The influence of ocean variations on the climate of Ireland

International Journal of Climatology, 2015

There is a paucity of dynamically downscaled climate model output at a high resolution over Ireland, of temperature projections for the mid-21st century. This study aims to address this shortcoming. A preliminary investigation of GCM data and high-resolution RCM data shows that the latter exhibits greater variability over Ireland by reducing the dominance of the surrounding seas on the climate signal. This motivates the subsequent dynamical downscaling and analysis of the temperature output from three high-resolution (4-7km grid size) RCMs over Ireland. The three RCMs, driven by four GCMs from CMIP3 and CMIP5, were run under different SRES and RCP future scenarios. Projections of mean and extreme temperature changes are considered for the mid-century (2041-2060) and assessed relative to the control period of 1981-2000. Analysis of the RCM data shows that annual mean temperatures are projected to rise to between 0.4°C and 1.8°C above control levels by mid-century. On a seasonal basis, results differ by forcing scenario. Future summers have the largest projected warming under RCP 8.5, where the greatest warming is seen in the southeast of Ireland. The remaining two high emission scenarios (SRESs A1B and A2) project future winters to have the greatest warming, with almost uniform increases of 1.5-2°C across the island. Changes in the bidecadal 5th and 95th percentile values of daily minimum and maximum temperatures, respectively, are also analysed. The greatest change in daily minimum temperature is projected for future winters (indicating fewer cold nights and frost days), a pattern which is consistent across all scenarios/forcings. An investigation into the distribution of temperature under RCP 8.5 shows a strong summer increase compounded by increased variability, and a winter increase compounded by an increase in skewness.

2017

Journal of Physical Oceanography, 2003

The temperature structure of the Irish Sea is investigated using a 3-yr simulation with a high-resolution (ϳ1.8 km) three-dimensional baroclinic model (the Proudman Oceanographic Laboratory Coastal-Ocean Modelling System) and CTD and Advanced Very High Resolution Radiometer observations. This paper focuses on the extent to which (horizontal) advection determines the temperature structure. It is found that it has a significant effect on the depth-mean temperatures throughout the region and on the vertical profiles in seasonally stratified areas, such as the Celtic Sea and western Irish Sea. There is depth-mean advective heating during the summer in these stratified regions, whereas in well-mixed regions advection tends to reduce the amplitude of the seasonal cycle. Through an analysis of the terms in the temperature equation, the warming of the ''cool pool'' waters of the western Irish Sea can be attributed to the advection of partially well-mixed waters into the stratified region from the north. This occurs as an entrainment process with the southward current on the western side of this region folding in this water from the north. This current is seen to originate both as part of the ''gyre'' circulation and from southward flow through the North Channel of the Irish Sea. The accuracy to which temperatures are modeled (particularly near the seabed in this stratified region), as compared with an experiment without temperature and salinity advection, lends weight to this interpretation of the model results. Overall rms errors against CTD observations are 1.1ЊC with advection and 1.7ЊC without. In addition to the direct effects of currents, salinity stratification (which is not present without advection in the western Irish Sea in this model) is seen to play a role in determining the temperature structure, particularly in the spring and early summer. Unlike previous baroclinic simulations in this region, the model run is continued for a further 2 yr, allowing the investigation of the seasonal cycle of temperature far removed from the initial condition. In a number of regions, a systematic overestimation of the winter temperatures is found (the cause of which has yet to be identified), but this bias does not compromise the accuracy of the results between the spring and autumn of subsequent years.

Climate of the Past, 2018

A continuous 305-year (1711-2016) monthly rainfall series (IoI_1711) is created for the Island of Ireland. The post 1850 series draws on an existing quality assured rainfall network for Ireland, while pre-1850 values come from instrumental and documentary series compiled, but not published by the UK Met Office. The series is evaluated by comparison with independent long-term observations and reconstructions of precipitation, temperature and circulation indices from across the British-Irish Isles. Strong decadal consistency of IoI_1711 with other long-term observations is evident throughout the annual, boreal spring and autumn series. Annually, the most recent decade (2006-2015) is found to be the wettest in over 300 years. The winter series is probably too dry between the 1740s and 1780s, but strong consistency with other long-term observations strengthens confidence from 1790 onwards. The IoI_1711 series has remarkably wet winters during the 1730s, concurrent with a period of strong westerly airflow, glacial advance throughout Scandinavia and near unprecedented warmth in the Central England Temperature record-all consistent with a strongly positive phase of the North Atlantic Oscillation. Unusually wet summers occurred in the 1750s, consistent with proxy (treering) reconstructions of summer precipitation in the region. Our analysis shows that inter-decadal variability of precipitation is much larger than previously thought, while relationships with key modes of climate variability are time-variant. The IoI_1711 series reveals statistically significant multicentennial trends in winter (increasing) and summer (decreasing) seasonal precipitation. However, given uncertainties in the early winter record, the former finding should be regarded as tentative. The derived record, one of the longest continuous series in Europe, offers valuable insights for understanding multi-decadal and centennial rainfall variability in Ireland, and provides a firm basis for benchmarking other long-term records and reconstructions of past climate. Correlation of Irish rainfall with other parts of Europe increases the utility of the series for understanding historical climate in further regions.

Polynomial regression techniques were used to d erive a baseline climatology for Ireland a t a scale of l km2 for the p eriod 1961-90. Monthly climate variables were related to position and elevation on a digital elevation model and these were found to provide good predicto rs fo r precipitat ion and m aximum/minim um temperature. Baseline maps fo r mean monthly radiation receipt a nd poten tial evapotranspiratio n were a lso derived at 1 km 2 scales. The National Centers for Environmental P rediction/National Center for A tm ospheric Research (NCEP/NCAR) Reanalysis D at a were then related to this b aselin e climatology a nd relatio nships be n veen upper air variables and surface climate establish ed as a basis for sta tistical downscal ing of global climate models. Monthly output for the spatial domain over Irela nd were extrac ted from th e latest Hadley C entre C lobal C limate Model (HadCM3). Using the upper air/surface relationships the climate differen ces be t\'Vee n a modelled run for the 196 1-90 period and the pe riod 204 1-70 was establish ed. T hese differences w ere th en applied to the b aseline climate d ata to provide future climatic scenarios fo r I reland fo r these period s. Mean te mpe rature increases of 2-3°C we re projected for mid century for both summ er and winter. Precip itation changes showed w inte r increases of the orde r of 10% in weste rn Ireland a nd similar summer decreases esp ecially in eastern Ireland. Observation al data tren ds appear to match these projectio ns.

Journal of Geophysical Research, 2007

The variability of temperature and salinity in the Irish Sea over the 40 year period 1960-1999 is investigated using a free-running fine-resolution local area model. The skill of the model to represent observed temperature and salinity variability is assessed using conductivity-temperature-depth survey data (3397 profiles) and a long time series of measurements from Cypris station (southwest of Isle of Man). This clearly demonstrates that the model can reproduce the observed seasonal and longer-term cycles in temperature, with mean and RMS errors of À0.01°C and 0.78°C. Particularly apparent is the long-term warming trend at Cypris station and throughout the model domain. Model estimates of salinity are less accurate and are generally too saline (mean and RMS errors are 0.79 and 0.98 practical salinity units). Inaccuracies are likely to arise from boundary conditions and forcing (riverine and surface). However, while absolute values are not particularly well represented, the model reproduces many of the trends in the salinity variability observed at Cypris station, suggesting that the dominant physical processes in the Irish Sea, with timescales up to $3 years, are well represented. The model is also used to investigate the variability in temperature stratification. While stratification is confined to approximately the same geographical area in each year of the simulation, there is significant variability in the timing of the onset and breakdown of stratification and in the peak surface to bed temperature difference. Together, these results suggest that a local area model with limited boundary conditions may be sufficiently accurate for climatic investigation of some (locally forced) parameters.

International Journal of Climatology, 2011

Surface air temperatures modelled by ERA-40, ERA-Interim and (NCEP)/(NCAR) reanalysis (NNRP-1) have been compared with observations at 11 synoptic stations in Ireland over the period 1989-2001. The three reanalysis datasets show good agreement with the observed data and with each other. Slopes of the least-squares line to scatter plots of reanalysis data versus observational data show small differences between the three reanalyses, with ERA-40, ERA-Interim and NNRP-1 slopes ranging between (0.79-1.06) ± 0.01, (0.83-1.01) ± 0.01 and (0.76-0.98) ± 0.01, respectively. Summary statistics and the monthly mean temperatures over the 1989-2001 period showed that the reanalyses were significantly warmer in winter than the observations, which resulted in best fit lines with slopes consistently less than unity. ERA-Interim was slightly better than both ERA-40 and NNRP-1 at modelling winter temperatures and it had higher correlation coefficients with the observations. All three reanalyses use different grid sizes and types. Subsequent regridding of the ERA-Interim and NNRP-1 data to the ERA-40 grid showed that the grid difference had no significant influence on the results. Comparison of ERA-Interim and NNRP-1 data with the air temperatures at four marine buoys around the Irish coast for the period 2001-2005 showed that the reanalyses modelled colder winter temperatures than the observations; resulting in best fit lines with slopes consistently greater than unity. The slopes for NNRP-1 and ERA-Interim at the marine buoys, respectively, averaged 1.09 ± 0.04 and 1.10 ± 0.05 while the slopes at the four land stations over the same period averaged 0.87 ± 0.02 and 0.89 ± 0.02, respectively. We believe that this pattern results from the difference in the treatment of land and sea surfaces in the reanalysis datasets.

Journal of Marine Systems, 2014

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Climate Dynamics, 2012

Proxy and instrumental records reflect a quasicyclic 50-80-year climate signal across the Northern Hemisphere, with particular presence in the North Atlantic. Modeling studies rationalize this variability in terms of intrinsic dynamics of the Atlantic Meridional Overturning Circulation influencing distribution of sea-surface-temperature anomalies in the Atlantic Ocean; hence the name Atlantic Multidecadal Oscillation (AMO). By analyzing a lagged covariance structure of a network of climate indices, this study details the AMO-signal propagation throughout the Northern Hemisphere via a sequence of atmospheric and lagged oceanic teleconnections, which the authors term the ''stadium wave''. Initial changes in the North Atlantic temperature anomaly associated with AMO culminate in an oppositely signed hemispheric signal about 30 years later. Furthermore, shorter-term, interannual-to-interdecadal climate variability alters character according to polarity of the stadium-wave-induced prevailing hemispheric climate regime. Ongoing research suggests mutual interaction between shorter-term variability and the stadium wave, with indication of ensuing modifications of multidecadal variability within the Atlantic sector. Results presented here support the hypothesis that AMO plays a significant role in hemispheric and, by inference, global climate variability, with implications for climate-change attribution and prediction.

2013

Proxy and instrumental records reflect a quasi-cyclic 50-to-80-year climate signal across the Northern Hemisphere, with particular presence in the North Atlantic. Modeling studies rationalize this variability in terms of intrinsic dynamics of the Atlantic Meridional Overturning Circulation influencing distribution of sea-surface-temperature anomalies in the Atlantic Ocean; hence the name Atlantic Multidecadal Oscillation (AMO). By analyzing a lagged covariance structure of a network of climate indices, this study details the AMO-signal propagation throughout the Northern Hemisphere via a sequence of atmospheric and lagged oceanic teleconnections, which the authors term the "stadium wave". Initial changes in the North Atlantic temperature anomaly associated with AMO culminate in an oppositely signed hemispheric signal about 30 years later. Furthermore, shorter-term, interannual-to-interdecadal climate variability alters character according to polarity of the stadium-wave-induced prevailing hemispheric climate regime. Ongoing research suggests mutual interaction between shorter-term variability and the stadium wave, with indication of ensuing modifications of multidecadal variability within the Atlantic sector.