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Testing a flexible method to reduce false monsoon onsets.

Stiller-Reeve MA, Spengler T, Chu PS - PLoS ONE (2014)

Bottom Line: Another problem is that local communities or stakeholder groups may define the monsoon differently.The presented results yield improved information about the monsoon length and its interannual variability.This implies that we can potentially get a more detailed picture of local climate variations that can be used in more local climate application projects such as community-based adaptations.

View Article: PubMed Central - PubMed

Affiliation: Uni Research Climate, Bergen, Norway; Bjerknes Centre for Climate Research, Bergen, Norway.

ABSTRACT
To generate information about the monsoon onset and withdrawal we have to choose a monsoon definition and apply it to data. One problem that arises is that false monsoon onsets can hamper our analysis, which is often alleviated by smoothing the data in time or space. Another problem is that local communities or stakeholder groups may define the monsoon differently. We therefore aim to develop a technique that reduces false onsets for high-resolution gridded data, while also being flexible for different requirements that can be tailored to particular end-users. In this study, we explain how we developed our technique and demonstrate how it successfully reduces false onsets and withdrawals. The presented results yield improved information about the monsoon length and its interannual variability. Due to this improvement, we are able to extract information from higher resolution data sets. This implies that we can potentially get a more detailed picture of local climate variations that can be used in more local climate application projects such as community-based adaptations.

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Differences in multi-year standard deviation between the IA and conventional methods for a). onset and b). withdrawal.
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pone-0104386-g005: Differences in multi-year standard deviation between the IA and conventional methods for a). onset and b). withdrawal.

Mentions: The IA method reduces the standard deviation of onset and withdrawal by up to 5 pentads in some regions (Figure 5a). For the onset, large differences in standard deviation are observed over the Pradesh region of northeast India (Figure 5a). For the withdrawal, consistently lower standard deviations are shown over most of Bangladesh for example (Figure 5b). Few regions show increases in interannual variability with the application of the IA methodology.


Testing a flexible method to reduce false monsoon onsets.

Stiller-Reeve MA, Spengler T, Chu PS - PLoS ONE (2014)

Differences in multi-year standard deviation between the IA and conventional methods for a). onset and b). withdrawal.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126718&req=5

pone-0104386-g005: Differences in multi-year standard deviation between the IA and conventional methods for a). onset and b). withdrawal.
Mentions: The IA method reduces the standard deviation of onset and withdrawal by up to 5 pentads in some regions (Figure 5a). For the onset, large differences in standard deviation are observed over the Pradesh region of northeast India (Figure 5a). For the withdrawal, consistently lower standard deviations are shown over most of Bangladesh for example (Figure 5b). Few regions show increases in interannual variability with the application of the IA methodology.

Bottom Line: Another problem is that local communities or stakeholder groups may define the monsoon differently.The presented results yield improved information about the monsoon length and its interannual variability.This implies that we can potentially get a more detailed picture of local climate variations that can be used in more local climate application projects such as community-based adaptations.

View Article: PubMed Central - PubMed

Affiliation: Uni Research Climate, Bergen, Norway; Bjerknes Centre for Climate Research, Bergen, Norway.

ABSTRACT
To generate information about the monsoon onset and withdrawal we have to choose a monsoon definition and apply it to data. One problem that arises is that false monsoon onsets can hamper our analysis, which is often alleviated by smoothing the data in time or space. Another problem is that local communities or stakeholder groups may define the monsoon differently. We therefore aim to develop a technique that reduces false onsets for high-resolution gridded data, while also being flexible for different requirements that can be tailored to particular end-users. In this study, we explain how we developed our technique and demonstrate how it successfully reduces false onsets and withdrawals. The presented results yield improved information about the monsoon length and its interannual variability. Due to this improvement, we are able to extract information from higher resolution data sets. This implies that we can potentially get a more detailed picture of local climate variations that can be used in more local climate application projects such as community-based adaptations.

Show MeSH
Related in: MedlinePlus