scholarly journals Dynamical Downscaling Projections of Late 21st Century U.S. Landfalling Hurricane Activity

2021 ◽  
Author(s):  
Thomas R Knutson ◽  
Joseph J. Sirutis ◽  
Morris A. Bender ◽  
Robert E. Tuleya
Keyword(s):  
Dynamical Downscaling ◽  
Statistical Significance ◽  
Atmospheric Model ◽  
Tropical Storms ◽  
Translation Speed ◽  
Hurricane Wind ◽  
Late 21St Century ◽  
Hurricane Activity ◽  
Storm Rainfall ◽  
Ensembles Project

Abstract U.S. landfalling tropical cyclone (TC) activity was projected for late 21st century conditions using a two-step dynamical downscaling framework. A regional atmospheric model, run for 27 seasons, generated tropical storm cases. Each storm case was re-simulated (up to 15 days) using the higher resolution GFDL hurricane model. Thirteen CMIP3 or CMIP5 modeled climate change projections were explored as scenarios. Robustness of projections was assessed using statistical significance tests and comparing the sign of changes derived from different models. The proportion of TCs (tropical storms and hurricanes) making U.S. landfall increases for the warming scenarios (by order 50% or more). For category 1-3 hurricane frequency, a robust decrease is projected (basin-wide), but robust changes are not projected for U.S. landfalling cases. A relatively robust increase in U.S. landfalling category 4-5 hurricane frequency is projected, averaging about +400% across the models; 10 of 13 models/ensembles project an increase (statistically significant in three individual models), while three models projected no change. The most robust projections overall for U.S. landfalling TC activity are for increased near-storm rainfall rates: these increases average +18% (all tropical storms and hurricanes), +26% (all hurricanes), and +37% (major hurricanes). Landfalling hurricane wind speed intensities show no robust signal, in contrast to a ~5% increase in basin-averaged TC intensity; basin-wide Power Dissipation Index (PDI) is projected to decrease, partly due to decreased duration. TC translation speed increases a few percent in most simulations. A caveat is the framework’s low correlation of modeled U.S. TC landfalls vs. observed interannual variations (1980-2016).

Evaluating climate model simulations of precipitation: methods, problems and performance

1995 ◽  
Vol 19 (4) ◽  
pp. 427-448 ◽  
Author(s):  
Martin Airey ◽  
Mike Hulme
Keyword(s):  
Model Evaluation ◽  
Climate Model ◽  
Spatial Scales ◽  
Evaluation Studies ◽  
Statistical Significance ◽  
Atmospheric Model ◽  
System Modelling ◽  
Statistical Significance Testing ◽  
Model Simulations ◽  
Global Precipitation

Climate system modelling has been used extensively to investigate the role of human activities in causing global change. Model evaluation assesses the ability of the models used to simulate current climate. This article reviews the methodology of model evaluation with examples from recent studies involving precipitation. This crucial element of climate is difficult to model since the majority of precipitation occurs at scales less than that of the gridboxes of the highest resolution models. Detailed and reliable evaluation requires investigation of interannual variability as well as of climatological means on a variety of spatial scales. This sort of detailed analysis requires time-series of observed global precipitation at monthly time-steps or less. No single currently available global dataset of precipitation fulfils all the requirements for model evaluation, making the comparison of modelled global precipitation fields with 'reality' difficult. A number of recent precipitation evaluation projects are reviewed and a hierarchy of evaluation methods is provided based on spatial and temporal scale and whether or not tests for statistical significance are applied. Most studies to date have not tested for statistical significance, although when models improve with higher resolution and better physical parameterizations, statistical significance testing of differences will become increasingly more essential. The problems of evaluating modelled precipitation are being tackled by international projects such as the Global Precipitation Climatology Project, the WetNet Precipitation Intercomparison Projects and the Atmospheric Model Intercomparison Project. The results of evaluation studies to date emphasize that model simulations of future changes to the magnitude, timing and spatial pattern of global precipitation be viewed as scenarios and not as predictions.

scholarly journals Effect of prescribed sea surface conditions on the modern and future Antarctic surface climate simulated by the ARPEGE atmosphere general circulation model

2019 ◽  
Vol 13 (11) ◽  
pp. 3023-3043
Author(s):  
Julien Beaumet ◽  
Michel Déqué ◽  
Gerhard Krinner ◽  
Cécile Agosta ◽  
Antoinette Alias
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Atmospheric Model ◽  
Sea Surface ◽  
Coupled Climate Model ◽  
Surface Climate ◽  
Late 21St Century ◽  
The Antarctic

Abstract. Owing to increase in snowfall, the Antarctic Ice Sheet surface mass balance is expected to increase by the end of the current century. Assuming no associated response of ice dynamics, this will be a negative contribution to sea-level rise. However, the assessment of these changes using dynamical downscaling of coupled climate model projections still bears considerable uncertainties due to poorly represented high-southern-latitude atmospheric circulation and sea surface conditions (SSCs), that is sea surface temperature and sea ice concentration. This study evaluates the Antarctic surface climate simulated using a global high-resolution atmospheric model and assesses the effects on the simulated Antarctic surface climate of two different SSC data sets obtained from two coupled climate model projections. The two coupled models from which SSCs are taken, MIROC-ESM and NorESM1-M, simulate future Antarctic sea ice trends at the opposite ends of the CMIP5 RCP8.5 projection range. The atmospheric model ARPEGE is used with a stretched grid configuration in order to achieve an average horizontal resolution of 35 km over Antarctica. Over the 1981–2010 period, ARPEGE is driven by the SSCs from MIROC-ESM, NorESM1-M and CMIP5 historical runs and by observed SSCs. These three simulations are evaluated against the ERA-Interim reanalyses for atmospheric general circulation as well as the MAR regional climate model and in situ observations for surface climate. For the late 21st century, SSCs from the same coupled climate models forced by the RCP8.5 emission scenario are used both directly and bias-corrected with an anomaly method which consists in adding the future climate anomaly from coupled model projections to the observed SSCs with taking into account the quantile distribution of these anomalies. We evaluate the effects of driving the atmospheric model by the bias-corrected instead of the original SSCs. For the simulation using SSCs from NorESM1-M, no significantly different climate change signals over Antarctica as a whole are found when bias-corrected SSCs are used. For the simulation driven by MIROC-ESM SSCs, a significant additional increase in precipitation and in winter temperatures for the Antarctic Ice Sheet is obtained when using bias-corrected SSCs. For the range of Antarctic warming found (+3 to +4 K), we confirm that snowfall increase will largely outweigh increases in melt and rainfall. Using the end members of sea ice trends from the CMIP5 RCP8.5 projections, the difference in warming obtained (∼ 1 K) is much smaller than the spread of the CMIP5 Antarctic warming projections. This confirms that the errors in representing the Southern Hemisphere atmospheric circulation in climate models are also determinant for the diversity of their projected late 21st century Antarctic climate change.

scholarly journals Using a Scale-Selective Filter for Dynamical Downscaling with the Conformal Cubic Atmospheric Model

2009 ◽  
Vol 137 (6) ◽  
pp. 1742-1752 ◽  
Author(s):  
Marcus Thatcher ◽  
John L. McGregor
Keyword(s):  
Dynamical Downscaling ◽  
Atmospheric Model ◽  
Length Scale ◽  
Far Field ◽  
Computationally Efficient ◽  
Forecast System ◽  
Selective Filter ◽  
Similar Accuracy ◽  
2D Filter ◽  
Ncep Global Forecast System

Abstract This article examines dynamical downscaling with a scale-selective filter in the Conformal Cubic Atmospheric Model (CCAM). In this study, 1D and 2D scale-selective filters have been implemented using a convolution-based scheme, since a convolution can be readily evaluated in terms of CCAM’s native conformal cubic coordinates. The downscaling accuracy of 1D and 2D scale-selective filters is evaluated after downscaling NCEP Global Forecast System analyses for 2006 from 200-km resolution to 60-km resolution over Australia. The 1D scale-selective filter scheme was found to downscale the analyses with similar accuracy to a 2D filter but required significantly fewer computations. The 1D and 2D scale-selective filters were also found to downscale the analyses more accurately than a far-field nudging scheme (i.e., analogous to a boundary-value nudging approach). It is concluded that when the model is required to reproduce the host model behavior above a specified length scale then the use of an appropriately designed 1D scale-selective filter can be a computationally efficient approach to dynamical downscaling for models having a cube-based geometry.

Dynamical Downscaling for Assessment of the Climate in Ghana

2014 ◽  
Vol 9 (4) ◽  
pp. 412-421
Author(s):  
Masaru Inatsu ◽  
◽  
Tsubasa Nakayama ◽  
Yoshie Maeda ◽  
Hirotaka Matsuda ◽  
...  
Keyword(s):  
Dynamical Downscaling ◽  
West African Monsoon ◽  
Satellite Observation ◽  
Atmospheric Model ◽  
West African ◽  
Present Climate ◽  
The West ◽  
Local Climate ◽  
Regional Atmospheric Model ◽  
Spatio Temporal

Dynamical downscaling (DDS), in which a regional atmospheric model (RAM) experiment nested into coarser-resolution data provides a spatio-temporal fine dataset for a particular region, was performed to assess the present climate in Ghana. The DDS successfully evaluated realistic seasonal march and inter-annual variability in rainfall, in comparison with gauge and satellite observation. The DDS also indicated that land-lake and land-sea circulation interacted with the West African monsoon likely characterized the local climate in Ghana.

scholarly journals Atlantic Hurricane Season of 2011*

2013 ◽  
Vol 141 (8) ◽  
pp. 2577-2596 ◽  
Author(s):  
Lixion A. Avila ◽  
Stacy R. Stewart
Keyword(s):  
United States ◽  
The United States ◽  
Tropical Storms ◽  
Track Forecast ◽  
Forecast Errors ◽  
Eastern Canada ◽  
The Bahamas ◽  
Hurricane Wind ◽  
Level Of Activity ◽  
High Level

Abstract The 2011 Atlantic season was marked by above-average tropical cyclone activity with the formation of 19 tropical storms. Seven of the storms became hurricanes and four became major hurricanes (category 3 or higher on the Saffir–Simpson hurricane wind scale). The numbers of tropical storms and hurricanes were above the long-term averages of 12 named storms, 6 hurricanes, and 3 major hurricanes. Despite the high level of activity, Irene was the only hurricane to hit land in 2011, striking both the Bahamas and the United States. Other storms, however, affected the United States, eastern Canada, Central America, eastern Mexico, and the northeastern Caribbean Sea islands. The death toll from the 2011 Atlantic tropical cyclones is 80. National Hurricane Center mean official track forecast errors in 2011 were smaller than the previous 5-yr means at all forecast times except 120 h. In addition, the official track forecast errors set records for accuracy at the 24-, 36-, 48-, and 72-h forecast times. The mean intensity forecast errors in 2011 ranged from about 6 kt (~3 m s−1) at 12 h to about 17 kt (~9 m s−1) at 72 and 120 h. These errors were below the 5-yr means at all forecast times.

scholarly journals Dynamical Downscaling Projections of Twenty-First-Century Atlantic Hurricane Activity: CMIP3 and CMIP5 Model-Based Scenarios

2013 ◽  
Vol 26 (17) ◽  
pp. 6591-6617 ◽  
Author(s):  
Thomas R. Knutson ◽  
Joseph J. Sirutis ◽  
Gabriel A. Vecchi ◽  
Stephen Garner ◽  
Ming Zhao ◽  
...  
Keyword(s):  
Inner Core ◽  
Dynamical Downscaling ◽  
Coupled Model ◽  
First Century ◽  
Cmip5 Models ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Model Intercomparison ◽  
Intercomparison Project ◽  
Hurricane Activity ◽  
Twenty First Century

Abstract Twenty-first-century projections of Atlantic climate change are downscaled to explore the robustness of potential changes in hurricane activity. Multimodel ensembles using the phase 3 of the Coupled Model Intercomparison Project (CMIP3)/Special Report on Emissions Scenarios A1B (SRES A1B; late-twenty-first century) and phase 5 of the Coupled Model Intercomparison Project (CMIP5)/representative concentration pathway 4.5 (RCP4.5; early- and late-twenty-first century) scenarios are examined. Ten individual CMIP3 models are downscaled to assess the spread of results among the CMIP3 (but not the CMIP5) models. Downscaling simulations are compared for 18-km grid regional and 50-km grid global models. Storm cases from the regional model are further downscaled into the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model (9-km inner grid spacing, with ocean coupling) to simulate intense hurricanes at a finer resolution. A significant reduction in tropical storm frequency is projected for the CMIP3 (−27%), CMIP5-early (−20%) and CMIP5-late (−23%) ensembles and for 5 of the 10 individual CMIP3 models. Lifetime maximum hurricane intensity increases significantly in the high-resolution experiments—by 4%–6% for CMIP3 and CMIP5 ensembles. A significant increase (+87%) in the frequency of very intense (categories 4 and 5) hurricanes (winds ≥ 59 m s−1) is projected using CMIP3, but smaller, only marginally significant increases are projected (+45% and +39%) for the CMIP5-early and CMIP5-late scenarios. Hurricane rainfall rates increase robustly for the CMIP3 and CMIP5 scenarios. For the late-twenty-first century, this increase amounts to +20% to +30% in the model hurricane’s inner core, with a smaller increase (~10%) for averaging radii of 200 km or larger. The fractional increase in precipitation at large radii (200–400 km) approximates that expected from environmental water vapor content scaling, while increases for the inner core exceed this level.

scholarly journals Dynamic downscaling of the ERA-40 data using a mesoscale meteorological model

2011 ◽  
Vol 12 (1) ◽  
pp. 183 ◽  
Author(s):  
A. PAPADOPOULOS ◽  
G. KORRES ◽  
P. KATSAFADOS ◽  
D. BALLAS ◽  
L. PERIVOLIOTIS ◽  
...  
Keyword(s):  
Dynamical Downscaling ◽  
Weather Forecasting ◽  
Quantitative Estimation ◽  
Three Dimensional ◽  
Atmospheric Model ◽  
Hydrological Models ◽  
Atmospheric Conditions ◽  
Meteorological Model ◽  
Medium Range ◽  
Forecasting System

A sophisticated downscaling procedure that was applied to reproduce high resolution historical records of the atmospheric conditions across the Mediterranean region is presented in this paper. This was accomplished by the dynamical downscaling of the European Center for Medium-Range Forecasts ERA-40 reanalyses with the aid of the atmospheric model of the POSEIDON weather forecasting system. The full three dimensional atmospheric fields with 6 hours of temporal resolution and the surface meteorological parameters at hourly intervals were produced for a 10-year period (1995-2004). The meteorological variables are readily available at 10 km resolution and may constitute the atmospheric forcing to drive wave, ocean hydrodynamic and hydrological models, as well as the baseline data for environmental impact assessment studies. A brief overview of the procedure and a quantitative estimation of the benefit of the new dynamical downscaling dataset are presented.

scholarly journals Modeling and Parameter Estimation of Hurricane Wind Fields with Asymmetry

2020 ◽  
Vol 59 (4) ◽  
pp. 687-705
Author(s):  
Derek Chang ◽  
Saurabh Amin ◽  
Kerry Emanuel
Keyword(s):  
Wind Field ◽  
Wind Shear ◽  
Field Model ◽  
Estimation Method ◽  
Translation Vector ◽  
Model Parameters ◽  
Wind Fields ◽  
Translation Speed ◽  
Wind Field Model ◽  
Hurricane Wind

AbstractThis article presents an azimuthally asymmetric gradient hurricane wind field model that can be coupled with hurricane-track models for engineering wind risk assessments. The model incorporates low-wavenumber asymmetries into the maximum wind intensity parameter of the Holland et al. wind field model. The amplitudes and phases of the asymmetries are parametric functions of the storm-translation speed and wind shear. Model parameters are estimated by solving a constrained, nonlinear least squares (CNLS) problem that minimizes the sum of squared residuals between wind field intensities of historical storms and model-estimated winds. There are statistically significant wavenumber-1 asymmetries in the wind field resulting from both storm translation and wind shear. Adding the translation vector to the wind field model with wavenumber-1 asymmetries further improves the model’s estimation performance. In addition, inclusion of the wavenumber-1 asymmetry resulting from translation results in a greater decrease in modeling error than does inclusion of the wavenumber-1 shear-induced asymmetry. Overall, the CNLS estimation method can handle the inherently nonlinear wind field model in a flexible manner; thus, it is well suited to capture the radial variability in the hurricane wind field’s asymmetry. The article concludes with brief remarks on how the CNLS-estimated model can be applied for simulating wind fields in a statistically generated ensemble.

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