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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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Related in: MedlinePlus

The trend in total yearly rainfall between 1978–2007 using the APHRODITE rainfall data set.The purpose of the figure is solely to illustrate the complexity in the monsoon system. For example, Bariyarpur experiences a negative trend of −14.7 mm mm/year/year, whereas Maniknagar has experienced a positive trend of +16.7 mm mm/year/year.
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pone-0104386-g001: The trend in total yearly rainfall between 1978–2007 using the APHRODITE rainfall data set.The purpose of the figure is solely to illustrate the complexity in the monsoon system. For example, Bariyarpur experiences a negative trend of −14.7 mm mm/year/year, whereas Maniknagar has experienced a positive trend of +16.7 mm mm/year/year.

Mentions: We illustrate these spatial variations by looking at the trends in total yearly rainfall within a single monsoon region between 1978–2007 as shown in Figure 1. We calculated the trends from the Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE, V1101R1) rainfall data set [6], [7]. We calculated statistical significance using a bootstrapping method. We rejected our hypothesis that the trend was non-zero if the trend lay outside the 5% and 95% percentiles of trends taken from 1000 random permutations of the time series at each grid point. The average trend over the whole region is +1.47 mm/year/year, which is not statistically significant. However, if we focus on local climate, then trends can become more significant. For example, in Bariyarpur, Madhya Pradesh, India, the trend was −14.7 mm/year/year, at the 10% significance test level. In Maniknagar, Bangladesh, the trend was +16.7 mm/year/year, at the 10% significance test level. This shows that we cannot apply information about the large-scale trend at locations where the local climate behaves very differently. We clearly need a local focus, if we aim to produce climate information that is useable [8] by people in places like Bariyarpur and Maniknagar, regional planners or other end users.


Testing a flexible method to reduce false monsoon onsets.

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

The trend in total yearly rainfall between 1978–2007 using the APHRODITE rainfall data set.The purpose of the figure is solely to illustrate the complexity in the monsoon system. For example, Bariyarpur experiences a negative trend of −14.7 mm mm/year/year, whereas Maniknagar has experienced a positive trend of +16.7 mm mm/year/year.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0104386-g001: The trend in total yearly rainfall between 1978–2007 using the APHRODITE rainfall data set.The purpose of the figure is solely to illustrate the complexity in the monsoon system. For example, Bariyarpur experiences a negative trend of −14.7 mm mm/year/year, whereas Maniknagar has experienced a positive trend of +16.7 mm mm/year/year.
Mentions: We illustrate these spatial variations by looking at the trends in total yearly rainfall within a single monsoon region between 1978–2007 as shown in Figure 1. We calculated the trends from the Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE, V1101R1) rainfall data set [6], [7]. We calculated statistical significance using a bootstrapping method. We rejected our hypothesis that the trend was non-zero if the trend lay outside the 5% and 95% percentiles of trends taken from 1000 random permutations of the time series at each grid point. The average trend over the whole region is +1.47 mm/year/year, which is not statistically significant. However, if we focus on local climate, then trends can become more significant. For example, in Bariyarpur, Madhya Pradesh, India, the trend was −14.7 mm/year/year, at the 10% significance test level. In Maniknagar, Bangladesh, the trend was +16.7 mm/year/year, at the 10% significance test level. This shows that we cannot apply information about the large-scale trend at locations where the local climate behaves very differently. We clearly need a local focus, if we aim to produce climate information that is useable [8] by people in places like Bariyarpur and Maniknagar, regional planners or other end users.

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