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Subseasonal to Seasonal Climate Forecasting
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Subseasonal to Seasonal Climate Forecasting

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 15548

Special Issue Editors

Dr. Shakeel Asharaf

E-Mail Website
Guest Editor
1. Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, USA
2. Jet Propulsion La-boratory, California Institute of Technol-ogy, Pasadena, CA, USA
Interests: land–atmosphere–ocean interaction; monsoons; seamless prediction/projection/verification; climate services; satellite / in situ data analysis
Dr. Anupam Kumar

E-Mail Website
Guest Editor
Centre for Climate Research Singapore, Meteorological Service Singapore, National Environment Agency, Singapore, Singapore
Interests: climate impacts; weather forecast; cold surge; extreme weather events; catastrophe risk modeling; food security; renewable energy; urban heat island

Special Issue Information

Dear Colleagues,

In the past few years, significant progress has been made in the usability of weather data at sub-seasonal to seasonal (S2S) timescales for decision-making. With the advancement of resources and technological developments (e.g., new satellites, in situ networks), more realistic and accurate measurements now allow for achieve better prediction systems. This potentially allows the development of standard tools to meet sector-specific (e.g., food, water, agriculture, energy, health, transportation, etc.) requirements. Yet, these prediction systems exhibit uncertainties when incorporating more detailed information at regional to local scales. An optimal approach is therefore needed to address a trade-off between uncertainties and skills of the prediction systems tailored to the user-specific requirements.

This Special Issue aims to utilize the S2S forecast data to determine the potential effects of impact-relevant studies (e.g., pre-defined natural hazards such as droughts, floods, heat stress, etc.) at regional to local scales. This also includes disseminating datasets, methods, and metric visualizations for sector-specific users.

  • Sub-seasonal to seasonal prediction
  • Climate services/decision making
  • Impact studies
  • Uncertainty quantification
  • Ensemble prediction system
  • Bias adjustment
  • Forecast skills

Dr. Shakeel Asharaf
Dr. Anupam Kumar
Guest Editors

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Published Papers (5 papers)

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Research

15 pages, 4399 KiB  
Article
Characteristics of Compound Climate Extremes and Impacts in Singapore, 1985–2020
by Jianjun Yu, Anupam Kumar, Kanhu Charan Pattnayak, Jeff Obbard and Aurel Florian Moise
Climate 2023, 11(3), 58; https://doi.org/10.3390/cli11030058 - 5 Mar 2023
Cited by 1 | Viewed by 2806
Abstract
Compound weather and climate extremes have amplified impacts on natural and socioeconomic systems across the world, including Singapore. To better understand the spatial and temporal characteristics of compound climate extremes, including concurrent rainfall and wind speed, as well as dry and hot conditions, [...] Read more.
Compound weather and climate extremes have amplified impacts on natural and socioeconomic systems across the world, including Singapore. To better understand the spatial and temporal characteristics of compound climate extremes, including concurrent rainfall and wind speed, as well as dry and hot conditions, we analyzed long-term observations from 11 selected meteorological stations over the period 1985–2020. The results revealed that the north and northeastern parts of Singapore were focal points for both types of compound extremes, with a higher frequency of occurrence than the southwest of the island. Concurrent rainfall and wind speed extremes were the most prominent in December and January thanks to the northeast monsoon, while dry and hot extremes were distributed mainly in the inter-monsoon season, with peaks in March and April. A notable upward trend was also detected for mild and moderate levels of both compound climate extremes over time. According to our review of the impacts, Singapore has benefited from investments in enhanced water infrastructure; water resource availability was less affected; and flash floods were not proportionally related to the severity of climate extremes. The forests in the urban landscape of Singapore also exhibit resilience to drought. Full article
(This article belongs to the Special Issue Subseasonal to Seasonal Climate Forecasting)
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12 pages, 2219 KiB  
Article
New Normal in ITCZ and Its Role in Altering Agroclimatic Suitability for Rice Production
by Somnath Jha, Mourani Sinha and Anupam Kumar
Climate 2023, 11(3), 52; https://doi.org/10.3390/cli11030052 - 25 Feb 2023
Viewed by 1980
Abstract
Intertropical Convergence Zone (ITCZ) primarily governs the convective rainfall potential of the summer monsoon in Asia. In the present study, non-parametric trend test with outgoing longwave radiation (OLR) for the summer monsoon period for the last 42 years (1980–2021) have been analyzed for [...] Read more.
Intertropical Convergence Zone (ITCZ) primarily governs the convective rainfall potential of the summer monsoon in Asia. In the present study, non-parametric trend test with outgoing longwave radiation (OLR) for the summer monsoon period for the last 42 years (1980–2021) have been analyzed for ITCZ zone, representative zones of Hadley circulation and Walker circulation for exploring trend of the deep convection activity. Besides, various climatic variables like temperature (maximum, minimum, mean), precipitation, and cloud cover dataset are used for exploring trend in major rice growing regions of the world. The results indicate that there is a significantly decreasing trend of OLR in ITCZ zone during summer monsoon season. Contrarily, major rice growing regions of the world have witnessed a significantly increasing trend for the temperature parameter among all the zones. Rainfall and cloud cover have shown a typical trend i.e., increasing rainfall but decreasing cloud cover in the Southeast Asian and Maritime Continent rice growing regions. In rice suitable climate assessment, it has been found that the Maritime Continent rice growing region, the Indo-Gangetic Plain and the Southeast Asian rice growing regions have witnessed better rice suitable climates than other rice growing regions during the last 42 years (1980–2021). Full article
(This article belongs to the Special Issue Subseasonal to Seasonal Climate Forecasting)
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14 pages, 7145 KiB  
Article
A Comparison of Wave Spectra during Pre-Monsoon and Post-Monsoon Tropical Cyclones under an Intense Positive IOD Year 2019
by Mourani Sinha, Somnath Jha and Anupam Kumar
Climate 2023, 11(2), 44; https://doi.org/10.3390/cli11020044 - 12 Feb 2023
Cited by 1 | Viewed by 2360
Abstract
The impact of Indian Ocean Dipole (IOD) events on the generation and intensity of tropical cyclones under the influence of monsoons is explored. The standardized sea surface temperature (SST) anomalies are computed for the pre-monsoon and post-monsoon months for the Bay of Bengal [...] Read more.
The impact of Indian Ocean Dipole (IOD) events on the generation and intensity of tropical cyclones under the influence of monsoons is explored. The standardized sea surface temperature (SST) anomalies are computed for the pre-monsoon and post-monsoon months for the Bay of Bengal (BOB) and Arabian Sea (AS) from 1971 to 2020 and relationships are analyzed with the frequency of tropical cyclones for the neutral, positive and negative IOD years. Ocean states are sensitive to cyclonic conditions exhibiting a complex spectral distribution of the wave energy. Due to a tropical cyclone, the surface waves remain under high wind forcing conditions for prolonged periods generating a huge amount of energy. The spectral wave model SWAN (Simulating WAves Nearshore) is used to generate the energy density spectra during FANI (26 April–5 May 2019), which was a pre-monsoon extreme severe cyclonic storm, and BULBUL (5–12 November 2019), which was a post-monsoon very severe cyclonic storm in the BOB region. This study aims to estimate the intensity of wave energy during tropical cyclones in the pre- and post-monsoon months for 2019 (an extremely positive IOD year). Full article
(This article belongs to the Special Issue Subseasonal to Seasonal Climate Forecasting)
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22 pages, 8714 KiB  
Article
Recent Warming Trends in the Arabian Sea: Causative Factors and Physical Mechanisms
by Jiya Albert, Venkata Sai Gulakaram, Naresh Krishna Vissa, Prasad K. Bhaskaran and Mihir K. Dash
Climate 2023, 11(2), 35; https://doi.org/10.3390/cli11020035 - 29 Jan 2023
Cited by 9 | Viewed by 4614
Abstract
In recent years, and particularly from 2000 onwards, the North Indian Ocean (NIO) has been acting as a major sink of ocean heat that is clearly visible in the sub-surface warming trend. Interestingly, a part of the NIO—the Arabian Sea (AS) sector—witnessed dramatic [...] Read more.
In recent years, and particularly from 2000 onwards, the North Indian Ocean (NIO) has been acting as a major sink of ocean heat that is clearly visible in the sub-surface warming trend. Interestingly, a part of the NIO—the Arabian Sea (AS) sector—witnessed dramatic variations in recent sub-surface warming that has direct repercussion on intense Tropical Cyclone (TC) activity. This study investigated the possible causative factors and physical mechanisms towards the multi-decadal warming trends in surface and sub-surface waters over the AS region. Responsible factors towards warming are examined using altimetric observations and reanalysis products. This study used ORAS5 OHC (Ocean Heat Content), derived meridional and zonal heat transport, currents, temperature, salinity, Outgoing Longwave Radiation (OLR), and air-sea fluxes to quantify the OHC build-up and its variability at water depths of 700 m (D700) and 300 m (D300) during the past four decades. The highest variability in deeper and upper OHC is noticed for the western and southern regions of the Indian Ocean. The warming trend is significantly higher in the deeper regions of AS compared to the upper waters, and relatively higher compared to the Bay of Bengal (BoB). Increased OHC in AS show good correlation with decreased OLR in the past 20 years. An analysis of altimetric observations revealed strengthening of downwelling Kelvin wave propagation leading to warming in eastern AS, mainly attributed due to intrusion of low saline water from BoB leading to stratification. Rossby wave associated with deepening of thermocline warmed the southern AS during its propagation. Heat budget analysis reveals that surface heat fluxes play a dominant role in warming AS during the pre-monsoon season. Increasing (decreasing) trend of surface heat fluxes (vertical entrainment) during 2000–2018 played a significant role in warming the southeastern sector of AS. Full article
(This article belongs to the Special Issue Subseasonal to Seasonal Climate Forecasting)
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19 pages, 4465 KiB  
Article
Appraisal of Satellite Rainfall Products for Malwathu, Deduru, and Kalu River Basins, Sri Lanka
by Helani Perera, Nipuna Senaratne, Miyuru B. Gunathilake, Nitin Mutill and Upaka Rathnayake
Climate 2022, 10(10), 156; https://doi.org/10.3390/cli10100156 - 20 Oct 2022
Cited by 2 | Viewed by 2385
Abstract
Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications. This evaluation [...] Read more.
Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications. This evaluation is very much necessary since, it had been found that their performances vary with different areas of interest. This research looks at the three prominent river basins; Malwathu, Deduru, and Kalu of Sri Lanka and evaluates six selected SRPs, namely, IMERG, TRMM 3B42, TRMM 3B42-RT, PERSIANN, PERSIANN-CCS, PERSIANN-CDR against 15+ years of observed rainfall data with the use of several indices. Four Continuous Evaluation Indices (CEI) such as Root Mean Square Error (RMSE), Percentage Bias (PBIAS), Pearson’s Correlation Coefficient (r), and Nash Sutcliffe Efficiency (NSE) were used to evaluate the accuracy of SRPs and four Categorical Indices (CI) namely, Probability of Detection (POD), Critical Success Index (CSI), False Alarm Ratio (FAR) and Proportion Correct (PC) was used to evaluate the detection and prediction accuracy of the SRPs. Then, the Mann–Kendall Test (MK test) was used to identify trends in the datasets and Theil’s and Sens Slope Estimator to quantify the trends observed. The study of categorical indicators yielded varying findings, with TRMM-3B42 performing well in the dry zone and IMERG doing well in the wet zone and intermediate zone of Sri Lanka. Regarding the CIs in the three basins, overall, IMERG was the most reliable. In general, all three basins had similar POD and PC findings. The SRPs, however, underperformed in the dry zone in terms of CSI and FAR. Similar findings were found in the CEI analysis, as IMERG gave top performance across the board for all four CEIs in the three basins. The three basins’ overall weakest performer was PERSIANN-CCS. The trend analysis revealed that there were very few significant trends in the observed data. Even when significant trends were apparent, the SRP projections seldom captured them. TRMM-3B42 RT had the best trend prediction performance. However, Sen’s slope analysis revealed that while the sense of the trend was properly anticipated, the amplitude of the prediction significantly differed from that of the observed data. Full article
(This article belongs to the Special Issue Subseasonal to Seasonal Climate Forecasting)
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