Current Status and Future Projections of the Snow Depth in the Third Pole from CMIP5 Global Climate Models

2014 ◽  
pp. 39-42
Author(s):  
Terzago Silvia ◽  
Von Hardenberg Jost ◽  
Palazzi Elisa ◽  
Provenzale Antonello
Keyword(s):  
Snow Depth ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Current Status ◽  
Future Projections ◽  
The Third

The CORDEX‐Australasia ensemble: evaluation and future projections

2021 ◽  
Author(s):  
Jason Evans ◽  
Giovanni Di Virgilio ◽  
Annette Hirsch ◽  
Peter Hoffmann ◽  
Armelle Reca Remedio ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Current Status ◽  
Climate Projections ◽  
Good Representation ◽  
Future Projections ◽  
Recent Climate ◽  
Climate Downscaling

<p>The World Climate Research Programme (WCRP) has an international initiative called the COordinated Regional climate Downscaling EXperiment (CORDEX). The goal of the initiative is to provide regionally downscaled climate projections for most land regions of the globe, as a compliment to the global climate model projections performed within the Coupled Model Intercomparison Projects (CMIP). CORDEX includes data from both dynamical and statistical downscaling. It is anticipated that the CORDEX dataset will provide a link to the impacts and adaptation community through its better resolution and regional focus. Participation in CORDEX is open and any researchers performing climate downscaling are encourage to engage with the initiative. Here I present the current status, <span>evaluation and future projections</span> for the CORDEX-AustralAsia <span>ensemble</span>.</p><p>The CORDEX-Australasia ensemble is the largest regional climate projection ensemble ever created for the region. It is a 20-member ensemble made by 6 regional climate models downscaling 11 global climate models. Overall the ensemble produces a good representation of recent climate. Consistent biases within the ensemble include an underestimation of the diurnal temperature range and an underestimation of precipitation across much of southern Australia. Under a high emissions scenario projected temperature changes by the end of the twenty-first century reach ~ 5 K in the interior of Australia with smaller increases found toward the coast. Projected precipitation changes are towards drying, particularly in the most populated areas of the southwest and southeast of the continent. The projected precipitation change is very seasonal with summer projected to see little change leaning toward an increase. These results provide a foundation enabling future studies of regional climate changes, climate change impacts, and adaptation options for Australia.</p>

scholarly journals Model improvement and future projection of permafrost processes in a global land surface model

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Tokuta Yokohata ◽  
Kazuyuki Saito ◽  
Kumiko Takata ◽  
Tomoko Nitta ◽  
Yusuke Satoh ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Global Climate ◽  
Land Surface Model ◽  
Global Climate Models ◽  
Soil Freezing ◽  
Surface Model ◽  
Southern Limit ◽  
Future Projections ◽  
Global Land

AbstractTo date, the treatment of permafrost in global climate models has been simplified due to the prevailing uncertainties in the processes involving frozen ground. In this study, we improved the modeling of permafrost processes in a state-of-the-art climate model by taking into account some of the relevant physical properties of soil such as changes in the thermophysical properties due to soil freezing. As a result, the improved version of the global land surface model was able to reproduce a more realistic permafrost distribution at the southern limit of the permafrost area by increasing the freezing of soil moisture in winter. The improved modeling of permafrost processes also had a significant effect on future projections. Using the conventional formulation, the predicted cumulative reduction of the permafrost area by year 2100 was approximately 60% (40–80% range of uncertainty from a multi-model ensemble) in the RCP8.5 scenario, while with the improved formulation, the reduction was approximately 35% (20–50%). Our results indicate that the improved treatment of permafrost processes in global climate models is important to ensuring more reliable future projections.

scholarly journals Snowpack Changes in the Hindu Kush–Karakoram–Himalaya from CMIP5 Global Climate Models

2014 ◽  
Vol 15 (6) ◽  
pp. 2293-2313 ◽  
Author(s):  
Silvia Terzago ◽  
Jost von Hardenberg ◽  
Elisa Palazzi ◽  
Antonello Provenzale
Keyword(s):  
Snow Depth ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Global Climate ◽  
Control Period ◽  
High Elevation ◽  
Global Climate Models ◽  
Spatial Average ◽  
Hindu Kush ◽  
Snow Water

Abstract The Hindu Kush, Karakoram, and Himalaya (HKKH) mountain ranges feed the most important Asian river systems, providing water to about 1.5 billion people. As a consequence, changes in snow dynamics in this area could severely impact water availability for downstream populations. Despite their importance, the amount, spatial distribution, and seasonality of snow in the HKKH region are still poorly known, owing to the limited availability of surface observations in this remote and high-elevation area. This work considers global climate models (GCM) participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and analyzes how they represent current and future snowpack in the HKKH region in terms of snow depth and snow water equivalent. It is found that models with high spatial resolution (up to 1.25°) simulate a spatial pattern of the winter snowpack in greater agreement with each other, with observations, with reanalysis datasets, and with the orographic features of the region, compared to most lower-resolution models. The seasonal cycle of snow depth displays a unimodal regime, with a maximum in February–March and almost complete melting in summer. The models generally indicate thicker [in Hindu Kush–Karakoram (HKK)] or comparable (in the Himalayas) snow depth and higher snow water equivalent compared to the reanalyses for the control period 1980–2005. Future projections, evaluated in terms of the ensemble mean of GCM simulations, indicate a significant reduction in the spatial average of snow depth over the HKK and an even stronger decrease in the Himalayas, where a reduction between 25% and 50% is expected by the end of the twenty-first century.

Numerical simulations of precipitation and streamflow in current climate and future projections to drainage areas of Brazilian hydroelectric plants

2020 ◽  
Vol 79 (3) ◽  
pp. 219-241
Author(s):  
W Luiz Silva ◽  
MEP Maceira ◽  
OC Rotunno Filho
Keyword(s):  
Climate Models ◽  
Hydrological Model ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Future Projections ◽  
Hydroelectric Plants

Hydroelectric sources are a major contributor to power generation in Brazil. The constant evaluation of climate change impacts is relevant for guiding Brazilian energy policy. This research presents a methodological framework composed of the calibration of a hydrological model and verification of a climate model in the ‘present’ climate (1961-1990), in addition to future scenarios (2011-2100) of precipitation and streamflow for 4 hydroelectric plants in Brazil. For future projections, data from the Eta regional climate model (20 km horizontal resolution) nested within the HadGEM2-ES and MIROC5 global climate models were used. Monthly linear bias correction was applied to the simulations. Future projections were based on IPCC RCP4.5 and 8.5 scenarios. The SMAP hydrological model was adopted on a monthly scale with the addition of a translation parameter that examines the level of dependence of the present streamflow on the previous month's streamflow. The climate and hydrological models satisfactorily capture the distribution of precipitation and streamflow in different Brazilian regions, and effectively represent seasonal variability. Future projections point to a reduction in rainfall and natural streamflow in central-northern Brazil and a slight increase in the southern region. These scenarios should be carefully considered and require constant improvement and research since there are uncertainties associated with atmospheric dynamics and the hydrological cycle.

Using the learnings of machine learning to distill cloud controlling environmental regimes from satellite observations

2021 ◽  
Author(s):  
Alyson Douglas ◽  
Philip Stier
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Controlling Factors ◽  
Global Climate Models ◽  
Satellite Observations ◽  
Cloud Formation ◽  
Future Projections ◽  
Cloud Properties ◽  
Environmental Regimes ◽  
Well Model

<div> <div> <div> <div> <p>Cloud processes are the leading source of uncertainty in our current global climate models. Therefore understanding cloud formation, lifetime, and decay remains pivotal in order to reduce uncertainty in our global climate models future projections. Exploiting over ten years of satellite observations, the relationships between cloud properties and environmental factors, including aerosols, can be better understood and clustered into environmental regimes. We cluster regimes based on the regional strength of the relationships between the environment and cloud properties revealed using a random forest. Numerous processes, such as stratocumulus to cumulus transitions, may be constrained by the environmental regimes revealed by our analysis. Our results show that depending on the region, aerosol and the environment work to determine the baseline cloud properties. These observation based regimes can be compared to regimes derived from global climate models to understand how well model parameterizations capture the cloud controlling factors.</p> </div> </div> </div> </div>

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

scholarly journals Regions of intensification of extreme snowfall under future warming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Observational Data ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Average Intensity ◽  
High Latitudes ◽  
Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

scholarly journals Reassessing Existing Reservoir Supply Capacity and Management Resilience under Climate Change and Sediment Deposition

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1819
Author(s):  
Eleni S. Bekri ◽  
Polychronis Economou ◽  
Panayotis C. Yannopoulos ◽  
Alexander C. Demetracopoulos
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Vital Role ◽  
Sediment Deposition ◽  
Global Climate Models ◽  
Exceedance Probability ◽  
Climate Change Effects ◽  
Management Scenario ◽  
Supply Capacity

Freshwater resources are limited and seasonally and spatially unevenly distributed. Thus, in water resources management plans, storage reservoirs play a vital role in safeguarding drinking, irrigation, hydropower and livestock water supply. In the last decades, the dams’ negative effects, such as fragmentation of water flow and sediment transport, are considered in decision-making, for achieving an optimal balance between human needs and healthy riverine and coastal ecosystems. Currently, operation of existing reservoirs is challenged by increasing water demand, climate change effects and active storage reduction due to sediment deposition, jeopardizing their supply capacity. This paper proposes a methodological framework to reassess supply capacity and management resilience for an existing reservoir under these challenges. Future projections are derived by plausible climate scenarios and global climate models and by stochastic simulation of historic data. An alternative basic reservoir management scenario with a very low exceedance probability is derived. Excess water volumes are investigated under a probabilistic prism for enabling multiple-purpose water demands. Finally, this method is showcased to the Ladhon Reservoir (Greece). The probable total benefit from water allocated to the various water uses is estimated to assist decision makers in examining the tradeoffs between the probable additional benefit and risk of exceedance.

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