scholarly journals Decadal Prediction of the Sahelian Precipitation in CMIP5 Simulations

2013 ◽  
Vol 26 (19) ◽  
pp. 7708-7719 ◽  
Author(s):  
Marco Gaetani ◽  
Elsa Mohino
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
System Model ◽  
Low Resolution ◽  
Coupled Models ◽  
Climate System Model ◽  
Model Version ◽  
Coupled Global Climate Model

Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.

scholarly journals An Improved Parameterization for Simulating Arctic Cloud Amount in the CCSM3 Climate Model

2008 ◽  
Vol 21 (21) ◽  
pp. 5673-5687 ◽  
Author(s):  
Steve Vavrus ◽  
Duane Waliser
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Cloud Amount ◽  
The Arctic ◽  
Climate Simulation ◽  
Polar Regions ◽  
Climate System Model ◽  
Model Version

Abstract A simple alternative parameterization for predicting cloud fraction in the Community Climate System Model, version 3 (CCSM3) global climate model is presented. This formula, dubbed “freeezedry,” is designed to alleviate the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic. The cloud reduction causes an Arctic-wide drop of 15 W m−2 in surface cloud radiative forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2–8 K over the Arctic Ocean, thus significantly reducing the model’s pronounced warm bias. Freezedry also affects CCSM3’s sensitivity to greenhouse forcing. In a transient-CO2 experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5- and 0.5-K-smaller warming, respectively). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during nonsummer months (when clouds warm the surface), apparently because of the colder modern reference climate. While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions and has already been implemented in another climate model, the Global Environmental and Ecological Simulation of Ecological Systems, version 1 (GENESIS1). Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness.

Uncertainty of climate change and its impact on reference evapotranspiration in Rasht City, Iran

2011 ◽  
Vol 2 (1) ◽  
pp. 72-83 ◽  
Author(s):  
Heerbod Jahanbani ◽  
Lee Teang Shui ◽  
Alireza Massah Bavani ◽  
Abdul Halim Ghazali
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Model ◽  
Reference Evapotranspiration ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
General Circulation Models ◽  
Model Version ◽  
The Impact

There are many factors of uncertainty regarding the impact of climate change on reference evapotranspiration (ETo). The accuracy of the results is strictly related to these factors and ignoring any one of them reduces the precision of the results, and reduces their applicability for decision makers. In this study, the uncertainty related to two ETo models, the Hargreaves-Samani (HGS) and Artificial Neural Network (ANN), and two Atmosphere-Ocean General Circulation Models (AOGCMs), Hadley Centre Coupled Model, version 3 (HadCM3) climatic model and the Canadian Global Climate Model, version 3 (CGCM3) climatic model under climate change, was evaluated. The models predicted average temperature increases by 2010 to 2039 of 0.95 °C by the HadCM3 model and 1.13°C by the CGCM3 model under the A2 scenario relative to observed temperature. Accordingly, the models predicted average ETo would increase of 0.48, 0.60, 0.50 and 0.60 (mm/day) by 2010 to 2039 projected by four methods (by introducing the temperature of the HadCM3-A2 model and the CGCM3-A2 to ANN and HGS) relative to ETo of the observed period. The results showed that uncertainty of the AOGCMs is more than that of the ETo models applied in this study.

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Model ◽  
Small Scale ◽  
Low Resolution ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

scholarly journals Northern Hemisphere storminess in the Norwegian Earth System Model (NorESM1-M)

2014 ◽  
Vol 7 (6) ◽  
pp. 8975-9015
Author(s):  
E. M. Knudsen ◽  
J. E. Walsh
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
System Model ◽  
High Latitudes ◽  
Earth System ◽  
Projected Changes

Abstract. Metrics of storm activity in Northern Hemisphere high- and midlatitudes are evaluated from historical output and future projections by the Norwegian Earth System Model (NorESM1-M) coupled global climate model. The European Re-Analysis Interim (ERA-Interim) and the Community Climate System Model (CCSM4), a global climate model of the same vintage as NorESM1-M, provide benchmarks for comparison. The focus is on the autumn and early winter (September through December), the period when the ongoing and projected Arctic sea ice retreat is greatest. Storm tracks derived from a vorticity-based algorithm for storm identification are reproduced well by NorESM1-M, although the tracks are somewhat better resolved in the higher-resolution ERA-Interim and CCSM4. The tracks are projected to shift polewards in the future as climate changes under the Representative Concentration Pathway (RCP) forcing scenarios. Cyclones are projected to become generally more intense in the high-latitudes, especially over the Alaskan region, although in some other areas the intensity is projected to decrease. While projected changes in track density are less coherent, there is a general tendency towards less frequent storms in midlatitudes and more frequent storms in high-latitudes, especially the Baffin Bay/Davis Strait region. Autumn precipitation is projected to increase significantly across the entire high-latitudes. Together with the projected increases in storm intensity and sea level and the loss of sea ice, this increase in precipitation implies a greater vulnerability to coastal flooding and erosion, especially in the Alaskan region. The projected changes in storm intensity and precipitation (as well as sea ice and sea level pressure) scale generally linearly with the RCP value of the forcing and with time through the 21st century.

Beyond Weather Time-Scale Prediction for Hurricane Sandy and Super Typhoon Haiyan in a Global Climate Model

2015 ◽  
Vol 143 (2) ◽  
pp. 524-535 ◽  
Author(s):  
Baoqiang Xiang ◽  
Shian-Jiann Lin ◽  
Ming Zhao ◽  
Shaoqing Zhang ◽  
Gabriel Vecchi ◽  
...  
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
The Philippines ◽  
Hurricane Sandy ◽  
False Alarms ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Super Typhoon

Abstract While tropical cyclone (TC) prediction, in particular TC genesis, remains very challenging, accurate prediction of TCs is critical for timely preparedness and mitigation. Using a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the authors studied the predictability of two destructive landfall TCs: Hurricane Sandy in 2012 and Super Typhoon Haiyan in 2013. Results demonstrate that the geneses of these two TCs are highly predictable with the maximum prediction lead time reaching 11 days. The “beyond weather time scale” predictability of tropical cyclogenesis is primarily attributed to the model’s skillful prediction of the intraseasonal Madden–Julian oscillation (MJO) and the westward propagation of easterly waves. Meanwhile, the landfall location and time can be predicted one week ahead for Sandy’s U.S landfall, and two weeks ahead for Haiyan’s landing in the Philippines. The success in predicting Sandy and Haiyan, together with low false alarms, indicates the potential of using the GFDL coupled model for extended-range predictions of TCs.

scholarly journals Saudi-KAU Coupled Global Climate Model: Description and Performance

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Mansour Almazroui ◽  
Osama Tayeb ◽  
Abdulfattah S. Mashat ◽  
Ahmed Yousef ◽  
Yusuf A. Al-Turki ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Description ◽  
And Performance ◽  
Coupled Global Climate Model

scholarly journals Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?

2015 ◽  
Vol 28 (17) ◽  
pp. 6938-6959 ◽  
Author(s):  
Alex J. Cannon ◽  
Stephen R. Sobie ◽  
Trevor Q. Murdock
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Precipitation Extremes ◽  
Extreme Value Analysis ◽  
Quantile Mapping ◽  
Value Analysis

Abstract Quantile mapping bias correction algorithms are commonly used to correct systematic distributional biases in precipitation outputs from climate models. Although they are effective at removing historical biases relative to observations, it has been found that quantile mapping can artificially corrupt future model-projected trends. Previous studies on the modification of precipitation trends by quantile mapping have focused on mean quantities, with less attention paid to extremes. This article investigates the extent to which quantile mapping algorithms modify global climate model (GCM) trends in mean precipitation and precipitation extremes indices. First, a bias correction algorithm, quantile delta mapping (QDM), that explicitly preserves relative changes in precipitation quantiles is presented. QDM is compared on synthetic data with detrended quantile mapping (DQM), which is designed to preserve trends in the mean, and with standard quantile mapping (QM). Next, methods are applied to phase 5 of the Coupled Model Intercomparison Project (CMIP5) daily precipitation projections over Canada. Performance is assessed based on precipitation extremes indices and results from a generalized extreme value analysis applied to annual precipitation maxima. QM can inflate the magnitude of relative trends in precipitation extremes with respect to the raw GCM, often substantially, as compared to DQM and especially QDM. The degree of corruption in the GCM trends by QM is particularly large for changes in long period return values. By the 2080s, relative changes in excess of +500% with respect to historical conditions are noted at some locations for 20-yr return values, with maximum changes by DQM and QDM nearing +240% and +140%, respectively, whereas raw GCM changes are never projected to exceed +120%.

scholarly journals Northern Hemisphere storminess in the Norwegian Earth System Model (NorESM1-M)

2016 ◽  
Vol 9 (7) ◽  
pp. 2335-2355 ◽  
Author(s):  
Erlend M. Knudsen ◽  
John E. Walsh
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
System Model ◽  
High Latitudes ◽  
Earth System ◽  
Projected Changes

Abstract. Metrics of storm activity in Northern Hemisphere high and midlatitudes are evaluated from historical output and future projections by the Norwegian Earth System Model (NorESM1-M) coupled global climate model. The European Re-Analysis Interim (ERA-Interim) and the Community Climate System Model (CCSM4), a global climate model of the same vintage as NorESM1-M, provide benchmarks for comparison. The focus is on the autumn and early winter (September through December) – the period when the ongoing and projected Arctic sea ice retreat is the greatest. Storm tracks derived from a vorticity-based algorithm for storm identification are reproduced well by NorESM1-M, although the tracks are somewhat better resolved in the higher-resolution ERA-Interim and CCSM4. The tracks show indications of shifting polewards in the future as climate changes under the Representative Concentration Pathway (RCP) forcing scenarios. Cyclones are projected to become generally more intense in the high latitudes, especially over the Alaskan region, although in some other areas the intensity is projected to decrease. While projected changes in track density are less coherent, there is a general tendency towards less frequent storms in midlatitudes and more frequent storms in high latitudes, especially the Baffin Bay/Davis Strait region in September. Autumn precipitation is projected to increase significantly across the entire high latitudes. Together with the projected loss of sea ice and increases in storm intensity and sea level, this increase in precipitation implies a greater vulnerability to coastal flooding and erosion, especially in the Alaskan region. The projected changes in storm intensity and precipitation (as well as sea ice and sea level pressure) scale generally linearly with the RCP value of the forcing and with time through the 21st century.

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