scholarly journals Reconstruction of daily snowfall accumulation at 5.5 km resolution over Dronning Maud Land, Antarctica, from 1850 to 2014 using an analog-based downscaling technique

2021 ◽  
Author(s):  
Nicolas Ghilain ◽  
Stéphane Vannitsem ◽  
Quentin Dalaiden ◽  
Hugues Goosse ◽  
Lesley De Cruz ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Ice Core ◽  
General Circulation Models ◽  
Past Century ◽  
The Past ◽  
Dronning Maud Land ◽  
Ice Core Records

Abstract. The surface mass balance (SMB) over the Antarctic Ice Sheet displays large temporal and spatial variations. Due to the complex Antarctic topography, modelling the climate at high resolution is crucial to accurately represent the dynamics of SMB. While ice core records provide a means to infer the SMB over centuries, the view is very spatially constrained. General circulation models (GCMs) estimate its spatial distribution over centuries, but with a resolution that is too coarse to capture the large variations due to local orographic effects. We have therefore explored a methodology to statistically downscale snowfall accumulation, the primary driver of SMB, from climate model historical simulations (1850–present day) over the coastal region of Dronning Maud Land. An analog method is set up over a period of 30 years with the ERA-Interim and ERA5 reanalyses (1979–2010 AD) and associated with snowfall daily accumulation forecasts from the Regional Atmospheric Climate Model (RACMO2.3) at 5.5 km spatial resolution over Dronning Maud in East Antarctica. The same method is then applied to the period from 1850 to present day using an ensemble of ten members from the CESM2 model. This method enables to derive a spatial distribution of the accumulation of snowfall, the principal driver of the SMB variability over the region. A new dataset of daily and yearly snowfall accumulation based on this methodology is presented in this paper (MASS2ANT dataset, https://doi.org/10.5281/zenodo.4287517, Ghilain et al. (2021)), along with comparisons with ice core data and available spatial reconstructions. It offers a more detailed spatio-temporal view of the changes over the past 150 years compared to other available datasets, allowing a possible connection with the ice core records, and provides information that may be useful in identifying the large-scale patterns associated to the local precipitation conditions and their changes over the past century.

scholarly journals A climate model intercomparison for the Antarctic region: present and past

2012 ◽  
Vol 8 (2) ◽  
pp. 803-814 ◽  
Author(s):  
M. N. A. Maris ◽  
B. de Boer ◽  
J. Oerlemans
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Reference Data ◽  
Regional Climate ◽  
Ice Core ◽  
Ice Sheet ◽  
General Circulation Models ◽  
Antarctic Region ◽  
The Past ◽  
The Antarctic

Abstract. Eighteen General Circulation Models (GCMs) are compared to reference data for the present, the Mid-Holocene (MH) and the Last Glacial Maximum (LGM) for the Antarctic region. The climatology produced by a regional climate model is taken as a reference climate for the present. GCM results for the past are compared to ice-core data. The goal of this study is to find the best GCM that can be used to drive an ice sheet model that simulates the evolution of the Antarctic Ice Sheet. Because temperature and precipitation are the most important climate variables when modelling the evolution of an ice sheet, these two variables are considered in this paper. This is done by ranking the models according to how well their output corresponds with the references. In general, present-day temperature is simulated well, but precipitation is overestimated compared to the reference data. Another finding is that model biases play an important role in simulating the past, as they are often larger than the change in temperature or precipitation between the past and the present. Considering the results for the present-day as well as for the MH and the LGM, the best performing models are HadCM3 and MIROC 3.2.2.

scholarly journals Description and Evaluation of the specified-dynamics experiment in the Chemistry-Climate Model Initiative

2020 ◽  
Vol 20 (6) ◽  
pp. 3809-3840 ◽  
Author(s):  
Clara Orbe ◽  
David A. Plummer ◽  
Darryn W. Waugh ◽  
Huang Yang ◽  
Patrick Jöckel ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Phase 1 ◽  
General Circulation Models ◽  
Atmospheric Composition ◽  
Cycle Amplitude ◽  
Free Running ◽  
Dynamics Simulations

Abstract. We provide an overview of the REF-C1SD specified-dynamics experiment that was conducted as part of phase 1 of the Chemistry-Climate Model Initiative (CCMI). The REF-C1SD experiment, which consisted of mainly nudged general circulation models (GCMs) constrained with (re)analysis fields, was designed to examine the influence of the large-scale circulation on past trends in atmospheric composition. The REF-C1SD simulations were produced across various model frameworks and are evaluated in terms of how well they represent different measures of the dynamical and transport circulations. In the troposphere there are large (∼40 %) differences in the climatological mean distributions, seasonal cycle amplitude, and trends of the meridional and vertical winds. In the stratosphere there are similarly large (∼50 %) differences in the magnitude, trends and seasonal cycle amplitude of the transformed Eulerian mean circulation and among various chemical and idealized tracers. At the same time, interannual variations in nearly all quantities are very well represented, compared to the underlying reanalyses. We show that the differences in magnitude, trends and seasonal cycle are not related to the use of different reanalysis products; rather, we show they are associated with how the simulations were implemented, by which we refer both to how the large-scale flow was prescribed and to biases in the underlying free-running models. In most cases these differences are shown to be as large or even larger than the differences exhibited by free-running simulations produced using the exact same models, which are also shown to be more dynamically consistent. Overall, our results suggest that care must be taken when using specified-dynamics simulations to examine the influence of large-scale dynamics on composition.

scholarly journals Reconciling the surface temperature–surface mass balance relationship in models and ice cores in Antarctica over the last two centuries

2020 ◽  
Author(s):  
Marie G. P. Cavitte ◽  
Quentin Dalaiden ◽  
Hugues Goosse ◽  
Jan T. M. Lenaerts ◽  
Elizabeth R. Thomas
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Ice Core ◽  
Ice Sheets ◽  
Ice Cores ◽  
Surface Mass Balance ◽  
Weak Correlation ◽  
Surface Mass ◽  
The Past ◽  
Ice Core Records

Abstract. Ice cores are an important record of the past surface mass balance (SMB) of ice sheets, with SMB mitigating the ice sheets’ sea level impact over the recent decades. For the Antarctic Ice Sheet (AIS), SMB is dominated by large-scale atmospheric circulation, which collects warm moist air from further north and releases it in the form of snow as widespread accumulation or focused atmospheric rivers on the continent. This implies that the snow deposited at the surface of the AIS should record strongly coupled SMB and surface air temperature (SAT) variations. Ice cores use δ18O as a proxy for SAT as they do not record SAT directly. Here, using isotope-enabled global climate models and the RACMO2.3 regional climate model, we calculate positive SMB-SAT and δ18O-SMB correlations over ∼90 % of the AIS. The high spatial resolution of the RACMO2.3 model allows us to highlight a number of areas where SMB and SAT are not correlated, and show that wind-driven processes acting locally, such as Foehn and katabatic effects, can overwhelm the large-scale atmospheric input in SMB and SAT responsible for the positive SMB-SAT correlations. We focus in particular on Dronning Maud Land, East Antarctica, where the ice promontories clearly show these wind-induced effects. However, using the PAGES2k ice core compilations of SMB and δ18O of Thomas et al. (2017) and Stenni et al. (2017), we obtain a weak correlation, on the order of 0.1, between SMB and δ18O over the past ~150 years. We obtain an equivalently weak correlation between ice core SMB and the SAT reconstruction of Nicolas and Bromwich (2014) over the past ~50 years, although the ice core sites are not spatially co-located with the areas displaying a low SMB-SAT correlation in the models. To resolve the discrepancy between the measured and modeled signals, we show that averaging the ice core records in close spatial proximity increases their SMB-SAT correlation. This increase shows that the weak measured correlation likely results from random noise present in the ice core records, but is not large enough to match the correlation calculated in the models. Our results indicate thus a positive correlation between SAT and SMB in models and ice core reconstructions but with a weaker value in observations that may be due to missing processes in models or some systematic biases in ice core data that are not removed by a simple average.

Spatial patterns of multi-centennial temperature trend in Antarctica over 0-1000 CE: insights from ice core records and modeling

2021 ◽  
Author(s):  
Zhiqiang Lyu ◽  
Hugues Goosse ◽  
Quentin Dalaiden
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Ice Core ◽  
High Sensitivity ◽  
General Circulation Models ◽  
Temperature Trend ◽  
East Antarctica ◽  
West Antarctica ◽  
Amundsen Sea ◽  
Ice Core Records

<p>Recent Antarctic surface climate change has been characterized by greater warming trends in West Antarctica than in East Antarctica. Although the changes over recent decades are well studied, the short instrumental record limits our ability to determine if such asymmetric patterns are common for Antarctica and the processes at their origin. Here, we will focus on the years 0-1000 CE as some ice core records display very contrasted trends during this period. Furthermore, the climate models are unable to reproduce the warming displayed in some reconstructions from 1 to 500 CE over East Antarctica. In order to understand the origin of these apparent incompatibilities and investigate the effect of proxy selection on regional reconstructions over 0-1000 CE, we performed several offline data assimilation experiments based on different groups of d<sup>18</sup>O records and the isotope-enabled general circulation models (iCESM). When assimilating different d18O data sets, large differences appear in the pattern of temperature trend over 0-500 CE, but the patterns over 500-1000 CE are more consistent among the various experiments. This implies that the spatial pattern of temperature trend over 0-500 CE is still uncertain because of this high sensitivity on the choice of the proxies to constrain the model results, while the pattern over 500-1000 is more robust, with the greater cooling over West Antarctica than East Antarctica. This pattern over 500-1000 CE relates to the intensifying of the low pressure centered in the Amundsen Sea, which induces enhanced southerly flow through most of WAIS.</p>

scholarly journals Climate Change Implications for Tropical Islands: Interpolating and Interpreting Statistically Downscaled GCM Projections for Management and Planning

2016 ◽  
Vol 55 (2) ◽  
pp. 265-282 ◽  
Author(s):  
Azad Henareh Khalyani ◽  
William A. Gould ◽  
Eric Harmsen ◽  
Adam Terando ◽  
Maya Quinones ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Model Averaging ◽  
General Circulation Models ◽  
Economic Effects ◽  
Drought Indices ◽  
Tropical Islands

AbstractThe potential ecological and economic effects of climate change for tropical islands were studied using output from 12 statistically downscaled general circulation models (GCMs) taking Puerto Rico as a test case. Two model selection/model averaging strategies were used: the average of all available GCMs and the average of the models that are able to reproduce the observed large-scale dynamics that control precipitation over the Caribbean. Five island-wide and multidecadal averages of daily precipitation and temperature were estimated by way of a climatology-informed interpolation of the site-specific downscaled climate model output. Annual cooling degree-days (CDD) were calculated as a proxy index for air-conditioning energy demand, and two measures of annual no-rainfall days were used as drought indices. Holdridge life zone classification was used to map the possible ecological effects of climate change. Precipitation is predicted to decline in both model ensembles, but the decrease was more severe in the “regionally consistent” models. The precipitation declines cause gradual and linear increases in drought intensity and extremes. The warming from the 1960–90 period to the 2071–99 period was 4.6°–9°C depending on the global emission scenarios and location. This warming may cause increases in CDD, and consequently increasing energy demands. Life zones may shift from wetter to drier zones with the possibility of losing most, if not all, of the subtropical rain forests and extinction risks to rain forest specialists or obligates.

scholarly journals Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM

2016 ◽  
Vol 55 (1) ◽  
pp. 173-196 ◽  
Author(s):  
Alan M. Rhoades ◽  
Xingying Huang ◽  
Paul A. Ullrich ◽  
Colin M. Zarzycki
Keyword(s):  
Sierra Nevada ◽  
General Circulation ◽  
Water Resource Management ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Winter Season ◽  
General Circulation Models ◽  
Variable Resolution

AbstractThe location, timing, and intermittency of precipitation in California make the state integrally reliant on winter-season snowpack accumulation to maintain its economic and agricultural livelihood. Of particular concern is that winter-season snowpack has shown a net decline across the western United States over the past 50 years, resulting in major uncertainty in water-resource management heading into the next century. Cutting-edge tools are available to help navigate and preemptively plan for these uncertainties. This paper uses a next-generation modeling technique—variable-resolution global climate modeling within the Community Earth System Model (VR-CESM)—at horizontal resolutions of 0.125° (14 km) and 0.25° (28 km). VR-CESM provides the means to include dynamically large-scale atmosphere–ocean drivers, to limit model bias, and to provide more accurate representations of regional topography while doing so in a more computationally efficient manner than can be achieved with conventional general circulation models. This paper validates VR-CESM at climatological and seasonal time scales for Sierra Nevada snowpack metrics by comparing them with the “Daymet,” “Cal-Adapt,” NARR, NCEP, and North American Land Data Assimilation System (NLDAS) reanalysis datasets, the MODIS remote sensing dataset, the SNOTEL observational dataset, a standard-practice global climate model (CESM), and a regional climate model (WRF Model) dataset. Overall, given California’s complex terrain and intermittent precipitation and that both of the VR-CESM simulations were only constrained by prescribed sea surface temperatures and data on sea ice extent, a 0.68 centered Pearson product-moment correlation, a negative mean SWE bias of <7 mm, an interquartile range well within the values exhibited in the reanalysis datasets, and a mean December–February extent of snow cover that is within 7% of the expected MODIS value together make apparent the efficacy of the VR-CESM framework.

scholarly journals Records of climatic changes and volcanic events in an ice core from Central Dronning Maud Land (East Antarctica) during the past century

2002 ◽  
Vol 111 (1) ◽  
pp. 39-49 ◽  
Author(s):  
V. N. Nijampurkar ◽  
D. K. Rao ◽  
H. B. Clausen ◽  
M. K. Kaul ◽  
A. Chaturvedi
Keyword(s):  
Ice Core ◽  
Climatic Changes ◽  
East Antarctica ◽  
Past Century ◽  
The Past ◽  
Volcanic Events ◽  
Dronning Maud Land

Constructing Records of Storminess

2018 ◽  
Author(s):  
Frauke Feser
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Measurement Data ◽  
General Circulation Models ◽  
Extreme Weather Events ◽  
Storm Events ◽  
Model Data ◽  
Storm Activity ◽  
The Past

Storms are characterized by high wind speeds; often large precipitation amounts in the form of rain, freezing rain, or snow; and thunder and lightning (for thunderstorms). Many different types exist, ranging from tropical cyclones and large storms of the midlatitudes to small polar lows, Medicanes, thunderstorms, or tornadoes. They can lead to extreme weather events like storm surges, flooding, high snow quantities, or bush fires. Storms often pose a threat to human lives and property, agriculture, forestry, wildlife, ships, and offshore and onshore industries. Thus, it is vital to gain knowledge about changes in storm frequency and intensity. Future storm predictions are important, and they depend to a great extent on the evaluation of changes in wind statistics of the past. To obtain reliable statistics, long and homogeneous time series over at least some decades are needed. However, wind measurements are frequently influenced by changes in the synoptic station, its location or surroundings, instruments, and measurement practices. These factors deteriorate the homogeneity of wind records. Storm indexes derived from measurements of sea-level pressure are less prone to such changes, as pressure does not show very much spatial variability as wind speed does. Long-term historical pressure measurements exist that enable us to deduce changes in storminess for more than the last 140 years. But storm records are not just compiled from measurement data; they also may be inferred from climate model data. The first numerical weather forecasts were performed in the 1950s. These served as a basis for the development of atmospheric circulation models, which were the first generation of climate models or general-circulation models. Soon afterward, model data was analyzed for storm events and cyclone-tracking algorithms were programmed. Climate models nowadays have reached high resolution and reliability and can be run not just for the past, but also for future emission scenarios which return possible future storm activity.

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