scholarly journals An Assessment of a Model-, Grid-, and Basin-Independent Tropical Cyclone Detection Scheme in Selected CMIP3 Global Climate Models

2013 ◽  
Vol 26 (15) ◽  
pp. 5508-5522 ◽  
Author(s):  
K. J. Tory ◽  
S. S. Chand ◽  
R. A. Dare ◽  
J. L. McBride
Keyword(s):  
Tropical Cyclone ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Max Planck ◽  
Detection Scheme ◽  
Coarse Resolution

Abstract A novel tropical cyclone (TC) detection technique designed for coarse-resolution models is tested and evaluated. The detector, based on the Okubo–Weiss–Zeta parameter (OWZP), is applied to a selection of Coupled Model Intercomparison Project, phase 3 (CMIP3), models [Commonwealth Scientific and Industrial Research Organisation Mark, version 3.5 (CSIRO-Mk3.5); Max Planck Institute ECHAM5 (MPI-ECHAM5); and Geophysical Fluid Dynamics Laboratory Climate Model, versions 2.0 (GFDL CM2.0) and 2.1 (GFDL CM2.1)], and the combined performance of the model and detector is assessed by comparison with observed TC climatology for the period 1970–2000. Preliminary TC frequency projections are made using the three better-performing models by comparing the detected TC climatologies between the late twentieth and late twenty-first centuries. Very reasonable TC formation climatologies were detected in CSIRO-Mk3.5, MPI-ECHAM5, and GFDL CM2.1 for most basins, with the exception of the North Atlantic, where a large underdetection was present in all models. The GFDL CM2.0 model was excluded from the projection study because of a systematic underdetection in all basins. The above detection problems have been reported in other published studies, which suggests model rather than detector limitations are mostly responsible. This study demonstrates that coarse-resolution climate models do in general produce TC-like circulations with realistic geographical and seasonal distributions detectable by the OWZP TC detector. The preliminary projection results are consistent with the published literature, based on higher-resolution studies, of a global reduction of TCs between about 6% and 20%, with a much larger spread of results (about +20% to −50%) in individual basins.

Precipitation Associated with Cyclogenetic Hotspot Regions in the Extratropical Southern Hemisphere: CORDEX-CORE Projections

2020 ◽  
Author(s):  
Michelle Reboita ◽  
Marco Reale ◽  
Rosmeri da Rocha ◽  
Graziano Giuliani ◽  
Erika Coppola ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Winter Season ◽  
Coupled Model ◽  
Global Climate Models ◽  
Precipitation Intensity ◽  
Southeastern Australia

<p>Projections of the precipitation associated with cyclones in the main cyclogenetic regions of the Extratropical Southern Hemisphere domains (Africa - AFR, Australia - AUS and South America - SAM) are here analyzed during the winter season (JJA). The projections were obtained with the Regional Climate Model version 4 (RegCM4) nested in three global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5) under the Representative Concentration Pathway 8.5. RegCM4 simulations were executed with horizontal grid spacing of 25 km and for the period 1979-2100. As reference period, we consider the interval 1995-2014 and as future climate, the period 2080-2099. Cyclones are identified using an algorithm based on the neighbor nearest approach applied to 6 hourly mean sea level pressure (SLP) fields. In SAM and AUS domains, two hotspot regions for cyclogenesis are selected while for AFR only one is considered. First, in each hotspot region, the cyclogeneses are identified and, then, the mean precipitation from the previous day (day<sub>-1</sub>) to the day after (day<sub>+1</sub>) of these processes is calculated. A general negative trend in the cyclone's frequency is projected for the period 2080-2099. However, for the same period, it is projected an increase of precipitation intensity for AFR domain, mainly near the southwestern coast of the continent. In AUS the increase is observed between southeastern Australia and New Zeland, and over north New Zealand. For SAM there is an expansion of the area with a maximum precipitation intensity close to southern Brazil and Uruguay and to the east of 60<sup>o</sup>W near 40<sup>o</sup>S. Summarizing, the precipitation associated with individual cyclones will increase on average in the future (for example 30% in the SAM domain), being the storms less frequent but more intense.</p>

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 Connecting Climate Model Projections of Global Temperature Change with the Real World

2016 ◽  
Vol 97 (6) ◽  
pp. 963-980 ◽  
Author(s):  
Ed Hawkins ◽  
Rowan Sutton
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Global Temperature ◽  
Climate Projections ◽  
Reference Period ◽  
Intergovernmental Panel ◽  
Temperature Levels

Abstract Current state-of-the-art global climate models produce different values for Earth’s mean temperature. When comparing simulations with each other and with observations, it is standard practice to compare temperature anomalies with respect to a reference period. It is not always appreciated that the choice of reference period can affect conclusions, both about the skill of simulations of past climate and about the magnitude of expected future changes in climate. For example, observed global temperatures over the past decade are toward the lower end of the range of the phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations irrespective of what reference period is used, but exactly where they lie in the model distribution varies with the choice of reference period. Additionally, we demonstrate that projections of when particular temperature levels are reached, for example, 2 K above “preindustrial,” change by up to a decade depending on the choice of reference period. In this article, we discuss some of the key issues that arise when using anomalies relative to a reference period to generate climate projections. We highlight that there is no perfect choice of reference period. When evaluating models against observations, a long reference period should generally be used, but how long depends on the quality of the observations available. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) choice to use a 1986–2005 reference period for future global temperature projections was reasonable, but a case-by-case approach is needed for different purposes and when assessing projections of different climate variables. Finally, we recommend that any studies that involve the use of a reference period should explicitly examine the robustness of the conclusions to alternative choices.

scholarly journals Observed versus GCM-Generated Local Tropical Cyclone Frequency: Comparisons Using a Spatial Lattice

2013 ◽  
Vol 26 (21) ◽  
pp. 8257-8268 ◽  
Author(s):  
Sarah Strazzo ◽  
James B. Elsner ◽  
Timothy LaRow ◽  
Daniel J. Halperin ◽  
Ming Zhao
Keyword(s):  
Tropical Cyclone ◽  
Climate Models ◽  
North Atlantic Ocean ◽  
Global Climate ◽  
Ocean Basin ◽  
Global Climate Models ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Large Area ◽  
South Central ◽  
Spatial Lattice

Abstract Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) model over the common period 1982–2008. Results show that the spatial distribution of TCs generated by the GFDL model compares well with observations globally, although there are areas of over- and underprediction, particularly in parts of the Pacific Ocean. Difference maps using the spatial lattice highlight these discrepancies. Additionally, comparisons focusing on the North Atlantic Ocean basin are made. Results confirm a large area of overprediction by the FSU COAPS model in the south-central portion of the basin. Relevant to projections of future U.S. hurricane activity is the fact that both models underpredict TC activity in the Gulf of Mexico.

scholarly journals Defining metrics of the Quasi-Biennial Oscillation in global climate models

2017 ◽  
Vol 10 (6) ◽  
pp. 2157-2168 ◽  
Author(s):  
Verena Schenzinger ◽  
Scott Osprey ◽  
Lesley Gray ◽  
Neal Butchart
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Dominant Mode ◽  
Global Climate Models ◽  
Mean Flow ◽  
Quasi Biennial Oscillation ◽  
Radiosonde Observation ◽  
Biennial Oscillation

Abstract. As the dominant mode of variability in the tropical stratosphere, the Quasi-Biennial Oscillation (QBO) has been subject to extensive research. Though there is a well-developed theory of this phenomenon being forced by wave–mean flow interaction, simulating the QBO adequately in global climate models still remains difficult. This paper presents a set of metrics to characterize the morphology of the QBO using a number of different reanalysis datasets and the FU Berlin radiosonde observation dataset. The same metrics are then calculated from Coupled Model Intercomparison Project 5 and Chemistry-Climate Model Validation Activity 2 simulations which included a representation of QBO-like behaviour to evaluate which aspects of the QBO are well captured by the models and which ones remain a challenge for future model development.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements

2017 ◽  
Vol 17 (7) ◽  
pp. 4451-4475 ◽  
Author(s):  
Ilissa B. Ocko ◽  
Paul A. Ginoux
Keyword(s):  
Climate Models ◽  
Climate Modeling ◽  
Global Climate ◽  
Measurement Techniques ◽  
Global Climate Models ◽  
Orthogonal Polarization ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Multiple Model ◽  
Anthropogenic Aerosols ◽  
Aerosol Properties

Abstract. Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud–Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

2021 ◽  
pp. 1-69
Author(s):  
Zane Martin ◽  
Clara Orbe ◽  
Shuguang Wang ◽  
Adam Sobel
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Quasi Biennial Oscillation ◽  
Meridional Winds ◽  
Goddard Institute ◽  
Minimal Bias

AbstractObservational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection.

scholarly journals A prognostic pollen emissions model for climate models (PECM1.0)

2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner
Keyword(s):  
United States ◽  
Land Cover ◽  
Climate Models ◽  
Climate Model ◽  
Vegetation Type ◽  
Global Climate ◽  
The United States ◽  
Global Climate Models ◽  
Pollen Counts ◽  
Surface Pollen

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

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