Special Issue "Climate and Atmospheric Dynamics and Predictability"

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: closed (30 September 2019).

Special Issue Editors

Assoc. Prof. Ioannis Pytharoulis
E-Mail Website
Guest Editor
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: synoptic and dynamic meteorology; numerical weather prediction; atmospheric model evaluation; operational weather forecasting; land/sea–air interaction; extreme weather events; African Easterly Waves; Mediterranean tropical-like cyclones
Special Issues and Collections in MDPI journals
Assoc. Prof. Petros Katsafados
E-Mail Website
Guest Editor
Department of Geography, Harokopio University of Athens, Kallithea 17676, Greece
Interests: atmosphere and climate dynamics; data assimilation and nowcasting; numerical weather prediction; air-sea-land interaction; seasonal forecasting; air quality forecasting
Special Issues and Collections in MDPI journals

Special Issue Information

The state of the weather and climate is largely defined by the interactions between the various components of the climate system (atmosphere, hydrosphere, land surface, cryosphere, and biosphere). The understanding of the atmospheric and climate dynamics, that is, how the natural laws determine the weather and climate, and their prediction/ projection, are essential for life, property, and environment. High-impact weather systems, and low-frequency oscillations and their climatic variability, exert a significant influence on humans and their activities. Over the last decades, the advances in weather and climate numerical models, and the increase of computational resources, have resulted in a blooming of weather forecasting and climate research, allowing for more effective planning and preparedness against adverse weather and climate change.

The aim of this Special Issue is to comprise review and original observational, theoretical, and modelling studies on the dynamics of the atmosphere and the climate system, as well as on their predictability at different spatiotemporal scales.

Topics of interest include, but are not limited to, the following:

  • Dynamics of intense/ high impact weather phenomena and low frequency oscillations
  • Climate dynamics
  • Land/sea–air interaction
  • Numerical weather prediction models and data assimilation
  • Climate models
  • Weather forecasting and climate projection techniques (e.g. ensembles, statistical post-processing, etc.)
  • Weather and climate model evaluation.
Dr. Ioannis Pytharoulis
Prof. Dr. Petros Katsafados
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Climate is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate dynamics
  • atmospheric dynamics
  • climate models
  • numerical weather prediction models
  • climate projections
  • weather forecasting
  • nowcasting
  • model evaluation

Published Papers (6 papers)

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Research

Open AccessArticle
Development of a Front Identification Scheme for Compiling a Cold Front Climatology of the Mediterranean
Climate 2019, 7(11), 130; https://doi.org/10.3390/cli7110130 - 11 Nov 2019
Abstract
The objective of this work is the development of an automated and objective identification scheme of cold fronts in order to produce a comprehensive climatology of Mediterranean cold fronts. The scheme is a modified version of The University of Melbourne Frontal Tracking Scheme [...] Read more.
The objective of this work is the development of an automated and objective identification scheme of cold fronts in order to produce a comprehensive climatology of Mediterranean cold fronts. The scheme is a modified version of The University of Melbourne Frontal Tracking Scheme (FTS), to take into account the particular characteristics of the Mediterranean fronts. We refer to this new scheme as MedFTS. Sensitivity tests were performed with a number of cold fronts in the Mediterranean using different threshold values of wind-related criteria in order to identify the optimum scheme configuration. This configuration was then applied to a 10-year period, and its skill was assessed against synoptic surface charts using statistic metrics. It was found that the scheme performs well with the dynamic criteria employed and can be successfully applied to cold front identification in the Mediterranean. Full article
(This article belongs to the Special Issue Climate and Atmospheric Dynamics and Predictability)
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Open AccessFeature PaperArticle
Modeling the Effects of Anthropogenic Land Cover Changes to the Main Hydrometeorological Factors in a Regional Watershed, Central Greece
Climate 2019, 7(11), 129; https://doi.org/10.3390/cli7110129 - 07 Nov 2019
Abstract
In this study, the physically-based hydrological model MIKE SHE was employed to investigate the effects of anthropogenic land cover changes to the hydrological cycle components of a regional watershed in Central Greece. Three case studies based on the land cover of the years [...] Read more.
In this study, the physically-based hydrological model MIKE SHE was employed to investigate the effects of anthropogenic land cover changes to the hydrological cycle components of a regional watershed in Central Greece. Three case studies based on the land cover of the years 1960, 1990, and 2018 were examined. Copernicus Climate Change Service E-OBS gridded meteorological data for 45 hydrological years were used as forcing for the model. Evaluation against observational data yielded sufficient quality for daily air temperature and precipitation. Simulation results demonstrated that the climatic variabilities primarily in precipitation and secondarily in air temperature affected basin-averaged annual actual evapotranspiration and average annual river discharge. Nevertheless, land cover effects can locally outflank the impact of climatic variability as indicated by the low interannual variabilities of differences in annual actual evapotranspiration among case studies. The transition from forest to pastures or agricultural land reduced annual actual evapotranspiration and increased average annual river discharge while intensifying the vulnerability to hydrometeorological-related hazards such as droughts or floods. Hence, the quantitative assessment of land cover effects presented in this study can contribute to the design and implementation of successful land cover and climate change mitigation and adaptation policies. Full article
(This article belongs to the Special Issue Climate and Atmospheric Dynamics and Predictability)
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Open AccessFeature PaperArticle
A Climatology of Atmospheric Patterns Associated with Red River Valley Blizzards
Climate 2019, 7(5), 66; https://doi.org/10.3390/cli7050066 - 06 May 2019
Abstract
Stretching along the border of North Dakota and Minnesota, The Red River Valley (RRV) of the North has the highest frequency of reported blizzards within the contiguous United States. Despite the numerous impacts these events have, few systematic studies exist that discuss the [...] Read more.
Stretching along the border of North Dakota and Minnesota, The Red River Valley (RRV) of the North has the highest frequency of reported blizzards within the contiguous United States. Despite the numerous impacts these events have, few systematic studies exist that discuss the meteorological properties of blizzards. As a result, forecasting these events and lesser blowing snow events is an ongoing challenge. This study presents a climatology of atmospheric patterns associated with RRV blizzards for the winter seasons of 1979–1980 and 2017–2018. Patterns were identified using subjective and objective techniques using meteorological fields from the North American Regional Re-analysis (NARR). The RRV experiences, on average, 2.6 events per year. Blizzard frequency is bimodal, with peaks occurring in December and March. The events can largely be typed into four meteorological categories dependent on the forcing that drives the blizzard: Alberta Clippers, Arctic Fronts, Colorado Lows, and Hybrids. The objective classification of these blizzards using a competitive neural network known as the Self-Organizing Map (SOM) demonstrates that gross segregation of the events can be achieved with a small (eight-class) map. This implies that objective analysis techniques can be used to identify these events in weather and climate model output that may aid future forecasting and risk assessment projects. Full article
(This article belongs to the Special Issue Climate and Atmospheric Dynamics and Predictability)
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Open AccessArticle
GPS Precipitable Water Vapor Estimations over Costa Rica: A Comparison against Atmospheric Sounding and Moderate Resolution Imaging Spectrometer (MODIS)
Climate 2019, 7(5), 63; https://doi.org/10.3390/cli7050063 - 03 May 2019
Abstract
The quantification of water vapor in tropical regions like Central America is necessary to estimate the influence of climate change on its distribution and the formation of precipitation. This work reports daily estimations of precipitable water vapor (PWV) using Global Positioning System (GPS) [...] Read more.
The quantification of water vapor in tropical regions like Central America is necessary to estimate the influence of climate change on its distribution and the formation of precipitation. This work reports daily estimations of precipitable water vapor (PWV) using Global Positioning System (GPS) delay data over the Pacific region of Costa Rica during 2017. The GPS PWV measurements were compared against atmospheric sounding and Moderate Resolution Imaging Spectrometer (MODIS) data. When GPS PWV was calculated, relatively small biases between the mean atmospheric temperatures (Tm) from atmospheric sounding and the Bevis equation were found. The seasonal PWV fluctuations were controlled by two of the main circulation processes in Central America: the northeast trade winds and the latitudinal migration of the Intertropical Convergence Zone (ITCZ). No significant statistical differences were found for MODIS Terra during the dry season with respect GPS-based calculations (p > 0.05). A multiple linear regression model constructed based on surface meteorological variables can predict the GPS-based measurements with an average relative bias of −0.02 ± 0.19 mm/day (R2 = 0.597). These first results are promising for incorporating GPS-based meteorological applications in Central America where the prevailing climatic conditions offer a unique scenario to study the influence of maritime moisture inputs on the seasonal water vapor distribution. Full article
(This article belongs to the Special Issue Climate and Atmospheric Dynamics and Predictability)
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Open AccessFeature PaperArticle
A Lagrangian Ocean Model for Climate Studies
Climate 2019, 7(3), 41; https://doi.org/10.3390/cli7030041 - 15 Mar 2019
Abstract
Most weather and climate models simulate circulations by numerically approximating a complex system of partial differential equations that describe fluid flow. These models also typically use one of a few standard methods to parameterize the effects of smaller-scale circulations such as convective plumes. [...] Read more.
Most weather and climate models simulate circulations by numerically approximating a complex system of partial differential equations that describe fluid flow. These models also typically use one of a few standard methods to parameterize the effects of smaller-scale circulations such as convective plumes. This paper discusses the continued development of a radically different modeling approach. Rather than solving partial differential equations, the author’s Lagrangian models predict the motions of individual fluid parcels using ordinary differential equations. They also use a unique convective parameterization, in which the vertical positions of fluid parcels are rearranged to remove convective instability. Previously, a global atmospheric model and basin-scale ocean models were developed with this approach. In the present study, components of these models are combined to create a new global Lagrangian ocean model (GLOM), which will soon be coupled to a Lagrangian atmospheric model. The first simulations conducted with the GLOM examine the contribution of interior tracer mixing to ocean circulation, stratification, and water mass distributions, and they highlight several special model capabilities: (1) simulating ocean circulations without numerical diffusion of tracers; (2) modeling deep convective transports at low resolution; and (3) identifying the formation location of ocean water masses and water pathways. Full article
(This article belongs to the Special Issue Climate and Atmospheric Dynamics and Predictability)
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Open AccessArticle
Seasonal Drought Forecasting for Latin America Using the ECMWF S4 Forecast System
Climate 2018, 6(2), 48; https://doi.org/10.3390/cli6020048 - 01 Jun 2018
Abstract
Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there are still not many studies of the feasibility of such a forecasts [...] Read more.
Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there are still not many studies of the feasibility of such a forecasts at continental level in the region. In this study, precipitation predictions from the European Centre for Medium Range Weather (ECMWF) seasonal forecast system S4 are combined with observed precipitation data to generate forecasts of the standardized precipitation index (SPI) for Latin America, and their skill is evaluated over the hindcast period 1981–2010. The value-added utility in using the ensemble S4 forecast to predict the SPI is identified by comparing the skill of its forecasts with a baseline skill based solely on their climatological characteristics. As expected, skill of the S4-generated SPI forecasts depends on the season, location, and the specific aggregation period considered (the 3- and 6-month SPI were evaluated). Added skill from the S4 for lead times equaling the SPI accumulation periods is primarily present in regions with high intra-annual precipitation variability, and is found mostly for the months at the end of the dry seasons for 3-month SPI, and half-yearly periods for 6-month SPI. The ECMWF forecast system behaves better than the climatology for clustered grid points in the North of South America, the Northeast of Argentina, Uruguay, southern Brazil and Mexico. The skillful regions are similar for the SPI3 and -6, but become reduced in extent for the severest SPI categories. Forecasting different magnitudes of meteorological drought intensity on a seasonal time scale still remains a challenge. However, the ECMWF S4 forecasting system does capture the occurrence of drought events for the aforementioned regions and seasons reasonably well. In the near term, the largest advances in the prediction of meteorological drought for Latin America are obtainable from improvements in near-real-time precipitation observations for the region. In the longer term, improvements in precipitation forecast skill from dynamical models, like the fifth generation of the ECMWF seasonal forecasting system, will be essential in this effort. Full article
(This article belongs to the Special Issue Climate and Atmospheric Dynamics and Predictability)
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