Glacier-climate interactions: a synoptic approach

The reliance on freshwater released by mountain glaciers and ice caps demands that the effects of climate change on these thermally-sensitive systems are evaluated thoroughly. Coupling climate variability to processes of mass and energy exchange at the glacier scale is challenged, however, by a lack of climate data at an appropriately fine spatial resolution. The thesis addresses this challenge through attempting to reconcile this scale mismatch: glacier boundary-layer observations of meteorology and ablation at Vestari Hagafellsjökull, Iceland, and Storglaciären, Sweden, are related to synoptic-scale meteorological variability recorded in gridded, reanalysis data. Specific attention is directed toward synoptic controls on: i) near-surface air temperature lapse rates; ii) stationarity of temperature-index melt model parameters; and iii) glacier-surface ablation. A synoptic weather-typing procedure, which groups days of similar reanalysis meteorology into weather categories , forms the basis of the analytical approach adopted to achieve these aims. Lapse rates at Vestari Hagafellsjökull were found to be shallowest during weather categories characterised by warm, cloud-free weather that encouraged katabatic drainage; steep lapse rates were encountered in weather categories associated with strong synoptic winds. Quantitatively, 26% to 38% of the daily lapse-rate variability could be explained by weather-category and regression-based models utilizing the reanalysis data: a level of skill sufficient to effect appreciable improvements in the accuracy of air temperatures extrapolated vertically over Vestari Hagafellsjökull. Weather categories also highlighted the dynamic nature of the temperature-ablation relationship. Notably, the sensitivity of ablation to changes in air temperature was observed to be non-stationary between weather categories, highlighting vulnerabilities of temperature-index models. An innovative solution to this limitation is suggested: the relationship between temperature and ablation can be varied as a function of weather-category membership. This flexibility leads to an overall improvement in the simulation of daily ablation compared to traditional temperature-index formulations (up to a 14% improvement in the amount of variance explained), without the need for additional meteorological data recorded in-situ. It is concluded that weather categories are highly appropriate for evaluating synoptic controls on glacier meteorology and surface energetics; significant improvements in the parameterization of boundary-layer meteorology and ablation rates are realised through their application

Multi-century trends to wetter winters and drier summers in the England and Wales precipitation series explained by observational and sampling bias in early records

Globally, few precipitation records extend to the 18th century. The England Wales Precipitation (EWP) series is a notable exception with continuous monthly records from 1766. EWP has found widespread use across diverse fields of research including trend detection, evaluation of climate model simulations, as a proxy for mid-latitude atmospheric circulation, a predictor in long-term European gridded precipitation data sets, the assessment of drought and extremes, tree-ring reconstructions and as a benchmark for other regional series. A key finding from EWP has been the multi-centennial trends towards wetter winters and drier summers. We statistically reconstruct seasonal EWP using independent, quality-assured temperature, pressure and circulation indices. Using a sleet and snow series for the UK derived by Profs. Gordon Manley and Elizabeth Shaw to examine winter reconstructions, we show that precipitation totals for pre-1870 winters are likely biased low due to gauge under-catch of snowfall and a higher incidence of snowfall during this period. When these factors are accounted for in our reconstructions, the observed trend to wetter winters in EWP is no longer evident. For summer, we find that pre-1820 precipitation totals are too high, likely due to decreasing network density and less certain data at key stations. A significant trend to drier summers is not robustly present in our reconstructions of the EWP series. While our findings are more certain for winter than summer, we highlight (a) that extreme caution should be exercised when using EWP to make inferences about multi-centennial trends, and; (b) that assessments of 18th and 19th Century winter precipitation should be aware of potential snow biases in early records. Our findings underline the importance of continual re-appraisal of established long-term climate data sets as new evidence becomes available. It is also likely that the identified biases in winter EWP have distorted many other long-term European precipitation series

The forgotten drought of 1765–1768: Reconstructing and re-evaluating historical droughts in the British and Irish Isles

Historical precipitation records are fundamental for the management of water resources, yet rainfall observations typically span 100–15 0 years at most, with considerable uncertainties surrounding earlier records. Here, we analyse some of the longest a vailabl e precipitation records globally, for England and Wales, Scotland and Ireland. To assess the credibility of these records and extend them further back in time, we statistically reconstruct (using independent predictors) monthly precipitation series representing these regions for the period 1748–2000. By applying the Standardized Precipi- tation Index at 12-month accumulations (SPI-12) to the observed and our reconstructed series we re-evaluate historical meteorological droughts. We find strong agreement between observed and reconstructed drought chronol- ogies in post-1870 records, but divergence in e arlier series due to biases in early precipitation observations. Hence, the 1800s decade was less drought prone in our reconstructions relative to observations. Overall, the drought of 1834–1836 was the most intense SPI-12 event in our reconstruction for England and Wales. Newspaper accounts and documentary sources confirm the extent of impacts across England in particular. We also identify a major, “forgotten” drought in 1765–1768 that affected the British-Irish Isles. This was the most intense event in our reconstructions for Ireland and Scotland, and ranks first for accumulated deficits a cross all three regional series. Moreover, the 1765–1768 event was also the most extreme multi-year drought across all regional series when considering 36-month a ccumulations (SPI-36). Newspaper and other sources confirm the occurrence and major socio- economic impact of this drought, such as major rivers like the Shannon being fordable by foot. Our results provide new insights into historical droughts across the British Irish Isles. Given the importance of historical droughts for stress-testing the resilience of water resources, drought plans and supply sys- tems, the forgotten drought of 1765–1 768 offers perhaps the most extreme benchmark scenario in more than 250-years

The 'dirty dozen' of freshwater science: detecting then reconciling hydrological data biases and errors

Sound water policy and management rests on sound hydrometeorological and ecological data. Conversely, unrepresentative, poorly collected, or erroneously archived data introduce uncertainty regarding the magnitude, rate, and direction of environmental change, in addition to undermining confidence in decision-making processes. Unfortunately, data biases and errors can enter the information flow at various stages, starting with site selection, instrumentation, sampling/measurement procedures, postprocessing and ending with archiving systems. Techniques such as visual inspection of raw data, graphical representation, and comparison between sites, outlier, and trend detection, and referral to metadata can all help uncover spurious data. Tell-tale signs of ambiguous and/or anomalous data are highlighted using 12 carefully chosen cases drawn mainly from hydrology (‘the dirty dozen’). These include evidence of changes in site or local conditions (due to land management, river regulation, or urbanization); modifications to instrumentation or inconsistent observer behavior; mismatched or misrepresentative sampling in space and time; treatment of missing values, postprocessing and data storage errors. Also for raising awareness of pitfalls, recommendations are provided for uncovering lapses in data quality after the information has been gathered. It is noted that error detection and attribution are more problematic for very large data sets, where observation networks are automated, or when various information sources have been combined. In these cases, more holistic indicators of data integrity are needed that reflect the overall information life-cycle and application(s) of the hydrological data

The “dirty dozen” of freshwater science: Detecting then reconciling hydrological data biases and errors

Sound water policy and management rests on sound hydrometeorological and ecological data. Conversely, unrepresentative, poorly collected or erroneously archived data introduces uncertainty regarding the magnitude, rate and direction of environmental change, in addition to undermining confidence in decision-making processes. Unfortunately, data biases and errors can enter the information flow at various stages, starting with site selection, instrumentation, sampling/ measurement procedures, post-processing and ending with archiving systems. Techniques such as visual inspection of raw data, graphical representation and comparison between sites, outlier and trend detection, and referral to metadata can all help uncover spurious data. Tell-tale signs of ambiguous and/or anomalous data are highlighted using 12 carefully chosen cases drawn mainly from hydrology (‘the dirty dozen’). These include evidence of changes in site or local conditions (due to land management, river regulation or urbanisation); modifications to instrumentation or inconsistent observer behaviour; mismatched or misrepresentative sampling in space and time; treatment of missing values, post-processing and data storage errors. As well as raising awareness of pitfalls, recommendations are provided for uncovering lapses in data quality after the information has been gathered. It is noted that error detection and attribution are more problematic for very large data sets, where observation networks are automated, or when various information sources have been combined. In these cases, more holistic indicators of data integrity are needed that reflect the overall information life-cycle and application(s) of the hydrological data

A cyclone climatology of the British-Irish Isles 1871–2012

The British-Irish Isles (BI) lie beneath the North Atlantic storm track year-round and thus are impacted by the passage of extra-tropical cyclones. Given recent extreme storminess and projections of enhanced winter cyclone activity for this region, there is much interest in assessing the extent to which the cyclone climate of the region may be changing. We address this by assessing a 142-year (1871–2012) record of cyclone frequency, intensity and ‘storminess’ derived from the 20th Century Reanalysis V2 (20CR) dataset. We also use this long-term record to examine associations between cyclone activity and regional hydroclimate. Our results confirm the importance of cyclone frequency in driving seasonal precipitation totals which we find to be greatest during summer months. Cyclone frequency and storminess are characterized by pronounced interannual and multi-decadal variability which are strongly coupled to atmospheric blocking in the Euro-Atlantic region, but we detect no evidence of an increasing trend. We observe an upward trend in cyclone intensity for the BI region, which is strongest in winter and consistent with model projections, but promote caution interpreting this given the changing data quality in the 20CR over time. Nonetheless, we assert that long-term reconstruction is helpful for contextualizing recent storminess and for identifying emerging changes in regional hydroclimate linked to cyclones

Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods

Understanding hydrological model predictive capabilities under contrasting climate conditions enables more robust decision making. Using Differential Split Sample Testing (DSST), we analyze the performance of six hydrological models for 37 Irish catchments under climate conditions unlike those used for model training. Additionally, we consider four ensemble averaging techniques when examining interperiod transferability. DSST is conducted using 2/3 year noncontinuous blocks of (i) the wettest/driest years on record based on precipitation totals and (ii) years with a more/less pronounced seasonal precipitation regime. Model transferability between contrasting regimes was found to vary depending on the testing scenario, catchment, and evaluation criteria considered. As expected, the ensemble average outperformed most individual ensemble members. However, averaging techniques differed considerably in the number of times they surpassed the best individual model member. Bayesian Model Averaging (BMA) and the Granger-Ramanathan Averaging (GRA) method were found to outperform the simple arithmetic mean (SAM) and Akaike Information Criteria Averaging (AICA). Here GRA performed better than the best individual model in 51%–86% of cases (according to the Nash-Sutcliffe criterion). When assessing model predictive skill under climate change conditions we recommend (i) setting up DSST to select the best available analogues of expected annual mean and seasonal climate conditions; (ii) applying multiple performance criteria; (iii) testing transferability using a diverse set of catchments; and (iv) using a multimodel ensemble in conjunction with an appropriate averaging technique. Given the computational efficiency and performance of GRA relative to BMA, the former is recommended as the preferred ensemble averaging technique for climate assessment

An evaluation of persistent meteorological drought using a homogeneous Island of Ireland precipitation network

This paper investigates the spatial and temporal properties of persistent meteorological droughts using the homogeneous Island of Ireland Precipitation (IIP) network. Relative to a 1961–1990 baseline period it is shown that the longest observed run of below average precipitation since the 1850s lasted up to 5 years (10 half-year seasons) at sites in southeast and east Ireland, or 3 years across the network as a whole. Dry spell and wet spell length distributions were represented by a first-order Markov model which yields realistic runs of below average rainfall for individual sites and IIP series. This model shows that there is relatively high likelihood (p=0.125) of a 5-year dry spell at Dublin, and that near unbroken dry runs of 10 years or more are conceivable. We suggest that the IIP network and attendant rainfall deficit modelling provide credible data for stress testing water supply and drought plans under extreme conditions

Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk

This study develops a coherent framework to detect those catchment types associated with a high risk of maladaptation to future flood risk. Using the “scenario‐neutral” approach to impact assessment the sensitivity of Irish catchments to fluvial flooding is examined in the context of national climate change allowances. A predefined sensitivity domain is used to quantify flood responses to +2 °C meanannualtemperaturewithincrementalchangesintheseasonalityandmeanoftheannualprecipitation cycle. The magnitude of the 20‐year flood is simulated at each increment using two rainfall‐runoff models (GR4J, NAM), then concatenated as response surfaces for 35 sample catchments. A typology of catchment sensitivityisdevelopedusingclusteringanddiscriminantanalysisofphysicalattributes.Thesameattributes areusedtoclassify215ungauged/data‐sparsecatchments.Toaddresspossibleredundancies,theexposureof different catchment types to projected climate is established using an objectively selected subset of the Coupled Model Intercomparison Project Phase 5 ensemble. Hydrological model uncertainty is shown to significantly influence sensitivity and have a greater effect than ensemble bias. A national flood risk allowance of 20%, considering all 215 catchments is shown to afford protection against ~48% to 98% of the uncertainty in the Coupled Model Intercomparison Project Phase 5 subset (Representative Concentration Pathway 8.5; 2070–2099), irrespective of hydrological model and catchment type. However, results indicate that assuming a standard national or regional allowance could lead to local over/under adaptation. Herein, catchments with relatively less storage are sensitive to seasonal amplification in the annual cycle of precipitation and warrant special attention

A 305-year continuous monthly rainfall series for the island of Ireland (1711–2016)

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 (tree-ring) 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 multi-centennial 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