scholarly journals Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part I: Climate Model Evaluation

2010 ◽  
Vol 23 (6) ◽  
pp. 1589-1606 ◽  
Author(s):  
Sven Kotlarski ◽  
Frank Paul ◽  
Daniela Jacob
Keyword(s):  
Regional Climate Model ◽  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Global Radiation ◽  
High Elevation ◽  
Balance Model ◽  
Future Climate Change ◽  
Glacier Mass Balance ◽  
Mass Balance Model

Abstract A coupling interface between the regional climate model REMO and a distributed glacier mass balance model is presented in a series of two papers. The first part describes and evaluates the reanalysis-driven regional climate simulation that is used to force a mass balance model for two glaciers of the Swiss mass balance network. The detailed validation of near-surface air temperature, precipitation, and global radiation for the European Alps shows that the basic spatial and temporal patterns of all three parameters are reproduced by REMO. Compared to the Climatic Research Unit (CRU) dataset, the Alpine mean temperature is underestimated by 0.34°C. Annual precipitation shows a positive bias of 17% (30%) with respect to the uncorrected gridded ALP-IMP (CRU) dataset. A number of important and systematic model biases arise in high-elevation regions, namely, a negative temperature bias in winter, a bias of seasonal precipitation (positive or negative, depending on gridbox altitude and season), and an underestimation of springtime and overestimation of summertime global radiation. These can be expected to have a strong effect on the simulated glacier mass balance. It is recommended to account for these shortcomings by applying correction procedures before using the RCM output for subsequent mass balance modeling. Despite the obvious model deficiencies in high-elevation regions, the new interface broadens the scope of application of glacier mass balance models and will allow for a straightforward assessment of future climate change impacts.

scholarly journals Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part II: Downscaling Strategy and Results for Two Swiss Glaciers

2010 ◽  
Vol 23 (6) ◽  
pp. 1607-1620 ◽  
Author(s):  
Frank Paul ◽  
Sven Kotlarski
Keyword(s):  
Time Series ◽  
Regional Climate Model ◽  
Mass Balance ◽  
Meteorological Parameters ◽  
Climate Model ◽  
Regional Climate ◽  
Balance Model ◽  
Glacier Mass Balance ◽  
Mass Balance Model ◽  
Climate Station

Abstract Distributed glacier mass balance models are efficient tools for the assessment of climate change impacts on glaciers at regional scales and at high spatial resolution (25–100 m). In general, these models are driven by time series of meteorological parameters that are obtained from a climate station near a glacier or from climate model output. Because most glaciers are located in rugged mountain topography with a high spatial and temporal variability of the meteorological conditions, the challenge is to distribute the point data from a climate station or the gridbox values from a regional climate model (RCM) in an appropriate way to the terrain. Here an approach is presented that uses normalized grids at the resolution of the mass balance model to capture the spatial variability, and time series from a climate station (Robiei) and an RCM Regional Model (REMO) to provide a temporal forcing for the mass balance model. The test site near Nufenen Pass (Swiss Alps) covers two glaciers with direct mass balance measurements that are used to demonstrate the approach. The meteorological parameters (temperature, global radiation, and precipitation) are obtained for the years 1997–99 (at daily steps) from the climate station Robiei (1898 m MSL) and one grid box of the RCM REMO. The results of the mass balance model agree closely with the measured values and the specific differences in mass balance between the two glaciers and the two balance years are well captured. Despite the disparities in the meteorological forcing from the climate station and REMO, there are only small differences in the modeled mass balances. This gives confidence that the developed approach of coupling the coarse-resolution (18 km) RCM with the high-resolution (25 m) mass balance model is suitable and can be applied to other regions as well as to RCM scenario runs.

scholarly journals Climate sensitivity of Storglaciären, Sweden: an intercomparison of mass-balance models using ERA-40 re-analysis and regional climate model data

2007 ◽  
Vol 46 ◽  
pp. 342-348 ◽  
Author(s):  
Regine Hock ◽  
Valentina Radić ◽  
Mattias De Woul
Keyword(s):  
Energy Balance ◽  
Regional Climate Model ◽  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Balance Model ◽  
Glacier Mass Balance ◽  
Temperature Index ◽  
Temperature Changes ◽  
Cumulative Mass

AbstractEstimates of glacier contributions to future sea-level rise are often computed from mass-balance sensitivities derived for a set of representative glaciers. Our purpose is to investigate how mass-balance projections and sensitivities vary when using different approaches to compute the glacier mass balance. We choose Storglaciären, Sweden, as a test site and apply five different models including temperature-index and energy-balance approaches further varying in spatial discretization. The models are calibrated using daily European Centre for Medium-Range Weather Forecasts re-analysis (ERA-40) data. We compute static mass-balance sensitivities and cumulative mass balances until 2100 based on daily temperatures predicted by a regional climate model. Net mass-balance sensitivities to a +1 K perturbation and a 10% increase in precipitation spanned from –0.41 to –0.61 and from 0.19 to 0.22ma–1, respectively. The cumulative mass balance for the period 2002–2100 in response to the climate-model predicted temperature changes varied between –81 and –92m for four models, but was –121m for the fully distributed detailed energy-balance model. This indicates that mass losses may be underestimated if temperature-index methods are used instead of detailed energy-balance approaches that account for the effects of temperature changes on all energy-balance components individually. Our results suggest that future glacier predictions are sensitive to the choice of the mass-balance model broadening the spectrum in uncertainties.

scholarly journals Modelling 60 years of glacier mass balance and runoff for Chhota Shigri Glacier, Western Himalaya, Northern India

2017 ◽  
Vol 63 (240) ◽  
pp. 618-628 ◽  
Author(s):  
MARKUS ENGELHARDT ◽  
AL. RAMANATHAN ◽  
TRUDE EIDHAMMER ◽  
PANKAJ KUMAR ◽  
OSKAR LANDGREN ◽  
...  
Keyword(s):  
Mass Balance ◽  
Global Radiation ◽  
Western Himalaya ◽  
Snow Accumulation ◽  
Balance Model ◽  
Model Parameters ◽  
Glacier Mass Balance ◽  
Mass Balance Model ◽  
Glacier Melt ◽  
Chhota Shigri Glacier

ABSTRACTGlacier mass balance and runoff are simulated from 1955 to 2014 for the catchment (46% glacier cover) containing Chhota Shigri Glacier (Western Himalaya) using gridded data from three regional climate models: (1) the Rossby Centre regional atmospheric climate model v.4 (RCA4); (2) the REgional atmosphere MOdel (REMO); and (3) the Weather Research and Forecasting Model (WRF). The input data are downscaled to the simulation grid (300 m) and calibrated with point measurements of temperature and precipitation. Additional input is daily potential global radiation calculated using a DEM at a resolution of 30 m. The mass-balance model calculates daily snow accumulation, melt and runoff. The model parameters are calibrated with available mass-balance measurements and results are validated with geodetic measurements, other mass-balance model results and run-off measurements. Simulated annual mass balances slightly decreased from −0.3 m w.e. a−1 (1955–99) to −0.6 m w.e. a−1 for 2000–14. For the same periods, mean runoff increased from 2.0 m3 s−1 (1955–99) to 2.4 m3 s−1 (2000–14) with glacier melt contributing about one-third to the runoff. Monthly runoff increases are greatest in July, due to both increased snow and glacier melt, whereas slightly decreased snowmelt in August and September was more than compensated by increased glacier melt.

scholarly journals Modelling the impact of superimposed ice on the mass balance of an Arctic glacier under scenarios of future climate change

2005 ◽  
Vol 42 ◽  
pp. 277-283 ◽  
Author(s):  
Andrew Wright ◽  
Jemma Wadham ◽  
Martin Siegert ◽  
Adrian Luckman ◽  
Jack Kohler
Keyword(s):  
Climate Change ◽  
Mass Balance ◽  
Climate Model ◽  
Global Climate Model ◽  
Balance Model ◽  
Explicit Calculation ◽  
Future Climate Change ◽  
Glacier Mass Balance ◽  
Positive Contribution ◽  
The Impact

AbstractA surface-energy/mass-balance model with an explicit calculation of meltwater refreezing and superimposed ice formation is applied to midre Lovénbreen, Spitsbergen, Svalbard. The model is run with meteorological measurements to represent the present climate, and run with scenarios taken from global climate model predictions based on the IS92a emissions scenario to represent future climates. Model results indicate that superimposed ice accounts for on average 37% of the total net accumulation under present conditions. The model is found to be highly sensitive to changes in the mean annual air temperature and much less sensitive to changes in the total annual precipitation. A 0.5˚C decade–1 temperature increase is predicted to cause an average mass-balance change of –0.43 ma–1, while a 2% decade–1 increase in precipitation will result in only a +0.02 ma–1 change in mass balance. An increase in temperature results in a significant decrease in the size of the accumulation area at midre Lovénbreen and hence a similar decrease in the net volume of superimposed ice. The model predicts, however, that the relative importance of superimposed ice will increase to account for >50% of the total accumulation by 2050. The results show that the refreezing of meltwater and in particular the formation of superimposed ice make an important positive contribution to the mass balance of midre Lovénbreen under present conditions and will play a vital future role in slowing down the response of glacier mass balance to climate change.

scholarly journals SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet

2017 ◽  
Vol 11 (4) ◽  
pp. 1519-1535 ◽  
Author(s):  
Mario Krapp ◽  
Alexander Robinson ◽  
Andrey Ganopolski
Keyword(s):  
Surface Energy ◽  
Mass Balance ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Balance Model ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Mass Balance Model ◽  
Ice Sheet Modelling

Abstract. We present SEMIC, a Surface Energy and Mass balance model of Intermediate Complexity for snow- and ice-covered surfaces such as the Greenland ice sheet. SEMIC is fast enough for glacial cycle applications, making it a suitable replacement for simpler methods such as the positive degree day (PDD) method often used in ice sheet modelling. Our model explicitly calculates the main processes involved in the surface energy and mass balance, while maintaining a simple interface and requiring minimal data input to drive it. In this novel approach, we parameterise diurnal temperature variations in order to more realistically capture the daily thaw–freeze cycles that characterise the ice sheet mass balance. We show how to derive optimal model parameters for SEMIC specifically to reproduce surface characteristics and day-to-day variations similar to the regional climate model MAR (Modèle Atmosphérique Régional, version 2) and its incorporated multilayer snowpack model SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer). A validation test shows that SEMIC simulates future changes in surface temperature and surface mass balance in good agreement with the more sophisticated multilayer snowpack model SISVAT included in MAR. With this paper, we present a physically based surface model to the ice sheet modelling community that is general enough to be used with in situ observations, climate model, or reanalysis data, and that is at the same time computationally fast enough for long-term integrations, such as glacial cycles or future climate change scenarios.

scholarly journals Mass-balance parameters derived from a synthetic network of mass-balance glaciers

2012 ◽  
Vol 58 (211) ◽  
pp. 965-979 ◽  
Author(s):  
Horst Machguth ◽  
Wilfried Haeberli ◽  
Frank Paul
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Synthetic Data ◽  
Swiss Alps ◽  
Balance Model ◽  
Glacier Mass Balance ◽  
Model Output ◽  
Equilibrium Line Altitude ◽  
Regional Climate Model Output

AbstractGlacier mass-balance parameters such as the equilibrium-line altitude (ELA) play an important role when working with large glacier samples. While the number of observational mass-balance series to derive such parameters is limited, more and more modeled data are becoming available.Here we explore the possibilities of analyzing such 'synthetic' mass-balance data with respect to mass-balance parameters. A simplified energy-balance model is driven by bias-corrected regional climate model output to model mass-balance distributions for 94 glaciers in the Swiss Alps over 15 years. The modeling results in realistic interannual variability and mean cumulative mass balance. Subsequently model output is analyzed with respect to 18 topographic and mass-balance parameters and a correlation analysis is performed. Well-known correlations such as for ELA and median elevation are confirmed from the synthetic data. Furthermore, previously unreported parameter relationships are found such as a correlation of the balance rate at the tongue with the accumulation-area ratio (AAR) and of the glacier elevation range with the AAR. Analyzing modeled data complements in situ observations and highlights their importance: the small number of accurate mass-balance observations available for validation is a major challenge for the presented approach.

scholarly journals Projected changes in haze pollution potential in China: an ensemble of regional climate model simulations

2017 ◽  
Vol 17 (16) ◽  
pp. 10109-10123 ◽  
Author(s):  
Zhenyu Han ◽  
Botao Zhou ◽  
Ying Xu ◽  
Jia Wu ◽  
Ying Shi
Keyword(s):  
Regional Climate Model ◽  
21St Century ◽  
Climate Model ◽  
Regional Climate ◽  
River Delta ◽  
Central China ◽  
Future Climate Change ◽  
Pollution Potential ◽  
Pollution Risk ◽  
Haze Pollution

Abstract. Based on the dynamic downscaling by the regional climate model RegCM4 from three CMIP5 global models under the historical and the RCP4.5 simulations, this article evaluated the performance of the RegCM4 downscaling simulations on the air environment carrying capacity (AEC) and weak ventilation days (WVDs) in China, which are applied to measure haze pollution potential. Their changes during the middle and the end of the 21st century were also projected. The evaluations show that the RegCM4 downscaling simulations can generally capture the observed features of the AEC and WVD distributions over the period 1986–2005. The projections indicate that the annual AEC tends to decrease and the annual WVDs tend to increase over almost the whole country except central China, concurrent with greater change by the late 21st century than by the middle of the 21st century. It suggests that annual haze pollution potential would be enlarged under the RCP4.5 scenario compared to the present. For seasonal change in the four main economic zones of China, it is projected consistently that there would be a higher probability of haze pollution risk over the Beijing–Tianjin–Hebei (BTH) region and the Yangtze River Delta (YRD) region in winter and over the Pearl River Delta (PRD) region in spring and summer in the context of the warming scenario. Over Northeast China (NEC), future climate change might reduce the AEC or increase the WVDs throughout the whole year, which favours the occurrence of haze pollution and thus the haze pollution risk would be aggravated. The relative contribution of different components related to the AEC change further indicates that changes in the boundary layer depth and the wind speed play leading roles in the AEC change over the BTH and NEC regions. In addition to those two factors, the precipitation change also exerts important impacts on the AEC change over the YRD and PRD zones.

Regional Climate Model Inter-Comparison for Antarctica within a Data Science Framework

2021 ◽  
Author(s):  
Jeremy Carter ◽  
Amber Leeson ◽  
Andrew Orr ◽  
Christoph Kittel ◽  
Melchior van Wessem
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate Change ◽  
Near Surface ◽  
Virtual Lab ◽  
Model Variability ◽  
The Antarctic

<p>Understanding the surface climatology of the Antarctic ice sheet is essential if we are to adequately predict its response to future climate change. This includes both primary impacts such as increased ice melting and secondary impacts such as ice shelf collapse events. Given its size, and inhospitable environment, weather stations on Antarctica are sparse. Thus, we rely on regional climate models to 1) develop our understanding of how the climate of Antarctica varies in both time and space and 2) provide data to use as context for remote sensing studies and forcing for dynamical process models. Given that there are a number of different regional climate models available that explicitly simulate Antarctic climate, understanding inter- and intra model variability is important.</p><p>Here, inter- and intra-model variability in Antarctic-wide regional climate model output is assessed for: snowfall; rainfall; snowmelt and near-surface air temperature within a cloud-based virtual lab framework. State-of-the-art regional climate model runs from the Antarctic-CORDEX project using the RACMO, MAR and MetUM models are used, together with the ERA5 and ERA-Interim reanalyses products. Multiple simulations using the same model and domain boundary but run at either different spatial resolutions or with different driving data are used. Traditional analysis techniques are exploited and the question of potential added value from more modern and involved methods such as the use of Gaussian Processes is investigated. The advantages of using a virtual lab in a cloud based environment for increasing transparency and reproducibility, are demonstrated, with a view to ultimately make the code and methods used widely available for other research groups.</p>

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