The response and role of ice cover in lake-climate interactions

2010 ◽  
Vol 34 (5) ◽  
pp. 671-704 ◽  
Author(s):  
Laura C. Brown ◽  
Claude R. Duguay
Keyword(s):  
Climate Models ◽  
Weather Forecasting ◽  
Regional Climate ◽  
Remote Sensing Data ◽  
Ice Cover ◽  
Climate Modelling ◽  
Lake Ice ◽  
Climate Conditions ◽  
Global Circulation Models

This paper reviews the current state of knowledge pertaining to the interactions of lake ice and climate. Lake ice has been shown to be sensitive to climate variability through observations and modelling, and both long-term and short-term trends have been identified from ice records. Ice phenology trends have typically been associated with variations in air temperatures while ice thickness trends tend to be associated more to changes in snow cover. The role of ice cover in the regional climate is less documented and with longer ice-free seasons possible as a result of changing climate conditions, especially at higher latitudes, the effects of lakes on their surrounding climate (such as increased evaporation, lake-effect snow and thermal moderation of surrounding areas, for example) can be expected to become more prominent. The inclusion of lakes and lake ice in climate modelling is an area of increased attention in recent studies. An important step in improving predictions of ice conditions in models is the assimilation of remote sensing data in areas where in-situ data is lacking, or non-representative of the lake conditions. The ability to accurately represent ice cover on lakes will be an important step in the improvement of global circulation models, regional climate models and numerical weather forecasting.

scholarly journals Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  
Keyword(s):  
Energy Budget ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Regional Climate ◽  
Climate Conditions ◽  
Continental Scale ◽  
Global Water Cycle ◽  
Wide Range ◽  
Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

The role of the surface evapotranspiration in regional climate modelling: Evaluation and near-term future changes

2020 ◽  
Vol 237 ◽  
pp. 104867 ◽  
Author(s):  
Matilde García-Valdecasas Ojeda ◽  
Juan José Rosa-Cánovas ◽  
Emilio Romero-Jiménez ◽  
P. Yeste ◽  
Sonia R. Gámiz-Fortis ◽  
...  
Keyword(s):  
Regional Climate ◽  
Regional Climate Modelling ◽  
Climate Modelling ◽  
Near Term

scholarly journals Evaluation of a New Statistical Method—TIN-Copula–for the Bias Correction of Climate Models’ Extreme Parameters

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 243 ◽  
Author(s):  
Georgia Lazoglou ◽  
Christina Angnostopoulou ◽  
Konstantia Tolika ◽  
Gräler Benedikt
Keyword(s):  
Statistical Method ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Regional Climate Models ◽  
Climate Conditions ◽  
Copula Theory ◽  
Mean Temperature ◽  
Copula Method

During the last decades, global and regional climate models have been widely used for the estimation of future climate conditions. Unfortunately, the models’ estimated values present important biases relative to the observed values, especially when the estimations refer to extremes. Consequently, several researchers have studied several statistical methods that are able to minimize the biases between climate models and observed values. The present study evaluates a new statistical method for bias correction: The triangular irregular network (TIN)-copula method. This method is a combination of the triangular irregular networks and the copula theory. In the present research, the new method is applied to ten Mediterranean stations and its results are compared with the bias-corrected values of three other widely used methods: The delta, the scaling, and the empirical quantile mapping methods. The analysis was made for maximum mean temperature (TMX) and minimum mean temperature (TMN) as well as for extreme precipitation (R99). According to the results, the TIN-copula method is able to correct extreme temperature and precipitation values, estimated by regional climate models, with high accuracy. Additionally, it is proven that the TIN-copula method is a useful tool for bias correction as it presents several advantages compared with the other methods, and it is recommended for future works.

scholarly journals The Impact of Climate Change on Material Degradation Criteria in Heritage over Iran: Regional Climate Model Evaluation

2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Salt Crystallization ◽  
Climate Modelling ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
The Impact

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.

Simulation of North American lake-ice cover characteristics under contemporary and future climate conditions

2011 ◽  
Vol 32 (5) ◽  
pp. 695-709 ◽  
Author(s):  
Yonas Dibike ◽  
Terry Prowse ◽  
Barrie Bonsal ◽  
Laurent de Rham ◽  
Tuomo Saloranta
Keyword(s):  
North American ◽  
Ice Cover ◽  
Future Climate ◽  
Lake Ice ◽  
Climate Conditions ◽  
Lake Ice Cover

scholarly journals Response of ice cover on shallow lakes of the North Slope of Alaska to contemporary climate conditions (1950–2011): radar remote sensing and numerical modeling data analysis

2013 ◽  
Vol 7 (4) ◽  
pp. 3783-3821 ◽  
Author(s):  
C. M. Surdu ◽  
C. R. Duguay ◽  
L. C. Brown ◽  
D. Fernández Prieto
Keyword(s):  
Shallow Lakes ◽  
Ice Cover ◽  
Arctic Lakes ◽  
North Slope ◽  
Lake Ice ◽  
Climate Conditions ◽  
The North ◽  
North Slope Of Alaska ◽  
Sar Data ◽  
Ice Model

Abstract. Air temperature and winter precipitation changes over the last five decades have impacted the timing, duration, and thickness of the ice cover on Arctic lakes as shown by recent studies. In the case of shallow tundra lakes, many of which are less than 3 m deep, warmer climate conditions could result in thinner ice covers and consequently, to a smaller fraction of lakes freezing to their bed in winter. However, these changes have not yet been comprehensively documented. The analysis of a 20 yr time series of ERS-1/2 synthetic aperture radar (SAR) data and a numerical lake ice model were employed to determine the response of ice cover (thickness, freezing to the bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA) to climate conditions over the last six decades. Analysis of available SAR data from 1991–2011, from a sub-region of the NSA near Barrow, shows a reduction in the fraction of lakes that freeze to the bed in late winter. This finding is in good agreement with the decrease in ice thickness simulated with the Canadian Lake Ice Model (CLIMo), a lower fraction of lakes frozen to the bed corresponding to a thinner ice cover. Observed changes of the ice cover show a trend toward increasing floating ice fractions from 1991 to 2011, with the greatest change occurring in April, when the grounded ice fraction declined by 22% (α = 0.01). Model results indicate a trend toward thinner ice covers by 18–22 cm (no-snow and 53% snow depth scenarios, α = 0.01) during the 1991–2011 period and by 21–38 cm (α = 0.001) from 1950–2011. The longer trend analysis (1950–2011) also shows a decrease in the ice cover duration by ∼24 days consequent to later freeze-up dates by 5.9 days (α = 0.1) and earlier break-up dates by 17.7–18.6 days (α = 0.001).

scholarly journals COSMO-CLM Regional Climate Simulations in the CORDEX framework: a review

2021 ◽  
Author(s):  
Silje Lund Sørland ◽  
Roman Brogli ◽  
Praveen Kumar Pothapakula ◽  
Emmanuele Russo ◽  
Jonas Van de Walle ◽  
...  
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Parameter Tuning ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Limited Area ◽  
Climate Projections ◽  
Climate Modelling ◽  
Near Surface ◽  
Climate Simulations

Abstract. In the last decade, the Climate Limited-area Modeling (CLM) Community has contributed to the Coordinated Re- gional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM community model, ERA-Interim reanalysis and eight Global Climate Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44° (∼50 km), 0.22° (∼25 km) and 0.11° (∼12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Fed- eration (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modelling communities is needed to increase the reliability of the GCM-RCM modelling chain.

scholarly journals Climate Modelling in Low Precision: Effects of Both Deterministic & Stochastic Rounding.

2021 ◽  
pp. 1-43
Author(s):  
E. Adam Paxton ◽  
Matthew Chantry ◽  
Milan Klöwer ◽  
Leo Saffin ◽  
Tim Palmer
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Weather Forecasting ◽  
Stress Test ◽  
Grid Point ◽  
Atmospheric Model ◽  
Extreme Weather Events ◽  
Climate Modelling ◽  
Double Precision ◽  
Rounding Error

AbstractMotivated by recent advances in operational weather forecasting, we study the efficacy of low-precision arithmetic for climate simulations. We develop a framework to measure rounding error in a climate model which provides a stress-test for a low-precision version of the model, and we apply our method to a variety of models including the Lorenz system; a shallow water approximation for ow over a ridge; and a coarse resolution spectral global atmospheric model with simplified parameterisations (SPEEDY). Although double precision (52 significant bits) is standard across operational climate models, in our experiments we find that single precision (23 sbits) is more than enough and that as low as half precision (10 sbits) is often sufficient. For example, SPEEDY can be run with 12 sbits across the code with negligible rounding error, and with 10 sbits if minor errors are accepted, amounting to less than 0.1 mm/6hr for average grid-point precipitation, for example. Our test is based on the Wasserstein metric and this provides stringent non-parametric bounds on rounding error accounting for annual means as well as extreme weather events. In addition, by testing models using both round-to-nearest (RN) and stochastic rounding (SR) we find that SR can mitigate rounding error across a range of applications, and thus our results also provide some evidence that SR could be relevant to next-generation climate models. Further research is needed to test if our results can be generalised to higher resolutions and alternative numerical schemes. However, the results open a promising avenue towards the use of low-precision hardware for improved climate modelling.

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