Precipitation trends in the island of Ireland using a dense, homogenized, observational dataset, 2020
A dense monthly precipitation dataset of Ireland and Northern Ireland was homogenized with severa... more A dense monthly precipitation dataset of Ireland and Northern Ireland was homogenized with several modern homogenization methods. The efficiency of these homogenizations was tested by examining the similarity of homogeniza-tion results both in the real data homogenization and in the homogenization of a simulated dataset. The analysis of homogenization results shows that the real dataset is characterized by a large number of, but mostly small, non-climatic biases, and a moderate reduction of such biases can be achieved with homogenization. Finally, a combination of the ACMANT and Climatol homogenization results was applied to improve the data accuracy before the trend calculations. These two methods were selected for their proven high accuracy, missing data tolerance and ability to complete time series via the infilling of missing values before the trend calculations. Metadata were used within the Climatol method. To facilitate this analysis the study area was split into smaller climatic regions by using the Ward clustering method. Five climatic zones consistent with the known spatial patterns of precipitation in Ire-land were established. Linear regression fitting and the Mann-Kendall test were applied. Low frequency fluctuations were also examined by applying a Gaussian filter. The results show that the precipitation amount generally increases in the study area, particularly in the northwestern region. The most significant increasing trends for the whole study period (1941-2010) are found for late winter and spring precipitation, as well as for the annual totals. In the period from the early 1970s the increase of precipitation is general in all seasons of the year except in winter, but the statistical significance of this increase is weak. K E Y W O R D S
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Papers by John Coll
air temperature test datasets. The homogeneous database is derived from an earlier benchmarking of daily temperature data in the
USA, and then outliers and inhomogeneities (IHs) are randomly inserted into the time series. Three inhomogeneous datasets are
generated and used, one with relatively few and small IHs, another one with IHs of medium frequency and size, and a third one
with large and frequent IHs. All of the inserted IHs are changes to the means. Most of the IHs are single sudden shifts or pair of
shifts resulting in platform-shaped biases. Each test dataset consists of 158 time series of 100 years length, and their mean spatial
correlation is 0.68–0.88. For examining the impacts of missing data, seven experiments are performed, in which 18 series are left
complete, while variable quantities (10–70%) of the data of the other 140 series are removed.
The results show that data gaps have a greater impact on the monthly root mean squared error (RMSE) than the annualRMSE
and trend bias. When data with a large ratio of gaps is homogenised, the reduction of the upper 5% of the monthly RMSE is the
least successful, but even there, the efficiency remains positive. In terms of reducing the annual RMSE and trend bias, the
efficiency is 54–91%. The inclusion of short and incomplete series with sufficient spatial correlation in all cases improves the
efficiency of homogenisation with ACMANTv3.
often affect the spatial and temporal comparability of the data; therefore, an important
part of improving the accuracy of observed climate variability is the time series homogenisation of
the source data. In undertaking homogenisation, an essential step is the spatial comparison of the
data within the same geographical region. To optimise the efficiency of homogenisation, we
should know when and to what extent two series are of the same geographical origin from a climatic
perspective, and how many partner series should be used. This study presents a number of
novel experiments for obtaining objective answers to these questions. Monthly temperature test
datasets were homogenised with ACMANT (Adapted Caussinus-Mestre Algorithm for homo -
genising Networks of Temperature series) by varying the number of partner series and their spatial
correlations with the candidate series. First, a homogeneous benchmark is constructed from
2 regional subsets of a simulated surface air temperature dataset from earlier work. Various kinds
of inhomogeneities are then inserted into the time series, producing 5 basic types of test datasets
for each geographical region. Further variation is introduced by adding additional noise to some
datasets, providing more diverse spatial correlations. The results indicate that for the identifi -
cation and correction of long-lasting biases in the data, the optimal number of partner series is
about 30. The optimum is largely independent from the frequency and intensity of inhomogeneities
and from the spatial correlation between the candidate series and its partner series. This
latter finding is unexpected; hence, its possible causes and the consequences are discussed and
explored more fully here.
(ACMANT), one of the most successful homogenisation methods tested by the European project COST ES0601 (HOME)
has been continued. The third generation of the software package ‘ACMANT3’ contains six programmes for homogenising
temperature values or precipitation totals. These incorporate two models of the annual cycle of temperature biases and
homogenisation either on a monthly or daily time scale. All ACMANT3 programmes are fully automatic and the method
is therefore suitable for homogenising large datasets. This paper describes the theoretical background of ACMANT and the
recent developments, which extend the capabilities, and hence, the application of the method. The most important novelties in
ACMANT3 are: the ensemble pre-homogenisation with the exclusion of one potential reference composite in each ensemble
member; the use of ordinary kriging for weighting reference composites; the assessment of seasonal cycle of temperature
biases in case of irregular-shaped seasonal cycles. ACMANT3 also allows for homogenisation on the daily scale including
for break timing assessment, gap filling and analysis of ANOVA application on the daily time scale. Examples of efficiency
tests of monthly temperature homogenisation using artificially developed but realistic test datasets are presented. ACMANT3
can be characterized by improved efficiency in comparison with earlier ACMANT versions, high missing data tolerance and
improved user friendliness. Discussion concerning when the use of an automatic homogenisation method is recommended is
included, and some caveats in relation to how and when ACMANT3 should be applied are provided.
on water treatment and distribution, and subsequently human health. Projections were made of impacts of climate
change on dissolved organic carbon (DOC) in the primarily agricultural Boyne catchment which is used
as a potablewater supply in Ireland. The results indicated that excluding a potential rise in extreme precipitation,
future projected loads are not dissimilar to those observed under current conditions. This is because projected increases
in DOC concentrations are offset by corresponding decreases in precipitation and hence river flow. However,
the results presented assume no changes in land use and highlight the predicted increase in DOC loads from
abstracted waters at water treatment plants.
influenced by changes in the climate. Because of the oceanic environment, Ireland has a high proportion
of the northern Atlantic wet heaths and alpine and boreal heaths of high conservation
value within Europe. Future climate change is widely expected to place additional pressure on
these systems. Seven bioclimatic envelope modelling techniques implemented in the BIOMOD
modelling framework were used to model wet heath and alpine and boreal heath distributions in
Ireland. The 1961−1990 baseline models closely matched the observed distribution and emphasise
the strong dependency on climate. Mean winter precipitation, mean winter temperature and elevation
were found to be important model components. The fitted model’s discrimination ability
was assessed using the area under the curve of a receiver operating characteristic plot; the true
skill statistic; and Cohen’s kappa. A BIOMOD ensemble prediction from all the models was used
to project changes based on a climate change scenario for 2031−2060 dynamically downscaled
from the Hadley Centre HadCM3-Q16 global climate model. The climate change projections for
the individual models change markedly from the consistent baseline predictions. Although the
consensus models project gains in climate space for both habitats in other parts of the country,
new habitat formation in these areas is unlikely, as current (and hence near-future) land use and
other conditions are not likely to favour expansion.
KEY WORDS: Wet heaths · Alpine heaths · Boreal heaths · Climate change · Bioclimatic envelope
models · BIOMOD · Climate space
2. Lepidoteran communities are an important component of raised bog biodiversity
and may be useful as biodiversity indicators, yet they are a neglected
area of research.
3. We address this by surveying night-flying macro-moths on six protected and six degraded raised bogs to establish whether there is a distinct moth fauna associated with the wettest areas of protected sites by comparing them to assemblages found on degraded sites where this wet habitat has been lost.
4. In general, differences between moth assemblages on protected and degraded
raised bogs are rather subtle, with assemblages on both site types generally similar.
But, a number of species were found to be associated with protected sites, three of which are bog-associated species of conservation concern and may be particularly
vulnerable due to the continuing loss of the wettest areas of raised bogs.
5. Degraded sites were found to harbour a significant number of bog-associated
species of conservation concern and may have a role to play in peatland invertebrate conservation, hitherto undervalued. To determine this, further research is required to describe the invertebrate fauna of these sites and of marginal areas of protected sites.
2. Lepidoteran communities are an important component of raised bog biodiversity and may be useful as biodiversity indicators, yet they are a neglected area of research.
3. We address this by surveying night-flying macro-moths on six protected and six degraded raised bogs to establish whether there is a distinct moth fauna associated with the wettest areas of protected sites by comparing them to assemblages found on degraded sites where this wet habitat has been lost.
4. In general, differences between moth assemblages on protected and degraded raised bogs are rather subtle, with assemblages on both site types generally similar. But, a number of species were found to be associated with protected sites, three of which are bog-associated species of conservation concern and may be particularly vulnerable due to the continuing loss of the wettest areas of raised bogs.
5. Degraded sites were found to harbour a significant number of bog-associated species of conservation concern and may have a role to play in peatland invertebrate conservation, hitherto undervalued. To determine this, further research is required to describe the invertebrate fauna of these sites and of marginal areas of protected sites.
air temperature test datasets. The homogeneous database is derived from an earlier benchmarking of daily temperature data in the
USA, and then outliers and inhomogeneities (IHs) are randomly inserted into the time series. Three inhomogeneous datasets are
generated and used, one with relatively few and small IHs, another one with IHs of medium frequency and size, and a third one
with large and frequent IHs. All of the inserted IHs are changes to the means. Most of the IHs are single sudden shifts or pair of
shifts resulting in platform-shaped biases. Each test dataset consists of 158 time series of 100 years length, and their mean spatial
correlation is 0.68–0.88. For examining the impacts of missing data, seven experiments are performed, in which 18 series are left
complete, while variable quantities (10–70%) of the data of the other 140 series are removed.
The results show that data gaps have a greater impact on the monthly root mean squared error (RMSE) than the annualRMSE
and trend bias. When data with a large ratio of gaps is homogenised, the reduction of the upper 5% of the monthly RMSE is the
least successful, but even there, the efficiency remains positive. In terms of reducing the annual RMSE and trend bias, the
efficiency is 54–91%. The inclusion of short and incomplete series with sufficient spatial correlation in all cases improves the
efficiency of homogenisation with ACMANTv3.
often affect the spatial and temporal comparability of the data; therefore, an important
part of improving the accuracy of observed climate variability is the time series homogenisation of
the source data. In undertaking homogenisation, an essential step is the spatial comparison of the
data within the same geographical region. To optimise the efficiency of homogenisation, we
should know when and to what extent two series are of the same geographical origin from a climatic
perspective, and how many partner series should be used. This study presents a number of
novel experiments for obtaining objective answers to these questions. Monthly temperature test
datasets were homogenised with ACMANT (Adapted Caussinus-Mestre Algorithm for homo -
genising Networks of Temperature series) by varying the number of partner series and their spatial
correlations with the candidate series. First, a homogeneous benchmark is constructed from
2 regional subsets of a simulated surface air temperature dataset from earlier work. Various kinds
of inhomogeneities are then inserted into the time series, producing 5 basic types of test datasets
for each geographical region. Further variation is introduced by adding additional noise to some
datasets, providing more diverse spatial correlations. The results indicate that for the identifi -
cation and correction of long-lasting biases in the data, the optimal number of partner series is
about 30. The optimum is largely independent from the frequency and intensity of inhomogeneities
and from the spatial correlation between the candidate series and its partner series. This
latter finding is unexpected; hence, its possible causes and the consequences are discussed and
explored more fully here.
(ACMANT), one of the most successful homogenisation methods tested by the European project COST ES0601 (HOME)
has been continued. The third generation of the software package ‘ACMANT3’ contains six programmes for homogenising
temperature values or precipitation totals. These incorporate two models of the annual cycle of temperature biases and
homogenisation either on a monthly or daily time scale. All ACMANT3 programmes are fully automatic and the method
is therefore suitable for homogenising large datasets. This paper describes the theoretical background of ACMANT and the
recent developments, which extend the capabilities, and hence, the application of the method. The most important novelties in
ACMANT3 are: the ensemble pre-homogenisation with the exclusion of one potential reference composite in each ensemble
member; the use of ordinary kriging for weighting reference composites; the assessment of seasonal cycle of temperature
biases in case of irregular-shaped seasonal cycles. ACMANT3 also allows for homogenisation on the daily scale including
for break timing assessment, gap filling and analysis of ANOVA application on the daily time scale. Examples of efficiency
tests of monthly temperature homogenisation using artificially developed but realistic test datasets are presented. ACMANT3
can be characterized by improved efficiency in comparison with earlier ACMANT versions, high missing data tolerance and
improved user friendliness. Discussion concerning when the use of an automatic homogenisation method is recommended is
included, and some caveats in relation to how and when ACMANT3 should be applied are provided.
on water treatment and distribution, and subsequently human health. Projections were made of impacts of climate
change on dissolved organic carbon (DOC) in the primarily agricultural Boyne catchment which is used
as a potablewater supply in Ireland. The results indicated that excluding a potential rise in extreme precipitation,
future projected loads are not dissimilar to those observed under current conditions. This is because projected increases
in DOC concentrations are offset by corresponding decreases in precipitation and hence river flow. However,
the results presented assume no changes in land use and highlight the predicted increase in DOC loads from
abstracted waters at water treatment plants.
influenced by changes in the climate. Because of the oceanic environment, Ireland has a high proportion
of the northern Atlantic wet heaths and alpine and boreal heaths of high conservation
value within Europe. Future climate change is widely expected to place additional pressure on
these systems. Seven bioclimatic envelope modelling techniques implemented in the BIOMOD
modelling framework were used to model wet heath and alpine and boreal heath distributions in
Ireland. The 1961−1990 baseline models closely matched the observed distribution and emphasise
the strong dependency on climate. Mean winter precipitation, mean winter temperature and elevation
were found to be important model components. The fitted model’s discrimination ability
was assessed using the area under the curve of a receiver operating characteristic plot; the true
skill statistic; and Cohen’s kappa. A BIOMOD ensemble prediction from all the models was used
to project changes based on a climate change scenario for 2031−2060 dynamically downscaled
from the Hadley Centre HadCM3-Q16 global climate model. The climate change projections for
the individual models change markedly from the consistent baseline predictions. Although the
consensus models project gains in climate space for both habitats in other parts of the country,
new habitat formation in these areas is unlikely, as current (and hence near-future) land use and
other conditions are not likely to favour expansion.
KEY WORDS: Wet heaths · Alpine heaths · Boreal heaths · Climate change · Bioclimatic envelope
models · BIOMOD · Climate space
2. Lepidoteran communities are an important component of raised bog biodiversity
and may be useful as biodiversity indicators, yet they are a neglected
area of research.
3. We address this by surveying night-flying macro-moths on six protected and six degraded raised bogs to establish whether there is a distinct moth fauna associated with the wettest areas of protected sites by comparing them to assemblages found on degraded sites where this wet habitat has been lost.
4. In general, differences between moth assemblages on protected and degraded
raised bogs are rather subtle, with assemblages on both site types generally similar.
But, a number of species were found to be associated with protected sites, three of which are bog-associated species of conservation concern and may be particularly
vulnerable due to the continuing loss of the wettest areas of raised bogs.
5. Degraded sites were found to harbour a significant number of bog-associated
species of conservation concern and may have a role to play in peatland invertebrate conservation, hitherto undervalued. To determine this, further research is required to describe the invertebrate fauna of these sites and of marginal areas of protected sites.
2. Lepidoteran communities are an important component of raised bog biodiversity and may be useful as biodiversity indicators, yet they are a neglected area of research.
3. We address this by surveying night-flying macro-moths on six protected and six degraded raised bogs to establish whether there is a distinct moth fauna associated with the wettest areas of protected sites by comparing them to assemblages found on degraded sites where this wet habitat has been lost.
4. In general, differences between moth assemblages on protected and degraded raised bogs are rather subtle, with assemblages on both site types generally similar. But, a number of species were found to be associated with protected sites, three of which are bog-associated species of conservation concern and may be particularly vulnerable due to the continuing loss of the wettest areas of raised bogs.
5. Degraded sites were found to harbour a significant number of bog-associated species of conservation concern and may have a role to play in peatland invertebrate conservation, hitherto undervalued. To determine this, further research is required to describe the invertebrate fauna of these sites and of marginal areas of protected sites.