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 A model comparison study for the Antarctic region: present and past

2011 ◽  
Vol 7 (5) ◽  
pp. 3583-3607
Author(s):  
M. N. A. Maris ◽  
B. de Boer ◽  
J. Oerlemans
Keyword(s):  
Model Comparison ◽  
Climate Models ◽  
Climate Model ◽  
Reference Data ◽  
Ice Sheet ◽  
Global Climate Models ◽  
Reference State ◽  
Antarctic Region ◽  
The Past ◽  
The Antarctic

Abstract. Eighteen global climate models (GCMs) are compared to reference data for the present, the mid-Holocene (MH) and the last glacial maximum (LGM) for the Antarctic region. For the present, the reference data come from a regional climate model. GCM results for the past are compared to ice core data. The goal of this study is to find the best GCM to model 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. In general, present-day temperature is simulated well, but precipitation is overestimated compared to the reference state. Some other findings are that the air above ice shelves is too warm and precipitation in the coastal region of the western peninsula is underestimated by the models, as compared to the present-day reference state. Furthermore, 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 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 The influence of ice sheets on temperature during the past 38 million years inferred from a one-dimensional ice sheet–climate model

2017 ◽  
Vol 13 (9) ◽  
pp. 1243-1257 ◽  
Author(s):  
Lennert B. Stap ◽  
Roderik S. W. van de Wal ◽  
Bas de Boer ◽  
Richard Bintanja ◽  
Lucas J. Lourens
Keyword(s):  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Atmospheric Temperature ◽  
Temperature Changes ◽  
One Dimensional ◽  
Ice Volume ◽  
The Past ◽  
Polar Amplification ◽  
The Antarctic

Abstract. Since the inception of the Antarctic ice sheet at the Eocene–Oligocene transition (∼ 34 Myr ago), land ice has played a crucial role in Earth's climate. Through feedbacks in the climate system, land ice variability modifies atmospheric temperature changes induced by orbital, topographical, and greenhouse gas variations. Quantification of these feedbacks on long timescales has hitherto scarcely been undertaken. In this study, we use a zonally averaged energy balance climate model bidirectionally coupled to a one-dimensional ice sheet model, capturing the ice–albedo and surface–height–temperature feedbacks. Potentially important transient changes in topographic boundary conditions by tectonics and erosion are not taken into account but are briefly discussed. The relative simplicity of the coupled model allows us to perform integrations over the past 38 Myr in a fully transient fashion using a benthic oxygen isotope record as forcing to inversely simulate CO2. Firstly, we find that the results of the simulations over the past 5 Myr are dependent on whether the model run is started at 5 or 38 Myr ago. This is because the relation between CO2 and temperature is subject to hysteresis. When the climate cools from very high CO2 levels, as in the longer transient 38 Myr run, temperatures in the lower CO2 range of the past 5 Myr are higher than when the climate is initialised at low temperatures. Consequently, the modelled CO2 concentrations depend on the initial state. Taking the realistic warm initialisation into account, we come to a best estimate of CO2, temperature, ice-volume-equivalent sea level, and benthic δ18O over the past 38 Myr. Secondly, we study the influence of ice sheets on the evolution of global temperature and polar amplification by comparing runs with ice sheet–climate interaction switched on and off. By passing only albedo or surface height changes to the climate model, we can distinguish the separate effects of the ice–albedo and surface–height–temperature feedbacks. We find that ice volume variability has a strong enhancing effect on atmospheric temperature changes, particularly in the regions where the ice sheets are located. As a result, polar amplification in the Northern Hemisphere decreases towards warmer climates as there is little land ice left to melt. Conversely, decay of the Antarctic ice sheet increases polar amplification in the Southern Hemisphere in the high-CO2 regime. Our results also show that in cooler climates than the pre-industrial, the ice–albedo feedback predominates the surface–height–temperature feedback, while in warmer climates they are more equal in strength.

scholarly journals How Well Do the CMIP5 Models Simulate the Antarctic Atmospheric Energy Budget?

2015 ◽  
Vol 28 (20) ◽  
pp. 7933-7942 ◽  
Author(s):  
Michael Previdi ◽  
Karen L. Smith ◽  
Lorenzo M. Polvani
Keyword(s):  
Sea Ice ◽  
Energy Budget ◽  
General Circulation ◽  
Climate Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Secondary Importance ◽  
Sea Ice Extent ◽  
Atmospheric Energy ◽  
The Antarctic

Abstract The authors evaluate 23 coupled atmosphere–ocean general circulation models from phase 5 of CMIP (CMIP5) in terms of their ability to simulate the observed climatological mean energy budget of the Antarctic atmosphere. While the models are shown to capture the gross features of the energy budget well [e.g., the observed two-way balance between the top-of-atmosphere (TOA) net radiation and horizontal convergence of atmospheric energy transport], the simulated TOA absorbed shortwave (SW) radiation is too large during austral summer. In the multimodel mean, this excessive absorption reaches approximately 10 W m−2, with even larger biases (up to 25–30 W m−2) in individual models. Previous studies have identified similar climate model biases in the TOA net SW radiation at Southern Hemisphere midlatitudes and have attributed these biases to errors in the simulated cloud cover. Over the Antarctic, though, model cloud errors are of secondary importance, and biases in the simulated TOA net SW flux are instead driven mainly by biases in the clear-sky SW reflection. The latter are likely related in part to the models’ underestimation of the observed annual minimum in Antarctic sea ice extent, thus underscoring the importance of sea ice in the Antarctic energy budget. Finally, substantial differences in the climatological surface energy fluxes between existing observational datasets preclude any meaningful assessment of model skill in simulating these fluxes.

scholarly journals On the potential use of glacier and permafrost observations for verification of climate models

1997 ◽  
Vol 25 ◽  
pp. 400-406 ◽  
Author(s):  
Martin Beniston ◽  
Wilfried Haeberli ◽  
Martin Hoelzle ◽  
Alan Taylor
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Model Performance ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Model Verification ◽  
Dominant Feature

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.

Robust Late 21st Century Shift in the Regional Monsoons in RegCM-CORDEX Simulations

2020 ◽  
Author(s):  
Moetasim Ashfaq ◽  
Tereza Cavazos ◽  
Michelle Reboita ◽  
José Abraham Torres-Alavez ◽  
Eun-Soon Im ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Lower Boundary ◽  
Coupled Model ◽  
General Circulation Models ◽  
Monsoon Onset ◽  
Historical Period ◽  
Monsoon Period

<p>We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability. </p>

scholarly journals Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods

2020 ◽  
Author(s):  
Yao Tong ◽  
Xuejie Gao ◽  
Zhenyu Han ◽  
Yaqi Xu ◽  
Ying Xu ◽  
...  
Keyword(s):  
Bias Correction ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
General Circulation Models ◽  
Grid Spacing ◽  
Quantile Mapping ◽  
Temperature And Precipitation ◽  
June July August ◽  
June July

Abstract Two different bias correction methods, the quantile mapping (QM) and quantile delta mapping (QDM), are applied to simulated daily temperature and precipitation over China from a set of 21st century regional climate model (the ICTP RegCM4) projections. The RegCM4 is driven by five different general circulation models (GCMs) under the representative concentration pathway RCP4.5 at a grid spacing of 25 km using the CORDEX East Asia domain. The focus is on mean temperature and precipitation in December–January–February (DJF) and June–July–August (JJA). The impacts of the two methods on the present day biases and future change signals are investigated. Results show that both the QM and QDM methods are effective in removing the systematic model biases during the validation period. For the future changes, the QDM preserves the temperature change signals well, in both magnitude and spatial distribution, while the QM artificially modifies the change signal by decreasing the warming and modifying the patterns of change. For precipitation, both methods preserve the change signals well but they produce greater magnitude of the projected increase, especially the QDM. We also show that the effects of bias correction are variable- and season-dependent. Our results show that different bias correction methods can affect in different way the simulated change signals, and therefore care has to be taken in carrying out the bias correction process.

scholarly journals Brief Communication: Upper air relaxation in RACMO2 significantly improves modelled interannual SMB variability in Antarctica

2015 ◽  
Vol 9 (5) ◽  
pp. 4981-4995
Author(s):  
W. J. van de Berg ◽  
B. Medley
Keyword(s):  
Regional Climate Model ◽  
Interannual Variability ◽  
Antarctic Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
West Antarctica ◽  
Steep Topography ◽  
The Antarctic

Abstract. The regional climate model RACMO2 has been a powerful tool for improving SMB estimates from GCMs or reanalyses. However, new yearly SMB observations for West Antarctica show that the modelled interannual variability in SMB is poorly simulated by RACMO2, in contrast to ERA-Interim, which resolves this variability well. In an attempt to remedy RACMO2 performance, we included additional upper air relaxation (UAR) in RACMO2. With UAR, the correlation to observations is similar for RACMO2 and ERA-Interim. The spatial SMB patterns and ice sheet integrated SMB modelled using UAR remain very similar to the estimates of RACMO2 without UAR. We only observe an upstream smoothing of precipitation in regions with very steep topography like the Antarctic Peninsula. We conclude that UAR is a useful improvement for RCM simulations, although results in regions with steep topography should be treated with care.

scholarly journals Regional Climate Model Projections and Uncertainties of U.S. Summer Heat Waves

2010 ◽  
Vol 23 (16) ◽  
pp. 4447-4458 ◽  
Author(s):  
Kenneth E. Kunkel ◽  
Xin-Zhong Liang ◽  
Jinhong Zhu
Keyword(s):  
United States ◽  
Regional Climate Model ◽  
Heat Wave ◽  
General Circulation ◽  
Climate Model ◽  
Heat Waves ◽  
Regional Climate ◽  
General Circulation Models ◽  
Threshold Temperature ◽  
Wave Characteristics

Abstract Regional climate model (RCM) simulations, driven by low and high climate-sensitivity coupled general circulation models (CGCMs) under various future emissions scenarios, were compared to projected changes in heat wave characteristics. The RCM downscaling reduces the CGCM biases in heat wave threshold temperature by a factor of 2, suggesting a higher credibility in the future projections. All of the RCM simulations suggest that there is a high probability of heat waves of unprecedented severity by the end of the twenty-first century if a high emissions path is followed. In particular, the annual 3-day heat wave temperature increases generally by 3°–8°C; the number of heat wave days increases by 30–60 day yr−1 over much of the western and southern United States with slightly smaller increases elsewhere; the variance spectra for intermediate, 3–7 days (prolonged, 7–14 days), temperature extremes increase (decrease) in the central (western) United States. If a lower emissions path is followed, then the outcomes range from quite small changes to substantial increases. In all cases, the mean temperature climatological shift is the dominant change in heat wave characteristics, suggesting that adaptation and acclimatization could reduce effects.

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.

Sign in / Sign up

Export Citation Format

Share Document