scholarly journals Confronting Arctic Troposphere, Clouds, and Surface Energy Budget Representations in Regional Climate Models With Observations

2020 ◽  
Vol 125 (6) ◽  
Author(s):  
Joseph Sedlar ◽  
Michael Tjernström ◽  
Annette Rinke ◽  
Andrew Orr ◽  
John Cassano ◽  
...  
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Surface Energy Budget

scholarly journals Projected Changes in Soil Temperature and Surface Energy Budget Components over the Alps and Northern Italy

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 954 ◽  
Author(s):  
Claudio Cassardo ◽  
Seon Park ◽  
Sungmin O ◽  
Marco Galli
Keyword(s):  
Heat Flux ◽  
Surface Energy ◽  
Soil Temperature ◽  
Energy Budget ◽  
Regional Climate ◽  
Northern Italy ◽  
Surface Energy Budget ◽  
Future Climate ◽  
Radiative Properties ◽  
The Alps

This study investigates the potential changes in surface energy budget components under certain future climate conditions over the Alps and Northern Italy. The regional climate scenarios are obtained though the Regional Climate Model version 3 (RegCM3) runs, based on a reference climate (1961–1990) and the future climate (2071–2100) via the A2 and B2 scenarios. The energy budget components are calculated by employing the University of Torino model of land Processes Interaction with Atmosphere (UTOPIA), and using the RegCM3 outputs as input data. Our results depict a significant change in the energy budget components during springtime over high-mountain areas, whereas the most relevant difference over the plain areas is the increase in latent heat flux and hence, evapotranspiration during summertime. The precedence of snow-melting season over the Alps is evidenced by the earlier increase in sensible heat flux. The annual mean number of warm and cold days is evaluated by analyzing the top-layer soil temperature and shows a large increment (slight reduction) of warm (cold) days. These changes at the end of this century could influence the regional radiative properties and energy cycles and thus, exert significant impacts on human life and general infrastructures.

scholarly journals Near-surface meteorology during the Arctic Summer Cloud Ocean Study (ASCOS): evaluation of reanalyses and global climate models

2014 ◽  
Vol 14 (1) ◽  
pp. 427-445 ◽  
Author(s):  
G. de Boer ◽  
M. D. Shupe ◽  
P. M. Caldwell ◽  
S. E. Bauer ◽  
O. Persson ◽  
...  
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Near Surface ◽  
Ocean Study ◽  
Arctic Summer

Abstract. Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)-Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

scholarly journals Sensitivity of the surface energy budget to drifting snow as simulated by MAR in coastal Adelie Land, Antarctica

2020 ◽  
Author(s):  
Louis Le Toumelin ◽  
Charles Amory ◽  
Vincent Favier ◽  
Christoph Kittel ◽  
Stefan Hofer ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Surface Energy ◽  
Energy Budget ◽  
Radiative Forcing ◽  
Climate Models ◽  
Surface Energy Budget ◽  
Near Surface ◽  
Surface Atmosphere ◽  
Drifting Snow ◽  
The Impact

Abstract. In order to understand the evolution of the climate of Antarctica, dominant processes that control surface and low-atmosphere meteorology need to be accurately captured in climate models. We used the regional climate model MAR (v3.11) at 10 km horizontal resolution, forced by ERA5 reanalysis over a 9-year period (2010–2018), to study the impact of drifting snow (designing here the wind-driven transport of snow particles below and above 2 m) on the near-surface atmosphere and surface in Adelie Land, East Antarctica. Two model runs were performed, respectively with and without drifting snow, and compared to half-hourly in situ observations at D17, a coastal and windy location of Adelie Land. We show that sublimation of drifting-snow particles in the atmosphere drives the difference between model runs and is responsible for significant impacts on the near-surface atmosphere. By cooling the low atmosphere and increasing its relative humidity, drifting snow also reduces sensible and latent heat exchanges at the surface (−5.9 W m−2 on average). Moreover, large and dense drifting-snow layers act as near-surface cloud by interacting with incoming radiative fluxes, enhancing incoming longwave radiations and reducing incoming shortwave radiations in summer (net radiative forcing: 5.9 W m−2). Even if drifting snow modifies these processes involved in surface-atmosphere interactions, the total surface energy budget is only slightly modified by introducing drifting snow, because of compensating effects in surface energy fluxes. The drifting-snow driven effects are not prominent near the surface but peak higher in the boundary layer (fifth vertical level, 38 m) where drifting snow sublimation is the most pronounced. Accounting for drifting snow in MAR generally improves the comparison at D17, more especially for the representation of relative humidity (mean bias reduced from −11.1 % to 2.9 %) and incoming longwave radiation (mean bias reduced from −7.6 W m−2 to −1.5 W m−2). Consequently, our results suggest that a detailed representation of drifting-snow processes is required in climate models to better capture the near–surface meteorology and surface–atmosphere interactions in coastal Adelie Land.

scholarly journals Sensitivity of the surface energy budget to drifting snow as simulated by MAR in coastal Adelie Land, Antarctica

2021 ◽  
Vol 15 (8) ◽  
pp. 3595-3614
Author(s):  
Louis Le Toumelin ◽  
Charles Amory ◽  
Vincent Favier ◽  
Christoph Kittel ◽  
Stefan Hofer ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Surface Energy ◽  
Energy Budget ◽  
Climate Models ◽  
Longwave Radiation ◽  
Surface Energy Budget ◽  
Near Surface ◽  
Surface Atmosphere ◽  
Drifting Snow ◽  
The Impact

Abstract. In order to understand the evolution of the climate of Antarctica, dominant processes that control surface and low-atmosphere meteorology need to be accurately captured in climate models. We used the regional climate model MAR (v3.11) at 10 km horizontal resolution, forced by ERA5 reanalysis over a 9-year period (2010–2018) to study the impact of drifting snow (designating here the wind-driven transport of snow particles below and above 2 m) on the near-surface atmosphere and surface in Adelie Land, East Antarctica. Two model runs were performed, one with and one without drifting snow, and compared to half-hourly in situ observations at D17, a coastal and windy location of Adelie Land. We show that sublimation of drifting-snow particles in the atmosphere drives the difference between model runs and is responsible for significant impacts on the near-surface atmosphere. By cooling the low atmosphere and increasing its relative humidity, drifting snow also reduces sensible and latent heat exchanges at the surface (−5.7 W m−2 on average). Moreover, large and dense drifting-snow layers act as near-surface cloud by interacting with incoming radiative fluxes, enhancing incoming longwave radiation and reducing incoming shortwave radiation in summer (net radiative forcing: 5.7 W m−2). Even if drifting snow modifies these processes involved in surface–atmosphere interactions, the total surface energy budget is only slightly modified by introducing drifting snow because of compensating effects in surface energy fluxes. The drifting-snow driven effects are not prominent near the surface but peak higher in the boundary layer (fourth vertical level, 12 m) where drifting-snow sublimation is the most pronounced. Accounting for drifting snow in MAR generally improves the comparison at D17, especially for the representation of relative humidity (mean bias reduced from −14.0 % to −0.7 %) and incoming longwave radiation (mean bias reduced from −20.4 W m−2 to −14.9 W m−2). Consequently, our results suggest that a detailed representation of drifting-snow processes is required in climate models to better capture the near-surface meteorology and surface–atmosphere interactions in coastal Adelie Land.

scholarly journals Near-surface meteorology during the Arctic Summer Cloud Ocean Study (ASCOS): evaluation of reanalyses and global climate models

2013 ◽  
Vol 13 (7) ◽  
pp. 19421-19470 ◽  
Author(s):  
G. de Boer ◽  
M. D. Shupe ◽  
P. M. Caldwell ◽  
S. E. Bauer ◽  
P. O. G. Persson ◽  
...  
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Near Surface ◽  
Ocean Study ◽  
Arctic Summer

Abstract. Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three reanalyses (ERA-Interim, NCEP/NCAR and NCEP/DOE) and two global climate models (CAM5 and NASA GISS ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, is demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the need to evaluate individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms resulting in the best net energy budget.

Regional Climate Scenarios for use in Nordic Water Resources Studies

2003 ◽  
Vol 34 (5) ◽  
pp. 399-412 ◽  
Author(s):  
M. Rummukainen ◽  
J. Räisänen ◽  
D. Bjørge ◽  
J.H. Christensen ◽  
O.B. Christensen ◽  
...  
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Scenarios ◽  
Soil Frost ◽  
Nordic Region ◽  
Regional Climate Projections

According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.

scholarly journals Cool season precipitation projections for California and the Western United States in NA-CORDEX models

2021 ◽  
Author(s):  
Kelly Mahoney ◽  
James D. Scott ◽  
Michael Alexander ◽  
Rachel McCrary ◽  
Mimi Hughes ◽  
...  
Keyword(s):  
United States ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Western United States ◽  
Monthly Precipitation ◽  
Wet Season ◽  
Cool Season ◽  
Projected Change

AbstractUnderstanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges.

scholarly journals Projecting Health Impacts of Future Temperature: A Comparison of Quantile-Mapping Bias-Correction Methods

2021 ◽  
Vol 18 (4) ◽  
pp. 1992
Author(s):  
Weijia Qian ◽  
Howard H. Chang
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Climate Science ◽  
Regional Climate Models ◽  
Health Impact ◽  
Quantile Mapping ◽  
Ed Visits

Health impact assessments of future environmental exposures are routinely conducted to quantify population burdens associated with the changing climate. It is well-recognized that simulations from climate models need to be bias-corrected against observations to estimate future exposures. Quantile mapping (QM) is a technique that has gained popularity in climate science because of its focus on bias-correcting the entire exposure distribution. Even though improved bias-correction at the extreme tails of exposure may be particularly important for estimating health burdens, the application of QM in health impact projection has been limited. In this paper we describe and apply five QM methods to estimate excess emergency department (ED) visits due to projected changes in warm-season minimum temperature in Atlanta, USA. We utilized temperature projections from an ensemble of regional climate models in the North American-Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). Across QM methods, we estimated consistent increase in ED visits across climate model ensemble under RCP 8.5 during the period 2050 to 2099. We found that QM methods can significantly reduce between-model variation in health impact projections (50–70% decreases in between-model standard deviation). Particularly, the quantile delta mapping approach had the largest reduction and is recommended also because of its ability to preserve model-projected absolute temporal changes in quantiles.

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