term (2070–99) future. Unlike the CCSM projections, the WRF projections reproduce the mechanism seen in the historical period—that is, the dynamic component dominates P − E changes. Furthermore, future P − E changes in the dynamical downscaling are less sensitive to warming than its coarse-resolution forcing.

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