Special Issue "Climate Change and Climate Variability, and Their Impact on Extreme Events"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: 30 June 2022.

Special Issue Editors

Dr. Sridhara Nayak
E-Mail Website
Guest Editor
Disaster Prevention Research Insitute, Kyoto University, Uji, Kyoto 611001, Japan
Interests: climate modeling; extreme events; dynamical downscaling; land use and land cover change; numerical weather prediction; statistical method applications; remote sensing applications and GIS
Special Issues and Collections in MDPI journals
Dr. Netrananda Sahu
E-Mail Website
Guest Editor
Department of Geography, Delhi School of Economics, University of Delhi, Delhi 110007, India
Interests: Indo-Pacific variability; climate variability and societal impacts; climate change and river hydrology; agriculture; hydroclimate; disaster risk reduction; trend analysis
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

In the present scenario, climate change and climate variability are of great concern around the world, particularly their impact on extreme weather events, which consequently affect all sectors, including habitat, economy, health, water, and agriculture. Thus, understanding the pattern of climate change and climate variability has been the focus of many researchers, and many efforts are being made to better frame the consequences of their future impacts. This Special Issue of Atmosphere seeks contributions on observational and numerical modeling studies to enhance the understanding of the global or regional climate patterns and variations over time in some measures of climate. This issue also encourages articles that discuss regional or global analysis of extreme weather events and their response to the climate change and climate variability trend. Contributions on model simulations and evaluations to advance the understanding of physics and dynamics associated with climate-change-related weather hazards will also be considered. Submissions in, but not limited to, the following research areas are invited:

Climate change;
Climate variability;
Extreme events;
Climate modeling;
Hydroclimate;
Hydrometeorology.

Dr. Sridhara Nayak
Dr. Netrananda Sahu
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. Atmosphere 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 1800 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 change
  • climate variability
  • extreme events
  • climate modeling
  • hydroclimate 
  • hydrometeorology

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Future Projections and Uncertainty Assessment of Precipitation Extremes in Iran from the CMIP6 Ensemble
Atmosphere 2021, 12(8), 1052; https://doi.org/10.3390/atmos12081052 - 16 Aug 2021
Viewed by 289
Abstract
Scientists who want to know future climate can use multimodel ensemble (MME) methods that combine projections from individual simulation models. To predict the future changes of extreme rainfall in Iran, we examined the observations and 24 models of the Coupled Model Inter-Comparison Project [...] Read more.
Scientists who want to know future climate can use multimodel ensemble (MME) methods that combine projections from individual simulation models. To predict the future changes of extreme rainfall in Iran, we examined the observations and 24 models of the Coupled Model Inter-Comparison Project Phase 6 (CMIP6) over the Middle East. We applied generalized extreme value (GEV) distribution to series of annual maximum daily precipitation (AMP1) data obtained from both of models and the observations. We also employed multivariate bias-correction under three shared socioeconomic pathway (SSP) scenarios (namely, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We used a model averaging method that takes both performance and independence of model into account, which is called PI-weighting. Return levels for 20 and 50 years, as well as the return periods of the AMP1 relative to the reference years (1971–2014), were estimated for three future periods. These are period 1 (2021–2050), period 2 (2046–2075), and period 3 (2071–2100). From this study, we predict that over Iran the relative increases of 20-year return level of the AMP1 in the spatial median from the past observations to the year 2100 will be approximately 15.6% in the SSP2-4.5, 23.2% in the SSP3-7.0, and 28.7% in the SSP5-8.5 scenarios, respectively. We also realized that a 1-in-20 year (or 1-in-50 year) AMP1 observed in the reference years in Iran will likely become a 1-in-12 (1-in-26) year, a 1-in-10 (1-in-22) year, and a 1-in-9 (1-in-20) year event by 2100 under the SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. We project that heavy rainfall will be more prominent in the western and southwestern parts of Iran. Full article
Show Figures

Figure 1

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Impact of soil moisture initialization in the simulation of In-dian Summer Monsoon using RegCM4
Authors: S Maity1, S Nayak2,*, K S Singh3, H Nayak4, S Dutta5
Affiliation:

1. Research Institute for Global Change; Japan Agency for Marine-Earth Science and Technology (JAMSTEC); Yokohama, 236-0001; Japan.

2. Disaster Prevention Research Institute; Kyoto University, Gokasho; Uji, Kyoto - 6110011; Japan.

3. Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology; Vellore - 632014; India.

4. School of Earth Ocean and Climate Sciences; Indian Institute of Technology Bhubaneswar; Odisha - 752050; India.

5. Farmneed AgriBusiness Private Limited; Salt Lake 700091; India.

Abstract: Soil moisture is one of the key components of the land surface processes and a potential source of atmospheric predictability that has received less attention in the regional scale studies. In this study, an attempt was made to investigate the impact of soil moisture on Indian Summer Mon-soon simulation using a regional model. We conducted seasonal simulations using Regional Climate Model (RegCM4) for two different years viz., 2002 (deficit) and 2011 (normal). The model was forced to initialize with the high resolution satellite derived soil moisture data obtained from the Climate Change Initiative (CCI) of European Space Agency (ESA) by replacing the default soil moisture. Simulated results were validated against India Meteorology Department (IMD) data. Careful examination revealed that there was significant advancement in the RegCM4 simulation while initialized with the soil moisture from ESA-CCI despite of having regional biases. Whilst in general, the model exhibited slightly higher soil moisture than observation, RegCM4 with ESA setup showed lower soil moisture than that of with default one. Model skill was relatively better in capturing surface temperature distribution when initialized with high resolution soil moisture. Rainfall biases over India as well as homogeneous regions were significantly improved with the use of ESA-CCI soil moisture. Several statistical measures such as temporal correlation, standard deviation and equitable threat score (ETS) etc. were also employed for the assessment. ETS values were found better in 2011 and higher in the simulation with ESA setup. However, RegCM4 still couldn’t able to enhance its skill in simulating temporal variation of rainfall adequately. Although initialization with the soil moisture from the satellite performed relatively better in normal monsoon year (2011) but had limitation in simulating different epochs of monsoon in extreme year (2002). Thus, the study concluded that the simulation of Indian Summer Monsoon was improved by using RegCM4 initialized with high resolution satellite soil moisture although having limitation in predicting temporal variability. Overall study suggests soil moisture initialization has critical impact on accurate prediction of atmospheric circulation process and convective rainfall activity.

Back to TopTop