scholarly journals Changes in Hurricanes from a 13-Yr Convection-Permitting Pseudo–Global Warming Simulation

2018 ◽  
Vol 31 (9) ◽  
pp. 3643-3657 ◽  
Author(s):  
Ethan D. Gutmann ◽  
Roy M. Rasmussen ◽  
Changhai Liu ◽  
Kyoko Ikeda ◽  
Cindy L. Bruyere ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Climate Modeling ◽  
Global Climate ◽  
Regional Climate ◽  
Good Reason ◽  
Wrf Model ◽  
Coupled Model ◽  
Regional Climate Modeling ◽  
Climate Signal ◽  
Wind Speeds

Abstract Tropical cyclones have enormous costs to society through both loss of life and damage to infrastructure. There is good reason to believe that such storms will change in the future as a result of changes in the global climate system and that such changes may have important socioeconomic implications. Here a high-resolution regional climate modeling experiment is presented using the Weather Research and Forecasting (WRF) Model to investigate possible changes in tropical cyclones. These simulations were performed for the period 2001–13 using the ERA-Interim product for the boundary conditions, thus enabling a direct comparison between modeled and observed cyclone characteristics. The WRF simulation reproduced 30 of the 32 named storms that entered the model domain during this period. The model simulates the tropical cyclone tracks, storm radii, and translation speeds well, but the maximum wind speeds simulated were less than observed and the minimum central pressures were too large. This experiment is then repeated after imposing a future climate signal by adding changes in temperature, humidity, pressure, and wind speeds derived from phase 5 of the Coupled Model Intercomparison Project (CMIP5). In the current climate, 22 tracks were well simulated with little changes in future track locations. These simulations produced tropical cyclones with faster maximum winds, slower storm translation speeds, lower central pressures, and higher precipitation rates. Importantly, while these signals were statistically significant averaged across all 22 storms studied, changes varied substantially between individual storms. This illustrates the importance of using a large ensemble of storms to understand mean changes.

Impact of Soil Moisture Initialization on Temperature Extreme Detection in the context of Regional Climate Modeling

2020 ◽  
Author(s):  
Matilde García-Valdecasas Ojeda ◽  
Juan José Rosa-Cánovas ◽  
Emilio Romero-Jiménez ◽  
Patricio Yeste ◽  
Sonia R. Gámiz-Fortis ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Initial Conditions ◽  
Climate Modeling ◽  
Regional Climate ◽  
Wrf Model ◽  
Regional Climate Modeling ◽  
Weather Research And Forecasting ◽  
Temperature Extremes ◽  
Temperature Extreme ◽  
The Impact

<p>Land surface-related processes play an essential role in the climate conditions at a regional scale. In this study, the impact of soil moisture (SM) initialization on regional climate modeling has been explored by using a dynamical downscaling experiment. To this end, the Weather Research and Forecasting (WRF) model was used to generate a set of high-resolution climate simulations driven by the ERA-Interim reanalysis for a period from 1989 to 2009. As the spatial configuration, two one-way nested domains were used, with the finer domain being centered over the Iberian Peninsula (IP) at a spatial resolution of about 10 km, and nested over a coarser domain that covers the Euro-CORDEX region at 50 km of spatial resolution.</p><p>The sensitivity experiment consisted of two control runs (CTRL) performed using as SM initial conditions those provided by ERA-Interim, and initialized for two different dates times (January and June). Additionally, another set of runs was completed driven by the same climate data but using as initial conditions prescribed SM under wet and dry scenarios.</p><p>The study is based on assessing the WRF performance by comparing the CTRL simulations with those performed with the different prescribed SM, and also, comparing them with the observations from the Spanish Temperature At Daily scale (STEAD) dataset. In this sense, we used two temperature extreme indices within the framework of decadal predictions: the warm spell index (WSDI) and the daily temperature range (DTR).</p><p>These results provide valuable information about the impact of the SM initial conditions on the ability of the WRF model to detect temperature extremes, and how long these affect the regional climate in this region. Additionally, these results may provide a source of knowledge about the mechanisms involved in the occurrence of extreme events such as heatwaves, which are expected to increase in frequency, duration, and magnitude under the context of climate change.</p><p><strong>Keywords</strong>: soil moisture initial conditions, temperature extremes, regional climate, Weather Research and Forecasting model</p><p>Acknowledgments: This work has been financed by the project CGL2017-89836-R (MINECO-Spain, FEDER). The WRF simulations were performed in the Picasso Supercomputer at the University of Málaga, a member of the Spanish Supercomputing Network.</p>

Coordinated Global and Regional Climate Modeling*

2015 ◽  
Vol 29 (1) ◽  
pp. 17-35 ◽  
Author(s):  
J. F. Scinocca ◽  
V. V. Kharin ◽  
Y. Jiao ◽  
M. W. Qian ◽  
M. Lazare ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Climate Modeling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Value Added ◽  
Regional Climate Modeling ◽  
Climate Projections ◽  
Climate Modelling

Abstract A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.

scholarly journals West African monsoon precipitation impacted by the South Eastern Atlantic biomass burning aerosol outflow

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
F. Solmon ◽  
N. Elguindi ◽  
M. Mallet ◽  
C. Flamant ◽  
P. Formenti
Keyword(s):  
Biomass Burning ◽  
Climate Modeling ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Scale ◽  
West African Monsoon ◽  
Regional Climate Modeling ◽  
West African ◽  
African Monsoon ◽  
Low Cloud

AbstractThe West African Monsoon (WAM) is a complex system depending on global climate influences and multiple regional environmental factors. Central and Southern African biomass-burning (SABB) aerosols have been shown to perturb WAM during episodic northward inter-hemispheric transport events, but a possible dynamical connection between the core of the SABB aerosol outflow and the WAM system remains unexplored. Through regional climate modeling experiments, we show that SABB aerosols can indeed impact WAM dynamics via two competitive regional scale and inter-hemispheric dynamical feedbacks originating from (i) enhanced diabatic heating occurring in the Southeastern Atlantic low-cloud deck region, and (ii) aerosol and cloud-induced sea surface temperature cooling. These mechanisms, related to aerosol direct, semi-direct, and indirect effects, are shown to have different seasonal timings, resulting in a reduction of June to September WAM precipitation, while possibly enhancing late-season rainfall in WAM coastal areas.

scholarly journals Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

2012 ◽  
Vol 25 (8) ◽  
pp. 2805-2823 ◽  
Author(s):  
Jared H. Bowden ◽  
Tanya L. Otte ◽  
Christopher G. Nolte ◽  
Martin J. Otte
Keyword(s):  
Climate Modeling ◽  
Regional Climate ◽  
Wrf Model ◽  
Regional Climate Modeling ◽  
Atmospheric Model ◽  
Meridional Wind ◽  
Department Of Energy ◽  
Monthly Precipitation ◽  
Spectral Nudging ◽  
Regional Reanalysis

Abstract This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis (R-2) data are downscaled to 36 km × 36 km by nudging only at the lateral boundaries, using gridpoint (i.e., analysis) nudging and using spectral nudging. Seven annual simulations are conducted and evaluated for 1988 by comparing 2-m temperature, precipitation, 500-hPa geopotential height, and 850-hPa meridional wind to the 32-km North American Regional Reanalysis (NARR). Using interior nudging reduces the mean biases for those fields throughout the CONUS compared to the simulation without interior nudging. The predictions of 2-m temperature and fields aloft behave similarly when either analysis or spectral nudging is used. For precipitation, however, analysis nudging generates monthly precipitation totals, and intensity and frequency of precipitation that are closer to observed fields than spectral nudging. The spectrum of 250-hPa zonal winds simulated by the WRF model is also compared to that of the R-2 and NARR. The spatial variability in the WRF model is reduced by using either form of interior nudging, and analysis nudging suppresses that variability more strongly than spectral nudging. Reducing the nudging strengths on the inner domain increases the variability but generates larger biases. The results support the use of interior nudging on both domains of a two-way nest to reduce error when the inner nest is not otherwise dominated by the lateral boundary forcing. Nevertheless, additional research is required to optimize the balance between accuracy and variability in choosing a nudging strategy.

Using Social Media to Improve Peer Dialogue in an Online Course About Regional Climate Modeling

2018 ◽  
Vol 8 (4) ◽  
pp. 1-21 ◽  
Author(s):  
Morgan B. Yarker ◽  
Michel D.S. Mesquita
Keyword(s):  
Social Media ◽  
Information Exchange ◽  
Online Courses ◽  
Climate Modeling ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Effective Learning ◽  
Classroom Dialogue ◽  
E Learning

Recent technology advancements provide worldwide information exchange that has been invaluable for the scientific community, particularly for issues surrounding global climate change. Many online learning spaces have developed which are often repositories of information rather than a space of knowledge construction. Classroom dialogue is shown to be an important component for effective learning, therefore it should be developed online as well. This article explores how social media can support dialogue in e-learning. Interactions were studied in two online courses about regional climate modeling. The first used traditional forums and the other promoted a Facebook group for online interactions. Qualitative results indicate that the Facebook group showed improvement because elements of dialogue began to emerge, including open-ended questions and episodes of peer discussion. Quantitative findings suggest the Facebook interactions were perceived as more informal and participants posted, responded, and interacted with their peers more significantly than traditional forums.

Modeling the Influence of Upstream Land-atmosphere Coupling on the 2017 Persistent Drought over Northeast China

2021 ◽  
pp. 1-62
Author(s):  
Dingwen Zeng ◽  
Xing Yuan
Keyword(s):  
Land Surface ◽  
Northeast China ◽  
Large Scale ◽  
Climate Modeling ◽  
Regional Climate ◽  
Critical Role ◽  
Wrf Model ◽  
Regional Climate Modeling ◽  
Anticyclonic Circulation ◽  
Persistent Drought

AbstractPersistent drought events that cause serious damages to economy and environment are usually intensified by the feedback between land surface and atmosphere. Therefore, reasonably modeling land-atmosphere coupling is critical for skillful prediction of persistent droughts. However, most high-resolution regional climate modeling focused on the amplification effect of land-atmosphere coupling on local anticyclonic circulation anomaly, while less attention was paid to the non-local influence through altering large-scale atmospheric circulation. Here we investigate how the antecedent land-atmosphere coupling over the area south to Lake Baikal (ASLB) influences the drought events occurred over its downstream region (Northeast China; NEC) by using Weather Research and Forecasting (WRF) model and linear baroclinic model (LBM). When the ASLB is artificially forced to be wet in the WRF simulations during March-May, the surface sensible heating is weakened and results in a cooling anomaly in low level atmosphere during May-July. Consequently, the anticyclonic circulation anomalies over ASLB and NEC are weakened, and the severity of NEC drought during May-July cannot be captured due to the upstream wetting in March-May. In the LBM experiments, idealized atmospheric heating anomaly that mimics the diabatic heating associated with surface wetness is imposed over ASLB, and the quasi-steady response pattern of 500-hPa geopotential height to the upstream wetting is highly consistent with that in the WRF simulation. In addition, the lower level heating instead of the upper level cooling makes a major contribution to the high pressure anomaly over NEC. This study implies the critical role of modeling upstream land-atmosphere coupling in capturing downstream persistent droughts.

Regional Climate Modeling and Air-Sea Coupling

2017 ◽  
Author(s):  
Corinna Schrum
Keyword(s):  
Climate Change ◽  
Climate Modeling ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Scale ◽  
Regional Climate Modeling ◽  
Climate Impact ◽  
Regional Models ◽  
Climate Research ◽  
Ocean Models

Regional models were originally developed to serve weather forecasting and regional process studies. Typical simulations encompass time periods in the order of days or weeks. Thereafter regional models were also used more and more as regional climate models for longer integrations and climate change downscaling. Regional climate modeling or regional dynamic downscaling, which are used interchangeably, developed as its own branch in climate research since the end of the 1990s out of the need to bridge the obvious inconsistencies at the interface of global climate research and climate impact research. The primary aim of regional downscaling is to provide consistent regional climate change scenarios with relevant spatial resolution to serve detailed climate impact assessments. Similar to global climate modeling, the early attempts at regional climate modeling were based on uncoupled atmospheric models or stand-alone ocean models, an approach that is still maintained as the most common on the regional scale. However, this approach has some fundamental limitations, since regional air-sea interaction remains unresolved and regional feedbacks are neglected. This is crucial when assessing climate change impacts in the coastal zone or the regional marine environment. To overcome these limitations, regional climate modeling is currently in a transition from uncoupled regional models into coupled atmosphere-ocean models, leading to fully integrated earth system models. Coupled ice-ocean-atmosphere models have been developed during the last decade and are currently robust and well established on the regional scale. Their added value has been demonstrated for regional climate modeling in marine regions, and the importance of regional air-sea interaction became obvious. Coupled atmosphere-ice-ocean models, but also coupled physical-biogeochemical modeling approaches are increasingly used for the marine realm. First attempts to couple these two approaches together with land surface models are underway. Physical coupled atmosphere-ocean modeling is also developing further and first model configurations resolving wave effects at the atmosphere-ocean interface are now available. These new developments now open up for improved regional assessment under broad consideration of local feedbacks and interactions between the regional atmosphere, cryosphere, hydrosphere, and biosphere.

scholarly journals Urban Climates and Climate Change

2020 ◽  
Vol 45 (1) ◽  
pp. 411-444 ◽  
Author(s):  
Valéry Masson ◽  
Aude Lemonsu ◽  
Julia Hidalgo ◽  
James Voogt
Keyword(s):  
Climate Change ◽  
Climate Modeling ◽  
Regional Climate ◽  
Urban Climate ◽  
Regional Climate Modeling ◽  
Climate Impact ◽  
Local Climate ◽  
Urban Climatology ◽  
Recent Developments ◽  
Global Agenda

Cities are particularly vulnerable to extreme weather episodes, which are expected to increase with climate change. Cities also influence their own local climate, for example, through the relative warming known as the urban heat island (UHI) effect. This review discusses urban climate features (even in complex terrain) and processes. We then present state-of-the-art methodologies on the generalization of a common urban neighborhood classification for UHI studies, as well as recent developments in observation systems and crowdsourcing approaches. We discuss new modeling paradigms pertinent to climate impact studies, with a focus on building energetics and urban vegetation. In combination with regional climate modeling, new methods benefit the variety of climate scenarios and models to provide pertinent information at urban scale. Finally, this article presents how recent research in urban climatology contributes to the global agenda on cities and climate change.

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