Effects of Convective Gravity Wave Drag in the Southern Hemisphere Winter Stratosphere

Abstract The excessively strong polar jet and cold pole in the Southern Hemisphere winter stratosphere are systematic biases in most global climate models and are related to underestimated wave drag in the winter extratropical stratosphere—namely, missing gravity wave drag (GWD). Cumulus convection is strong in the winter extratropics in association with storm-track regions; thus, convective GWD could be one of the missing GWDs in models that do not adopt source-based nonorographic GWD parameterizations. In this study, the authors use the Whole Atmosphere Community Climate Model (WACCM) and show that the zonal-mean wind and temperature biases in the Southern Hemisphere winter stratosphere of the model are significantly alleviated by including convective GWD (GWDC) parameterizations. The reduction in the wind biases is due to enhanced wave drag in the winter extratropical stratosphere, which is caused directly by the additional GWDC and indirectly by the increased existing nonorographic GWD and resolved wave drag in response to the GWDC. The cold temperature biases are alleviated by increased downwelling in the winter polar stratosphere, which stems from an increased poleward motion due to enhanced wave drag in the winter extratropical stratosphere. A comparison between two simulations separately using the ray-based and columnar GWDC parameterizations shows that the polar night jet with a ray-based GWDC parameterization is much more realistic than that with a columnar GWDC parameterization.

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Using PRIMAVERA high-resolution global climate models for European windstorm risk assessment in present and future climates for the (re)insurance industry

10.5194/egusphere-egu2020-7676 ◽

2020 ◽

Author(s):

Julia Lockwood ◽

Erika Palin ◽

Galina Guentchev ◽

Malcolm Roberts

Keyword(s):

High Resolution ◽

Climate Models ◽

Climate Model ◽

Insurance Industry ◽

Global Climate ◽

Storm Track ◽

Global Climate Models ◽

Climate Modelling ◽

Business And Society ◽

High Resolution Models

PRIMAVERA is a European Union Horizon2020 project about creating a new generation of advanced and well-evaluated high-resolution global climate models, for the bene&#64257;t of governments, business and society in general. The project has been engaging with several sectors, including &#64257;nance, transport, and energy, to understand the extent to which any improved process understanding arising from high-resolution global climate modelling can &#8211; in turn &#8211; help with using climate model output to address user needs.In this talk we will outline our work for the &#64257;nance and (re)insurance industries.&#160; Following consultation with members of the industry, we are using PRIMAVERA climate models to generate a European windstorm event set for use in catastrophe modelling and risk analysis.&#160; The event set is generated from five different climate models, each run at a selection of resolutions ranging from 18-140km, covering the period 1950-2050, giving approximately 1700 years of climate model data in total.&#160; High-resolution climate models tend to have reduced biases in storm track position (which is too zonal in low-resolution climate models) and windstorm intensity.&#160; We will compare the properties of the windstorm footprints and associated risk across the different models and resolutions, to assess whether the high-resolution models lead to improved estimation of European windstorm risk.&#160; We will also compare windstorm risk in present and future climates, to see if a consistent picture emerges between models.&#160; Finally we will address the question of whether the event sets from each PRIMAVERA model can be combined to form a multi-model event set ensemble covering thousands of years of windstorm data.

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

10.5194/egusphere-egu2020-3147 ◽

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

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-1) to the day after (day+1) 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 60oW near 40oS. 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.

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Holocene evolution of the Southern Hemisphere westerly winds in transient simulations with global climate models

Climate of the Past Discussions ◽

10.5194/cpd-7-1797-2011 ◽

2011 ◽

Vol 7 (3) ◽

pp. 1797-1824 ◽

Cited By ~ 3

Author(s):

V. Varma ◽

M. Prange ◽

U. Merkel ◽

T. Kleinen ◽

G. Lohmann ◽

...

Keyword(s):

Southern Hemisphere ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Global Climate Models ◽

Orbital Forcing ◽

Westerly Winds ◽

Transient Simulations ◽

Southern Hemisphere Westerly Winds

Abstract. The Southern Hemisphere Westerly Winds (SWW) have been suggested to exert a critical influence on global climate through wind-driven upwelling of deep water in the Southern Ocean and the potentially resulting atmospheric CO2 variations. The investigation of the temporal and spatial evolution of the SWW along with forcings and feedbacks remains a significant challenge in climate research. In this study, the evolution of the SWW under orbital forcing from the mid-Holocene (7 kyr BP) to pre-industrial modern times (250 yr BP) is examined with transient experiments using the comprehensive coupled global climate model CCSM3. In addition, a model inter-comparison is carried out using orbitally forced Holocene transient simulations from four other coupled global climate models. Analyses and comparison of the model results suggest that the annual and seasonal mean SWW were subject to an overall strengthening and poleward shifting trend during the course of the mid-to-late Holocene under the influence of orbital forcing, except for the austral spring season, where the SWW exhibited an opposite trend of shifting towards the equator.

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Holocene evolution of the Southern Hemisphere westerly winds in transient simulations with global climate models

Climate of the Past ◽

10.5194/cp-8-391-2012 ◽

2012 ◽

Vol 8 (2) ◽

pp. 391-402 ◽

Cited By ~ 49

Author(s):

V. Varma ◽

M. Prange ◽

U. Merkel ◽

T. Kleinen ◽

G. Lohmann ◽

...

Keyword(s):

Southern Hemisphere ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Global Climate Models ◽

Orbital Forcing ◽

Westerly Winds ◽

Transient Simulations ◽

Southern Hemisphere Westerly Winds

Abstract. The Southern Hemisphere Westerly Winds (SWW) have been suggested to exert a critical influence on global climate through the wind-driven upwelling of deep water in the Southern Ocean and the potentially resulting atmospheric CO2 variations. The investigation of the temporal and spatial evolution of the SWW along with forcings and feedbacks remains a significant challenge in climate research. In this study, the evolution of the SWW under orbital forcing from the mid-Holocene (7 kyr BP) to pre-industrial modern times (250 yr BP) is examined with transient experiments using the comprehensive coupled global climate model CCSM3. In addition, a model inter-comparison is carried out using orbitally forced Holocene transient simulations from four other coupled global climate models. Analyses and comparison of the model results suggest that the annual and seasonal mean SWW were subject to an overall strengthening and poleward shifting trend during the course of the mid-to-late Holocene under the influence of orbital forcing, except for the austral spring season, where the SWW exhibited an opposite trend of shifting towards the equator.

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The MJO-QBO Relationship in a GCM with Stratospheric Nudging

Journal of Climate ◽

10.1175/jcli-d-20-0636.1 ◽

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.

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

10.5194/gmd-2017-105 ◽

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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Tendency Bias Correction in Coupled and Uncoupled Global Climate Models with a Focus on Impacts over North America

Journal of Climate ◽

10.1175/jcli-d-18-0598.1 ◽

2019 ◽

Vol 32 (2) ◽

pp. 639-661 ◽

Cited By ~ 5

Author(s):

Y. Chang ◽

S. D. Schubert ◽

R. D. Koster ◽

A. M. Molod ◽

H. Wang

Keyword(s):

North America ◽

Bias Correction ◽

Climate Models ◽

Global Climate ◽

Storm Track ◽

Coupled Model ◽

Global Climate Models ◽

Forecast Skill ◽

Boreal Summer ◽

Transient Wave

Abstract We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.

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Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

The Journal of Agricultural Science ◽

10.1017/s0021859616000654 ◽

2016 ◽

Vol 155 (3) ◽

pp. 407-420 ◽

Cited By ~ 7

Author(s):

R. S. SILVA ◽

L. KUMAR ◽

F. SHABANI ◽

M. C. PICANÇO

Keyword(s):

Climate Change ◽

Global Warming ◽

Open Field ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Current Model ◽

Global Climate Models ◽

The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

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Back to the Future: Using Long-Term Observational and Paleo-Proxy Reconstructions to Improve Model Projections of Antarctic Climate

Geosciences ◽

10.3390/geosciences9060255 ◽

2019 ◽

Vol 9 (6) ◽

pp. 255 ◽

Cited By ~ 6

Author(s):

Thomas J. Bracegirdle ◽

Florence Colleoni ◽

Nerilie J. Abram ◽

Nancy A. N. Bertler ◽

Daniel A. Dixon ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Ice Core ◽

Global Climate Models ◽

Climate Projections ◽

Past Performance ◽

Wide Range ◽

Proxy Reconstructions

Quantitative estimates of future Antarctic climate change are derived from numerical global climate models. Evaluation of the reliability of climate model projections involves many lines of evidence on past performance combined with knowledge of the processes that need to be represented. Routine model evaluation is mainly based on the modern observational period, which started with the establishment of a network of Antarctic weather stations in 1957/58. This period is too short to evaluate many fundamental aspects of the Antarctic and Southern Ocean climate system, such as decadal-to-century time-scale climate variability and trends. To help address this gap, we present a new evaluation of potential ways in which long-term observational and paleo-proxy reconstructions may be used, with a particular focus on improving projections. A wide range of data sources and time periods is included, ranging from ship observations of the early 20th century to ice core records spanning hundreds to hundreds of thousands of years to sediment records dating back 34 million years. We conclude that paleo-proxy records and long-term observational datasets are an underused resource in terms of strategies for improving Antarctic climate projections for the 21st century and beyond. We identify priorities and suggest next steps to addressing this.

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Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China

Journal of Climate ◽

10.1175/jcli-d-18-0104.1 ◽

2018 ◽

Vol 32 (1) ◽

pp. 195-212 ◽

Cited By ~ 9

Author(s):

Sicheng He ◽

Jing Yang ◽

Qing Bao ◽

Lei Wang ◽

Bin Wang

Keyword(s):

Extreme Precipitation ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Yangtze River Basin ◽

Global Climate Model ◽

Global Climate Models ◽

Global Ocean ◽

East China ◽

Cmip5 Models

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.

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