EXPLORING INLAND TROPICAL CYCLONE RAINFALL AND TORNADOES UNDER FUTURE CLIMATE CONDITIONS THROUGH A CASE STUDY OF HURRICANE IVAN

2020 ◽  
Author(s):  
Dereka Carroll-Smith ◽  
Robert J. Trapp ◽  
James M. Done
Keyword(s):  
Climate Change ◽  
Tropical Cyclone ◽  
Climate Models ◽  
Climate Model ◽  
Convective Available Potential Energy ◽  
Track Length ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Climate System Model ◽  
Hurricane Ivan ◽  
Model Version

AbstractThe overarching purpose of this study is to investigate the impacts of anthropogenic climate change both on the rainfall and tornadoes associated with tropical cyclones (TCs) making landfall in the U.S. Atlantic Basin. The “pseudo-global” warming (PGW) approach is applied to Hurricane Ivan (2004), a historically prolific tropical cyclone tornado (TCT)-producing storm. Hurricane Ivan is simulated under its current climate forcings using the Weather Research and Forecasting model. This control simulation (CTRL) is then compared to PGW simulations in which the current forcings are modified by climate-change differences obtained from the Community Climate System Model version 4 (NCAR), Model for Interdisciplinary Research on Climate version 5 (MIROC), and Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL) climate models. Changes in TC intensity, TC rainfall, and TCT production, identified for the PGW-modified Ivan are documented and analyzed.Compared to CTRL, all three PGW simulations show an increase in TC intensity and generate substantially more accumulated rainfall over the course of Ivan’s progression overland. However, only one of the TCs under PGW (MIROC) produced more TCTs than the control. Evidence is provided that in addition to favorable environmental conditions, TCT production is related to the TC track length and to the strength of the interaction between the TC and an environmental mid-level trough. Enhanced TCT generation at landfall for MIROC and GFDL is attributed to increased values of convective available potential energy, low level shear and storm relative environmental helicity.

scholarly journals Dynamical Downscaling for Southeast Alaska: Historical Climate and Future Projections

2020 ◽  
Vol 59 (10) ◽  
pp. 1607-1623
Author(s):  
Rick Lader ◽  
Allison Bidlack ◽  
John E. Walsh ◽  
Uma S. Bhatt ◽  
Peter A. Bieniek
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Forest Health ◽  
Warm Season ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Southeast Alaska ◽  
Climate System Model ◽  
Model Version ◽  
Precipitation Regimes

AbstractWarming temperatures across southeast Alaska are affecting the region’s energy and transportation sectors, marine ecosystems, and forest health. More frequent above-freezing temperatures lead a transition from snow- to rain-dominant precipitation regimes, accelerating glacial mass balance loss and a leading to a greater risk for warm-season drought. Southeast Alaska has steep topographical gradients, which necessitate the use of downscaled climate information to study historical and projected periods. This study used regional dynamical downscaling at 4-km spatial resolution with the Weather Research and Forecasting Model to assess historical (1981–2010) and projected (2031–60) climate states for southeast Alaska. These simulations were driven by one reanalysis (i.e., the Climate Forecast System Reanalysis) and two climate models (i.e., the Geophysical Fluid Dynamics Laboratory Climate Model, version 3, and the NCAR Community Climate System Model, version 4), which each included a historical simulation and a projected simulation. The future simulations used the representative concentration pathway 8.5 emissions scenario. Bias-corrected projections (2031–60 minus 1981–2010) indicated seasonal warming of 1°–3°C, increased precipitation during autumn (4%–12%) and winter (7%–12%), and decreased snowfall in all seasons (up to 60% in autumn). The average number of days annually with a minimum temperature below freezing dropped by more than 30. The average annual maximum consecutive 3-day precipitation amounts increased by 11%–16%, but analogous extreme snowfall amounts dropped by 5%–11%. The most substantial snow losses occurred at low-elevation and coastal locations; at many high elevations (e.g., above 1000 m), extreme snowfall amounts increased.

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.

Climate Model Forecast Experiments for TOGA COARE

2008 ◽  
Vol 136 (3) ◽  
pp. 808-832 ◽  
Author(s):  
J. Boyle ◽  
S. Klein ◽  
G. Zhang ◽  
S. Xie ◽  
X. Wei
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Deep Convection ◽  
Atmospheric Model ◽  
Static Stability ◽  
Geophysical Fluid Dynamics Laboratory ◽  
State Variables ◽  
Tropical Ocean ◽  
Model Version ◽  
Toga Coare

Abstract Short-term (1–10 day) forecasts are made with climate models to assess the parameterizations of the physical processes. The time period for the integrations is that of the intensive observing period (IOP) of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). The models used are the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3.1 (CAM3.1); CAM3.1 with a modified deep convection parameterization; and the Geophysical Fluid Dynamics Laboratory (GFDL) Atmospheric Model, version 2 (AM2). The models were initialized using the state variables from the 40-yr ECMWF Re-Analysis (ERA-40). The CAM deep convective parameterization fails to demonstrate the sensitivity to the imposed forcing to simulate precipitation patterns associated with the Madden–Julian oscillations (MJOs) present during the period. AM2 and modified CAM3.1 exhibit greater correspondence to the observations at the TOGA COARE site, suggesting that convective parameterizations that have some type of limiter (as do AM2 and the modified CAM3.1) simulate the MJO rainfall with more fidelity than those without. None of the models are able to fully capture the correct phasing of westerly wind bursts with respect to precipitation in the eastward-moving MJO disturbance. Better representation of the diabatic heating and effective static stability profiles is associated with a better MJO simulation. Because the models’ errors in the forecast mode bear a resemblance to the errors in the climate mode in simulating the MJO, the forecasts may allow for a better way to dissect the reasons for model error.

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.

Anthropogenic Influences on Tornadic Storms

2021 ◽  
pp. 1-57
Author(s):  
Emily Bercos-Hickey ◽  
Christina M. Patricola ◽  
William A. Gallus
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Convective Available Potential Energy ◽  
Future Climate Change ◽  
Storm Events ◽  
Climate Model Simulations ◽  
Tornadic Storms ◽  
The Impact ◽  
Insight Into

AbstractThe impact of climate change on severe storms and tornadoes remains uncertain, largely owing to inconsistencies in observational data and limitations of climate models. We performed ensembles of convection-permitting climate model simulations to examine how three tornadic storms would change if similar events were to occur in pre-industrial and future climates. The choice of events includes winter, nocturnal, and spring tornadic storms to provide insight into how the timing and seasonality of storms may affect their response to climate change. Updraft helicity (UH), convective available potential energy (CAPE), storm relative helicity (SRH), and convective inhibition (CIN) were used to determine the favorability for the three tornadic storm events in the different climate states. We found that from the pre-industrial to present, the potential for tornadic storms decreased in the winter event and increased in the nocturnal and spring events. With future climate change, the potential for tornadic storms increased in the winter and nocturnal events in association with increased CAPE, and decreased in the spring event despite greater CAPE.

scholarly journals Evaluating the Uncertainty Induced by the Virtual Salt Flux Assumption in Climate Simulations and Future Projections

2010 ◽  
Vol 23 (1) ◽  
pp. 80-96 ◽  
Author(s):  
Jianjun Yin ◽  
Ronald J. Stouffer ◽  
Michael J. Spelman ◽  
Stephen M. Griffies
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Ocean Model ◽  
Salt Flux ◽  
Freshwater Flux ◽  
Unexpected Result ◽  
Geophysical Fluid Dynamics Laboratory ◽  
External Forcing ◽  
Future Evolution ◽  
Near Term

Abstract The unphysical virtual salt flux (VSF) formulation widely used in the ocean component of climate models has the potential to cause systematic and significant biases in modeling the climate system and projecting its future evolution. Here a freshwater flux (FWF) and a virtual salt flux version of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1) are used to evaluate and quantify the uncertainties induced by the VSF formulation. Both unforced and forced runs with the two model versions are performed and compared in detail. It is found that the differences between the two versions are generally small or statistically insignificant in the unforced control runs and in the runs with a small external forcing. In response to a large external forcing, however, some biases in the VSF version become significant, especially the responses of regional salinity and global sea level. However, many fundamental aspects of the responses differ only quantitatively between the two versions. An unexpected result is the distinctly different ENSO responses. Under a strong external freshwater forcing, the great enhancement of the ENSO variability simulated by the FWF version does not occur in the VSF version and is caused by the overexpansion of the top model layer. In summary, the principle assumption behind using virtual salt flux is not seriously violated and the VSF model has the ability to simulate the current climate and project near-term climate evolution. For some special studies such as a large hosing experiment, however, both the VSF formulation and the use of the FWF in the geopotential coordinate ocean model could have some deficiencies and one should be cautious to avoid them.

scholarly journals Pan-spectral observing system simulation experiments of shortwave reflectance and long-wave radiance for climate model evaluation

2015 ◽  
Vol 8 (7) ◽  
pp. 1943-1954 ◽  
Author(s):  
D. R. Feldman ◽  
W. D. Collins ◽  
J. L. Paige
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Coupled Model ◽  
Climate System ◽  
Spectral Measurements ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Detection And Attribution ◽  
Long Wave ◽  
Hadley Centre

Abstract. Top-of-atmosphere (TOA) spectrally resolved shortwave reflectances and long-wave radiances describe the response of the Earth's surface and atmosphere to feedback processes and human-induced forcings. In order to evaluate proposed long-duration spectral measurements, we have projected 21st Century changes from the Community Climate System Model (CCSM3.0) conducted for the Intergovernmental Panel on Climate Change (IPCC) A2 Emissions Scenario onto shortwave reflectance spectra from 300 to 2500 nm and long-wave radiance spectra from 2000 to 200 cm−1 at 8 nm and 1 cm−1 resolution, respectively. The radiative transfer calculations have been rigorously validated against published standards and produce complementary signals describing the climate system forcings and feedbacks. Additional demonstration experiments were performed with the Model for Interdisciplinary Research on Climate (MIROC5) and Hadley Centre Global Environment Model version 2 Earth System (HadGEM2-ES) models for the Representative Concentration Pathway 8.5 (RCP8.5) scenario. The calculations contain readily distinguishable signatures of low clouds, snow/ice, aerosols, temperature gradients, and water vapour distributions. The goal of this effort is to understand both how climate change alters reflected solar and emitted infrared spectra of the Earth and determine whether spectral measurements enhance our detection and attribution of climate change. This effort also presents a path forward to understand the characteristics of hyperspectral observational records needed to confront models and inline instrument simulation. Such simulation will enable a diverse set of comparisons between model results from coupled model intercomparisons and existing and proposed satellite instrument measurement systems.

scholarly journals Climate-mediated changes to mixed-layer properties in the Southern Ocean: assessing the phytoplankton response

2008 ◽  
Vol 5 (3) ◽  
pp. 847-864 ◽  
Author(s):  
P. W. Boyd ◽  
S. C. Doney ◽  
R. Strzepek ◽  
J. Dusenberry ◽  
K. Lindsay ◽  
...  
Keyword(s):  
Climate Change ◽  
Southern Ocean ◽  
Climate Model ◽  
Environmental Changes ◽  
Environmental Control ◽  
Climate System Model ◽  
Climate Change Effects ◽  
Detection And Attribution ◽  
Key Species ◽  
Phytoplankton Functional Groups

Abstract. Concurrent changes in ocean chemical and physical properties influence phytoplankton dynamics via alterations in carbonate chemistry, nutrient and trace metal inventories and upper ocean light environment. Using a fully coupled, global carbon-climate model (Climate System Model 1.4-carbon), we quantify anthropogenic climate change relative to the background natural interannual variability for the Southern Ocean over the period 2000 and 2100. Model results are interpreted using our understanding of the environmental control of phytoplankton growth rates – leading to two major findings. Firstly, comparison with results from phytoplankton perturbation experiments, in which environmental properties have been altered for key species (e.g., bloom formers), indicates that the predicted rates of change in oceanic properties over the next few decades are too subtle to be represented experimentally at present. Secondly, the rate of secular climate change will not exceed background natural variability, on seasonal to interannual time-scales, for at least several decades – which may not provide the prevailing conditions of change, i.e. constancy, needed for phytoplankton adaptation. Taken together, the relatively subtle environmental changes, due to climate change, may result in adaptation by resident phytoplankton, but not for several decades due to the confounding effects of climate variability. This presents major challenges for the detection and attribution of climate change effects on Southern Ocean phytoplankton. We advocate the development of multi-faceted tests/metrics that will reflect the relative plasticity of different phytoplankton functional groups and/or species to respond to changing ocean conditions.

scholarly journals Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Joseph Leedale ◽  
Adrian M. Tompkins ◽  
Cyril Caminade ◽  
Anne E. Jones ◽  
Grigory Nikulin ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Climate Projections ◽  
Model Ensemble ◽  
East African Community ◽  
Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

scholarly journals Evaluating quantile-based bias adjustment methods for climate change scenarios

2021 ◽  
Author(s):  
Fabian Lehner ◽  
Imran Nadeem ◽  
Herbert Formayer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Climate Change Signal ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Statistical Bias ◽  
Bias Adjustment ◽  
Direct Model

Abstract. Daily meteorological data such as temperature or precipitation from climate models is needed for many climate impact studies, e.g. in hydrology or agriculture but direct model output can contain large systematic errors. Thus, statistical bias adjustment is applied to correct climate model outputs. Here we review existing statistical bias adjustment methods and their shortcomings, and present a method which we call EQA (Empirical Quantile Adjustment), a development of the methods EDCDFm and PresRAT. We then test it in comparison to two existing methods using real and artificially created daily temperature and precipitation data for Austria. We compare the performance of the three methods in terms of the following demands: (1): The model data should match the climatological means of the observational data in the historical period. (2): The long-term climatological trends of means (climate change signal), either defined as difference or as ratio, should not be altered during bias adjustment, and (3): Even models with too few wet days (precipitation above 0.1 mm) should be corrected accurately, so that the wet day frequency is conserved. EQA fulfills (1) almost exactly and (2) at least for temperature. For precipitation, an additional correction included in EQA assures that the climate change signal is conserved, and for (3), we apply another additional algorithm to add precipitation days.

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