Special Issue "Development of Precise Indexes for Assessing the Potential Impacts of Climate Change"

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

Deadline for manuscript submissions: closed (15 March 2020).

Special Issue Editor

Dr. Vinay Kumar
E-Mail Website
Guest Editor
Department of Physical and Environmental Studies, Texas A & M University, Kingsville, TX 78363, USA
Interests: stream flow; monsoon; extreme rainfall event
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Special Issue Information

Dear Colleagues,

Indexes are a well-known tool and have proven fundamental in the discovery and understanding of global teleconnection patterns (e.g., El-Nino, Atlantic Oscillations, Indian Ocean Dipole, Arctic Oscillations). Many more Indexes have been used to calculate the length of dry/wet spell, heat degrees, comfort, and mood of a person. A number of Indexes have been used in the literature to define the monsoon, soil moisture, teleconnections, and other climate–weather issues. Most of the Indexes are based on air temperature, precipitation, air pressure, and sea surface temperature. However, very few such Indexes are utilized for future datasets. For future projection dataset and special simulations, those may need modifications or may lead to new discoveries. Futuristic datasets will provide new opportunities to define some new Indexes for climate change. High-resolution modeling has brought many new variables to analyze the weather and climate. Those new variables (cloud mixing ratio, buoyancy, etc.) can be utilized to define new Indexes. The new fields, e.g., thunderstorm, cloud physics, hydrology, aerosol science, ice melt, and biosphere, have a great impact on climate change. Appropriate Indexes can be put together to access and analyze the climate change and global warning issue. New insights based on new Indexes, themselves in turn based on new advances and variables, can provide new dimensions to the climate change science. Multidisciplinary disciplines may join to access climate change using Indexes from their filed.

Dr. Vinay Kumar
Guest Editor

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Keywords

  • Climate change
  • Indexes
  • Teleconnection pattern
  • High resolution

Published Papers (9 papers)

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Editorial

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Editorial
Development of Precise Indices for Assessing the Potential Impacts of Climate Change
Atmosphere 2020, 11(11), 1231; https://doi.org/10.3390/atmos11111231 - 15 Nov 2020
Viewed by 478
Abstract
The Special Issue on climate indices and climate change deals with various kinds of indices exits to assess weather and climate over a region. These indices might be based on local, regional, remote variables, which may affect and define the weather and climate [...] Read more.
The Special Issue on climate indices and climate change deals with various kinds of indices exits to assess weather and climate over a region. These indices might be based on local, regional, remote variables, which may affect and define the weather and climate of a region. Climate indices are the time series used to monitor the state of the climate and its relationship with other possible causes. With indices being myriad, it is challenging to choose which one is appropriate for a region of interest. However, the relationship between the indices and the climate of a region varies. El-Nino Southern Oscillation (Southern Oscillation Index, SOI/ENSO) is one of the most robust climate signals that stimulate rainfall, temperature, and hurricanes via teleconnections. SOI has a correlation of 0.5 over the Indonesian archipelago. Here, some of the well-known indices Holiday Climate Index (HCI), Tourism Climate Index (TCI), and Simple Diversity Index (SDI) are being reconnoitered to understand the holiday-tourism, end-of-the-day (EOD) judgment. The intrusion of dry air in the middle troposphere can create unstable weather, leading to heavy precipitation. The Special Issue seeks to encourage researchers to discover new indices in multidisciplinary department of atmospheric and physical sciences. Full article
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Research

Jump to: Editorial

Article
End of the Day (EOD) Judgment for Daily Rain-Gauge Data
Atmosphere 2020, 11(8), 772; https://doi.org/10.3390/atmos11080772 - 22 Jul 2020
Cited by 3 | Viewed by 994
Abstract
Several versions of Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Extreme Events (APHRODITE-2) have been released for analyzing rain-gauge-based daily precipitation. APHRODITE-2 constitutes an improvement compared with the previous versions for evaluating extreme precipitation. One advantage of APHRODITE-2 products (versions 1801R1 and [...] Read more.
Several versions of Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Extreme Events (APHRODITE-2) have been released for analyzing rain-gauge-based daily precipitation. APHRODITE-2 constitutes an improvement compared with the previous versions for evaluating extreme precipitation. One advantage of APHRODITE-2 products (versions 1801R1 and 1901) over APHRODITE-1 products is the ability to ensure uniformity in the daily accumulation period (end of the day, EOD) used in a specific domain. To create these EOD segregated or EOD adjusted products, we applied an EOD judgment scheme using multi-satellite merged precipitation products CMORPH V1.0 and ERA-Interim reanalysis. The novelty of the current methodology was tested against rain-gauge datasets with known EOD information. Despite the difference in horizontal resolution, ERA-Interim shows similar EOD detection performance to CMORPH. However, CMORPH showed better performance over India than ERA-Interim. The current method has potential to judge EOD of rain-gauge station data with an unknown observation time. Having prior EOD information as metadata is very important for gridded datasets as well as station data. Here, we also present deterministic/estimated EOD that we used for V1801R1 over Monsoon Asia. Full article
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Article
Interaction of a Low-Pressure System, an Offshore Trough, and Mid-Tropospheric Dry Air Intrusion: The Kerala Flood of August 2018
Atmosphere 2020, 11(7), 740; https://doi.org/10.3390/atmos11070740 - 13 Jul 2020
Cited by 4 | Viewed by 778
Abstract
The present study examines the Kerala Flood Event (KFE, 15–16 August 2018, in India) that occurred along the west coast of India and resulted in ~400 mm of rainfall in one day. The KFE was unique in comparison to previous floods in India, [...] Read more.
The present study examines the Kerala Flood Event (KFE, 15–16 August 2018, in India) that occurred along the west coast of India and resulted in ~400 mm of rainfall in one day. The KFE was unique in comparison to previous floods in India, not only due to the rainfall duration and amount, but also due to the fact that the dams failed to mitigate the flood, which made it the worst in history. The main goal of this study is to analyze and elucidate the KFE based on meteorological and hydrological parameters. A propagating low-pressure system (LPS) from the Bay of Bengal (BoB) caused the streak of plenty of rainfall over Kerala, the west coast, central India, and the BoB. Additionally, the upper-tropospheric anti-cyclonic system over the Middle East region inhibited a northward advancement of LPS. On the western coast of India, a non-propagating (with diurnal fluctuations) offshore trough was observed over the west coast (from Kerala to Gujarat state). Therefore, a synergic interaction between LPS, an intrusion of dry air in the middle-troposphere, and the offshore trough was the main reason for KFE. However, after around ten days, rainfall saturated the dam capacities; thus, the released water, along with the amount of precipitation on the day of the event, was one of the other possible reasons which worsened the flood over Kerala. Full article
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Article
Evaluation of Historical CMIP5 GCM Simulation Results Based on Detected Atmospheric Teleconnections
Atmosphere 2020, 11(7), 723; https://doi.org/10.3390/atmos11070723 - 07 Jul 2020
Cited by 1 | Viewed by 723
Abstract
Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a [...] Read more.
Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a statistical method is introduced to evaluate historical GCM outputs of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with respect to teleconnection patterns. The introduced method is based on the calculation of correlations between gridded time series of the 500 hPa geopotential height fields in the Northern Hemisphere. GCMs are quantified by a simple diversity index. Additionally, potential action centers of the teleconnection patterns are identified on which the local polynomial regression model is fitted. Diversity fields and regression curves obtained from the GCMs are compared against the NCEP/NCAR Reanalysis 1 and the ERA-20C reanalysis datasets. The introduced method is objective, reproducible, and reduces the number of arbitrary decisions during the analysis. We conclude that major teleconnection patterns are positioned in the GCMs and in the reanalysis datasets similarly, however, spatial differences in their intensities can be severe in some cases that could hamper the applicability of the GCM results for some regions. Based on the evaluation method, best-performing GCMs can be clearly distinguished. Evaluation of the GCMs based on the introduced method might help the modeling community to choose GCMs that are the most applicable for impact studies and for regional downscaling exercises. Full article
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Article
Evaluation for Characteristics of Tropical Cyclone Induced Heavy Rainfall over the Sub-basins in The Central Hokkaido, Northern Japan by 5-km Large Ensemble Experiments
Atmosphere 2020, 11(5), 435; https://doi.org/10.3390/atmos11050435 - 25 Apr 2020
Cited by 6 | Viewed by 1170
Abstract
Previous studies have shown that the acceleration of global warming will increase the intensity of rainfall induced by tropical cyclones (TCs) (hereinafter referred to as “TC-induced rainfall”). TC-induced rainfall is affected by TC position and topography (slope shape and direction). Thus, TC-induced rainfall [...] Read more.
Previous studies have shown that the acceleration of global warming will increase the intensity of rainfall induced by tropical cyclones (TCs) (hereinafter referred to as “TC-induced rainfall”). TC-induced rainfall is affected by TC position and topography (slope shape and direction). Thus, TC-induced rainfall is expected to vary by sub-basin due to varying topographies. However, these relationships have not been explained, as historical TCs, which occurred several decades earlier, do not exhaustively encompass all TC positions that could potentially affect each basin. We used large ensemble regional climate model experiments with 5 km grid spacing, which enabled us to prepare a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins. We quantified the characteristics of TC-induced rainfall (rainfall volume, relationship between TC position and rainfall intensity, and contribution of TC intensity on rainfall) over four sub-basins in the Tokachi River basin, central Hokkaido, northern Japan. The results reveal differences in TC-induced rainfall characteristics between the sub-basins. In addition, the large ensemble data under a future climate scenario were used to evaluate future changes in the characteristics of TC-induced rainfall for each sub-basin. Full article
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Article
An Inter-Comparison of the Holiday Climate Index (HCI:Beach) and the Tourism Climate Index (TCI) to Explain Canadian Tourism Arrivals to the Caribbean
Atmosphere 2020, 11(4), 412; https://doi.org/10.3390/atmos11040412 - 20 Apr 2020
Cited by 13 | Viewed by 1320
Abstract
Through an empirical investigation of the historical relationship between the destination climate and tourist arrivals in the Caribbean, this study presents the first revealed preference evaluation of a climate index informed by tourists’ stated climatic preferences for coastal-beach tourism (i.e., a sun-sand-surf or [...] Read more.
Through an empirical investigation of the historical relationship between the destination climate and tourist arrivals in the Caribbean, this study presents the first revealed preference evaluation of a climate index informed by tourists’ stated climatic preferences for coastal-beach tourism (i.e., a sun-sand-surf or 3S travel market). The goal of this multi-organization collaboration was to examine the potential application of a newly designed climate index—the Holiday Climate Index (HCI):Beach—for three Caribbean destinations (Antigua and Barbuda, Barbados, Saint Lucia). This paper provides an overview of the evolution of climate indices, including the development of the (HCI):Beach. To test the validity of climate indices for a beach travel market, daily climate ratings based on outputs from the Tourism Climate Index and the HCI were correlated with monthly arrivals data from Canada (a key source market) at an island destination scale. The results underscore the strength of the new index, with each destination scoring consistently higher using the HCI:Beach, including a stronger relationship (R2) between index scores and tourist arrivals. These findings demonstrate the value of combining stated and revealed preference methodologies to predict tourism demand and highlight opportunities for future research. Full article
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Article
Evaluating the Sensitivity of Growing Degree Days as an Agro-Climatic Indicator of the Climate Change Impact: A Case Study of the Russian Far East
Atmosphere 2020, 11(4), 404; https://doi.org/10.3390/atmos11040404 - 17 Apr 2020
Cited by 2 | Viewed by 624
Abstract
Climate is a key factor in agriculture, but we are unable to adequately predict future climates. Although some studies have addressed the short and long-run impacts of climate change on agriculture, few of them specifically focused on the analysis of its thermal component. [...] Read more.
Climate is a key factor in agriculture, but we are unable to adequately predict future climates. Although some studies have addressed the short and long-run impacts of climate change on agriculture, few of them specifically focused on the analysis of its thermal component. Climatic regions with an extreme thermal range are a special case, as seasonal contrasts complicate the picture. Based on the above, the purpose of the paper is twofold. First, we review methods and indices used for the estimation of changes in the thermal component of the climate and demonstrate the usefulness of a sensitivity assessment methodology that gives some indication of the likely spatial extent of areas of high or low sensitivity to climate change and the size of the potential impact of that change, which is specifically beneficial in regions with high temperature extremes. Secondly, we constructed a composite indicator, called the Growing Degree Day Sensitivity Index (GDDSI) and defined as the percentage change in Growing Degree Day (GDD) for warming scenarios +1, +2 and +3 °C. GDDs were calculated for threshold base air temperatures of 0, 5, 10 and 15 °C, and a high-temperature limit of 30 °C. A GDD sensitivity analysis was applied to the thermally extreme climate of the Russian Far East. We analyzed the data of 50 weather stations across the study region over the period 1966–2017. The results show a strong GDDSI north-to-south gradient. In most cases, the sensitivity does not increase significantly as the warming rate increases. The higher the base threshold, the higher the sensitivity: GDDs with a threshold at 15 °C had the highest sensitivity in the far north of the study area where conditions are currently marginal for crop growth. The sensitivity analysis circumnavigates the difficulty of uncertainty in knowing what future climate to expect and informs planning decisions. The mapped results are useful for identifying areas of high sensitivity to climate change as well as the magnitude of the potential impact of that change. Full article
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Article
Influence of the Long-Term Temperature Trend on the Number of New Records for Annual Maximum Daily Precipitation in Japan
Atmosphere 2020, 11(4), 371; https://doi.org/10.3390/atmos11040371 - 10 Apr 2020
Cited by 3 | Viewed by 824
Abstract
Record-breaking precipitation events have been frequent in Japan in recent years. To investigate the statistical characteristics of the frequency of record-breaking events, observations can be compared with the values derived from sampling theory with a stationary state. This study counted the number of [...] Read more.
Record-breaking precipitation events have been frequent in Japan in recent years. To investigate the statistical characteristics of the frequency of record-breaking events, observations can be compared with the values derived from sampling theory with a stationary state. This study counted the number of record-breaking daily and 3-day total precipitation events at 58 rain-gauge stations in Japan between 1901 and 2018. The average number of record-breaking events over the 118-year period was 5.9 for daily total precipitation, which is larger than the theoretical value of 5.4 derived using the assumption that the climate system over the same period was stationary. Sampling theory was used to incorporate the influence of the long-term temperature trend from the Clausius–Clapeyron relation associated with the saturation vapor pressure. In theory, the long-term temperature trend gives a similar number of observed record-breaking events when the long-term temperature trend is approximately 0.5 Kelvin/100 years. Full article
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Article
Evaluating the Adaptation of Chinese Torreya Plantations to Climate Change
Atmosphere 2020, 11(2), 176; https://doi.org/10.3390/atmos11020176 - 08 Feb 2020
Cited by 4 | Viewed by 773
Abstract
Studying the capacity of some plant species to adapt to climate change is essential for ecological research and agricultural policy development. Chinese Torreya (Torreya grandis ‘Merrillii’) has been an important crop tree in subtropical China for over a thousand years. It is [...] Read more.
Studying the capacity of some plant species to adapt to climate change is essential for ecological research and agricultural policy development. Chinese Torreya (Torreya grandis ‘Merrillii’) has been an important crop tree in subtropical China for over a thousand years. It is necessary to characterize its adaptation to climate change. In this study, the average monthly temperature and precipitation from 1901 to 2017 in the six regions with Chinese Torreya plantations at different provinces were analyzed. The results indicated that the average annual air temperature across these regions had increased by about 2.0 °C, but no general trend in the annual precipitation and incidence of drought was found. The annual air temperature that Chinese Torreya plantations had experienced was 12.96–18.23 °C; the highest and the lowest average monthly air temperatures were 30.1 °C and −0.8 °C, respectively. The lowest and the highest annual precipitation were 874.56 mm and 2501.88 mm, respectively. Chinese Torreya trees endured a severe drought period in the 1920s. The monthly air temperature at Zhuji, which is the central production region, showed a significant correlation with the air temperature in the other five regions. The monthly precipitation in Hunan and Guizhou had no significant correlation with that of Zhuji. Chinese Torreya plantations have been grown in the regions with a similar climate distance index of air temperatures but different precipitation. This tree has a high capacity to adapt to climate change based on the climate dynamics across its range. This approach may provide a way to evaluate climate adaptation in other tree species. These results may provide helpful information for the development of Chinese Torreya plantations. Full article
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