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 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 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 Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics

2016 ◽  
Vol 29 (2) ◽  
pp. 543-560 ◽  
Author(s):  
Ming Zhao ◽  
J.-C. Golaz ◽  
I. M. Held ◽  
V. Ramaswamy ◽  
S.-J. Lin ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Convective Precipitation ◽  
Climate Projections ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Convection Parameterization ◽  
Comparable Quality

Abstract Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the intermodel spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, the authors use a developmental version of the next-generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the model ensemble from phase 5 of CMIP (CMIP5). The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere–land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear observational constraint that favors one version of the authors’ model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.

scholarly journals Projected Response of Tropical Cyclone Intensity and Intensification in a Global Climate Model

2018 ◽  
Vol 31 (20) ◽  
pp. 8281-8303 ◽  
Author(s):  
Kieran Bhatia ◽  
Gabriel Vecchi ◽  
Hiroyuki Murakami ◽  
Seth Underwood ◽  
James Kossin
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Climate Models ◽  
Control Experiment ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
First Century ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Twenty First Century

As one of the first global coupled climate models to simulate and predict category 4 and 5 (Saffir–Simpson scale) tropical cyclones (TCs) and their interannual variations, the High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) model at the Geophysical Fluid Dynamics Laboratory (GFDL) represents a novel source of insight on how the entire TC intensification distribution could be transformed because of climate change. In this study, three 70-yr HiFLOR experiments are performed to identify the effects of climate change on TC intensity and intensification. For each of the experiments, sea surface temperature (SST) is nudged to different climatological targets and atmospheric radiative forcing is specified, allowing us to explore the sensitivity of TCs to these conditions. First, a control experiment, which uses prescribed climatological ocean and radiative forcing based on observations during the years 1986–2005, is compared to two observational records and evaluated for its ability to capture the mean TC behavior during these years. The simulated intensification distributions as well as the percentage of TCs that become major hurricanes show similarities with observations. The control experiment is then compared to two twenty-first-century experiments, in which the climatological SSTs from the control experiment are perturbed by multimodel projected SST anomalies and atmospheric radiative forcing from either 2016–35 or 2081–2100 (RCP4.5 scenario). The frequency, intensity, and intensification distribution of TCs all shift to higher values as the twenty-first century progresses. HiFLOR’s unique response to climate change and fidelity in simulating the present climate lays the groundwork for future studies involving models of this type.

Water cycle changes over the Mediterranean: a comparison study of a super-high-resolution global model with CMIP3

2010 ◽  
Vol 368 (1931) ◽  
pp. 5137-5149 ◽  
Author(s):  
Fengjun Jin ◽  
Akio Kitoh ◽  
Pinhas Alpert
Keyword(s):  
Climate Model ◽  
Water Cycle ◽  
Eastern Mediterranean ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Western Mediterranean ◽  
Significant Difference ◽  
The Mediterranean ◽  
Projected Changes

Water cycle components over the Mediterranean for both a current run (1979–2007) and a future run (2075–2099) are studied with the Japan Meteorological Agency’s 20 km grid global climate model. Results are compared with another study using the Coupled Model Intercomparison Project Phase 3 ensemble model (hereafter, the Mariotti model). Our results are surprisingly close to Mariotti’s. The projected mean annual change rates of precipitation ( P ) between the future and the current run for sea and land are −11 per cent and −10 per cent, respectively, which are not as high as Mariotti’s. Projected changes for evaporation ( E ) are +9.3 per cent and −3.6 per cent, compared with +7.2 per cent and −8.1 per cent in Mariotti’s study, respectively. However, no significant difference in the change in P – E over the sea body was found between these two studies. The increased E over the eastern Mediterranean was found to be higher than that in the western Mediterranean, but the P decrease was lower. The net moisture budget, P – E , shows that the eastern Mediterranean will become even drier than the western Mediterranean. The river model suggests decreasing water inflow to the Mediterranean of approximately 36 per cent (excluding the Nile).

scholarly journals Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation

2015 ◽  
Vol 8 (12) ◽  
pp. 10539-10583 ◽  
Author(s):  
V. Eyring ◽  
S. Bony ◽  
G. A. Meehl ◽  
C. Senior ◽  
B. Stevens ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Research Programme ◽  
Future Climate ◽  
Model Intercomparison ◽  
Historical Simulation ◽  
Intercomparison Project

Abstract. By coordinating the design and distribution of global climate model simulations of the past, current and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima experiments) and the CMIP Historical Simulation (1850–near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP, (2) common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble, and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and the CMIP Historical Simulation to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP Historical Simulation, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. The participation in the CMIP6-Endorsed MIPs will be at the discretion of the modelling groups, and will depend on scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: (i) how does the Earth system respond to forcing?, (ii) what are the origins and consequences of systematic model biases?, and (iii) how can we assess future climate changes given climate variability, predictability and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and the CMIP6 Historical Simulation, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.

scholarly journals The Impact of Climate Change on Meningitis in Northwest Nigeria: An Assessment Using CMIP5 Climate Model Simulations

2014 ◽  
Vol 6 (3) ◽  
pp. 371-379 ◽  
Author(s):  
Auwal F. Abdussalam ◽  
Andrew J. Monaghan ◽  
Daniel F. Steinhoff ◽  
Vanja M. Dukic ◽  
Mary H. Hayden ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Treatment Strategies ◽  
Coupled Model ◽  
Annual Incidence ◽  
Future Climate ◽  
Future Climate Change ◽  
The Impact

Abstract Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily populated northwest Nigeria with an annual incidence rate ranging from 18 to 200 per 100 000 people for 2000–11. Several studies have established that cases exhibit sensitivity to intra- and interannual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations of seven meteorological variables from an ensemble of 13 statistically downscaled global climate model projections from phase 5 of the Coupled Model Intercomparison Experiment (CMIP5) for representative concentration pathway (RCP) 2.6, 6.0, and 8.5 scenarios, with the numbers representing the globally averaged top-of-the-atmosphere radiative imbalance (in W m−2) in 2100. The results suggest future temperature increases due to climate change have the potential to significantly increase meningitis cases in both the early (2020–35) and late (2060–75) twenty-first century, and for the seasonal onset of meningitis to begin about a month earlier on average by late century, in October rather than November. Annual incidence may increase by 47% ± 8%, 64% ± 9%, and 99% ± 12% for the RCP 2.6, 6.0, and 8.5 scenarios, respectively, in 2060–75 with respect to 1990–2005. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as it is assumed that current prevention and treatment strategies will remain similar in the future.

scholarly journals Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization

2016 ◽  
Vol 9 (5) ◽  
pp. 1937-1958 ◽  
Author(s):  
Veronika Eyring ◽  
Sandrine Bony ◽  
Gerald A. Meehl ◽  
Catherine A. Senior ◽  
Bjorn Stevens ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Research Programme ◽  
Climate Science ◽  
Future Climate ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.

scholarly journals GCMs Derived Projection of Precipitation and Analysis of Spatio-Temporal Variation over N-W Himalayan Region

2016 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Dharmaveer Singh ◽  
R.D. Gupta ◽  
Sanjay K. Jain
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Global Climate Models ◽  
Himalayan Region ◽  
Mean Annual Precipitation ◽  
Hadcm3 Model

The ensembles of two Global Climate Models (GCMs) namely, third generation Canadian Coupled Global Climate Model (CGCM3) and Hadley Center Coupled Model, version 3 (HadCM3) are used to project future precipitation in a part of North-Western (N-W) Himalayan region, India. Statistical downscaling method is used to downscale and generate future scenarios of precipitation at station scale from large scale climate variables obtained from GCMs. The observed historical precipitation data has been collected for three metrological stations, namely, Rampur, Sunni and Kasol falling in the basin for further analysis. The future trends and patterns in precipitation under scenarios A2 and A1B for CGCM3 model, and A2 and B2 for HadCM3 model are analyzed for these stations under three different time periods: 2020’s, 2050’s and 2080’s. An overall rise in mean annual precipitation under scenarios A2 and A1B for CGCM3 model have been noticed for future periods: 2020’s, 2050’s and 2080’s. Decrease, in precipitation has been found under A2 and B2 scenarios of HadCM3 model for 2050’s and slight increase for 2080’s periods. Based on the analysis of results, CGCM3 model has been found better for simulation of precipitation in comparison to HadCM3 model.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.1-14

scholarly journals Set-up of the PMIP3 paleoclimate experiments conducted using an Earth system model, MIROC-ESM

2013 ◽  
Vol 6 (3) ◽  
pp. 819-836 ◽  
Author(s):  
T. Sueyoshi ◽  
R. Ohgaito ◽  
A. Yamamoto ◽  
M. O. Chikamoto ◽  
T. Hajima ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Volcanic Eruptions ◽  
Earth System ◽  
Good Test ◽  
Effective Measure ◽  
Intercomparison Project

Abstract. Paleoclimate experiments using contemporary climate models are an effective measure to evaluate climate models. In recent years, Earth system models (ESMs) were developed to investigate carbon cycle climate feedbacks, as well as to project the future climate. Paleoclimate events can be suitable benchmarks to evaluate ESMs. The variation in aerosols associated with the volcanic eruptions provide a clear signal in forcing, which can be a good test to check the response of a climate model to the radiation changes. The variations in atmospheric CO2 level or changes in ice sheet extent can be used for evaluation as well. Here we present implementations of the paleoclimate experiments proposed by the Coupled Model Intercomparison Project phase 5/Paleoclimate Modelling Intercomparison Project phase 3 (CMIP5/PMIP3) using MIROC-ESM, an ESM based on the global climate model MIROC (Model for Interdisciplinary Research on Climate). In this paper, experimental settings and spin-up procedures of the mid-Holocene, the Last Glacial Maximum, and the Last Millennium experiments are explained. The first two experiments are time slice experiments and the last one is a transient experiment. The complexity of the model requires various steps to correctly configure the experiments. Several basic outputs are also shown.

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