SOLA

Scope & Guideline

Advancing atmospheric science through open collaboration.

Introduction

Delve into the academic richness of SOLA with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN1349-6476
PublisherMETEOROLOGICAL SOC JAPAN
Support Open AccessYes
CountryJapan
TypeJournal
Convergefrom 2005 to 2024
AbbreviationSOLA / SOLA
Frequency1 issue/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressC/O JAPAN METEOROLOGICAL AGENCY 1-3-4 OTE-MACHI, CHIYODA-KU, TOKYO 100-0004, JAPAN

Aims and Scopes

The journal SOLA is dedicated to the dissemination of research that addresses various aspects of atmospheric science, focusing particularly on the impacts of climate change and extreme weather events. It aims to provide insights into the mechanisms driving weather phenomena and climate variability, with an emphasis on both observational studies and numerical modeling.
  1. Climate Change and Its Impacts:
    Research exploring the effects of climate change on weather patterns, including assessments of extreme weather events such as heavy rainfall, snowfall, and temperature anomalies.
  2. Numerical Weather Prediction and Modeling:
    Development and evaluation of numerical models for predicting weather events, including the use of high-resolution simulations and ensemble forecasting techniques.
  3. Extreme Weather Events:
    Studies focused on understanding the causes, characteristics, and impacts of extreme weather events, particularly in the context of Japan and surrounding regions.
  4. Atmospheric Observations and Remote Sensing:
    Utilization of various observational techniques and satellite data to analyze atmospheric phenomena and validate model predictions.
  5. Hydrometeorology and Precipitation Studies:
    Investigations into precipitation patterns, including the microphysical characteristics of precipitation and the hydrological responses to weather systems.
Recent publications in SOLA indicate a notable shift toward specific themes that reflect current challenges and advancements in atmospheric sciences. These emerging trends highlight the journal's responsiveness to evolving scientific inquiries and societal needs.
  1. Deep Learning and AI Applications:
    The integration of artificial intelligence and machine learning techniques in meteorological research is gaining traction, particularly in areas like nowcasting and precipitation prediction.
  2. Impact of Climate Change on Extreme Weather:
    There is a growing focus on the direct impacts of climate change on the frequency and intensity of extreme weather events, reinforcing the need for adaptive strategies in vulnerable regions.
  3. Regional Climate Modeling:
    Increased attention to regional climate modeling, particularly high-resolution simulations that provide better insights into localized climate impacts and phenomena.
  4. Cloud Microphysics and Precipitation Processes:
    Research into the microphysical processes of clouds and their influence on precipitation patterns is becoming more prominent, reflecting advancements in observational techniques and modeling.
  5. Interdisciplinary Approaches:
    Emerging studies that combine atmospheric science with other fields such as urban planning, agriculture, and public health are on the rise, highlighting the interdisciplinary nature of climate-related research.

Declining or Waning

While SOLA has consistently focused on numerous important themes within atmospheric sciences, certain areas appear to be experiencing a decline in research activity. This waning focus may indicate a shift in the research community's priorities or advancements in methodologies that render previous approaches less relevant.
  1. Historical Climate Data Analysis:
    Research centered on historical climate data and long-term trends has decreased, possibly due to a shift towards more immediate climate impacts and real-time data applications.
  2. Static Climate Models:
    The use of traditional, non-ensemble-based climate models is becoming less common as researchers increasingly adopt advanced ensemble methods and machine learning techniques.
  3. General Climate Trends without Regional Focus:
    Studies that provide general assessments of climate trends without a specific regional focus are declining, as there is a growing emphasis on localized and actionable climate science.

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