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Drought events are influenced by a combination of both climatic and local catchment characteristics. In Great Britain the North Atlantic Oscillation (NAO) has long been recognised as the leading mode of climate variability, and studies have also noted the role of the East Atlantic Pattern (EA) as a secondary mode. This study aimed to develop an understanding of the combined influence of the NAO and EA on rainfall distribution and magnitude and the variable nature of meteorological to hydrological drought propagation. Initially, this study explores correlations between teleconnection indices and standardised precipitation and streamflow indices for 291 catchments across Great Britain, before focusing on nine case study catchments for further analysis. For each case study catchment, we use quantile regression and an analysis of drought frequency to explore the combined influence of the NAO and EA on drought conditions.Through a convergence of evidence from these analyses we make three observations. Firstly, in the winter months both the NAO and EA exert an influence on drought conditions, however there is spatial variability in the relative influence of the NAO and EA; the NAO has a stronger influence in the north-west, whilst the EA has a stronger influence in the southern and central regions. Secondly, in the summer months, less distinctive spatial differences were found, with higher probability of drought conditions under NAO+ phases, which however can be enhanced or moderated by the EA. Finally, as a result of catchment characteristics there is spatio-temporal variability in the propagation of meteorological to hydrological drought. Our findings suggest that by considering the NAO and EA in combination, we can better describe climate and drought variability. We conclude by noting the potential implications our study has on the role of monthly teleconnection forecasts in water management decision making in Great Britain, and acknowledge the current limitations associated with incorporating such understanding.

The North Atlantic Oscillation (NAO) is often cited as the primary atmospheric-oceanic circulation or teleconnection influencing regional climate in Great Britain. As our ability to predict the NAO several months in advance improves, it is important that we also continue to develop our spatial and temporal understanding of the rainfall signatures which the circulation produces.We present a novel application of spatial statistics to explore variability in monthly NAO rainfall signatures using a 5km gridded monthly Standardised Precipitation Index (SPI) dataset. We first use the Getis-Ord Gi* statistic to map spatially significant hot and cold spots (clusters of high/wet and low/dry SPI values) in average monthly rainfall signatures under NAO Positive and Negative conditions over the period 1900-2015. We then look across the record and explore the temporal variability in these signatures, in other words how often a location is in a significant spatial hot/cold spot (high/low SPI) at a monthly scale under NAO Positive/Negative conditions.The two phases of the NAO are typically more distinctive in the winter months, with stronger and more variable NAO Index values. The average monthly SPI analysis reveals a north-west/south-east ‘spatial divide’ in rainfall response. NAO Positive phases result in a southerly North Atlantic Jet Stream bringing warm and wet conditions from the tropics, increasing rainfall particularly in the north-western regions. However, under NAO Negative phases which result in a northerly Jet Stream, much drier conditions in the north-west prevail. Meanwhile in the south-eastern regions under both NAO phases a weaker and opposite wet/dry signal is observed. This north-west/south-east ‘spatial divide’ is marked by the location of spatially extensive hot/cold spots. The Getis-Ord Gi* result identifies that the spatial pattern we detect in average winter rainfall is statistically significant. Looking across the record, this NW/SE opposing response appears to have a relatively high degree of spatio-temporal consistency. This suggests that there is a high probability that NAO Positive and Negative phases will result in this NW/SE statistically significant spatial pattern.Even though the phases of the NAO in the summer months are less distinctive they still produce rainfall responses which are evident in the monthly average SPI. However, the spatiality in wet/dry conditions is more homogenous across the country. In other words the ‘spatial divide’ observed in winter is diluted in summer. As a result, the occurrence of significant hot/cold spots is more variable in space and time.Our analysis demonstrates a novel application of the Getis-Ord Gi* statistic which allows for spatially significant patterns in the monthly SPI data to be mapped for each NAO phase. In winter months particularly, this analysis reveals statistically significant opposing rainfall responses, which appear to have long-term spatio-temporal consistency. This is important because as winter NAO forecasting skill improves, the findings of our research enable a more spatially reliable estimate of the likely impacts of NAO-influenced rainfall distribution.

The resolution of satellite of satellite-derived soil moisture data products has matured, notably in recent years due to the Soil Moisture Active Passive mission (SMAP) launched in 2015. Whilst spatial resolutions still fall short of those suitable for field-scale monitoring, there are several ‘value-added’ RS soil moisture products available at the regional (e.g. SMAP: 36km) to meso-scale (e.g. SMAP: 9km) resolution. Although the intended 3km scale SMAP product did not materialise due to the failure of the L-Band radar, a potential substitute product has recently become available (Das et al. 2019). The SMAP-Sentinel1 product combines data from SMAP and C-Band Sentinel 1A/B SAR data to synthesise global soil moisture at a 3km and 1km resolution (~6 day revisit for Europe).Evaluation of these products against ground-based measurements in the USA and elsewhere is encouraging, but only preliminary evaluation has been undertaken in the United Kingdom. Evaluation is always challenging because (i) rather than a direct measurement, satellite estimates are based on other measured properties (e.g. brightness temperature) with soil moisture algorithmically inferred, (ii) ground-based measurements are highly localised in comparison with the measurement averaged over the satellites much larger pixel resolution, and (iii) satellite sensors typically estimate only surface soil moisture (0-5cm).The COSMOS-UK network, under development since 2013, provides high resolution soil moisture data at 51 sites in the UK, corresponding to a variety of climatic, soil and land cover settings. Sites typically contain soil moisture probes at a variety of depths (including 10cm) as well as a cosmic ray sensor. The latter integrates soil moisture over an area of ~12ha, and while not matching the spatial scale or soil depth of satellite measurements, it does avoid some of the field-scale heterogeneity issues associated with point-based measurements.The 9km SMAP L3 product performs well against 10cm soil probe measurements at most sites (>70% at ubRMSE

The North Atlantic Oscillation (NAO) is one of the primary atmospheric circulations which influence weather patterns in Great Britain. Its two phases (either positive or negative depending on differences in sea level pressure) result in characteristic precipitation patterns, the effects of which cascade down to signatures in streamflow. However, in relation to streamflow response to the NAO, these studies have been spatio-temporally limited as they have been undertaken using a small number of measurement sites with relatively short records.The release of new historic datasets from the UK Centre for Ecology and Hydrology (CEH) provides a new opportunity to undertake a broad spatio-temporal analysis of the relationship between NAO and streamflow. This research used reconstructed daily flows for 291 catchments and the associated Standardised Streamflow Index (SSI) to explore the relationship between the North Atlantic Oscillation Index (NAOI) for the period January 1900-November 2015. Spearman correlations were calculated at monthly intervals between the NAOI and SSI (with a 1-month accumulation period), and the historic flows dataset was used to explore the variability in flows across the catchments under NAO+ and NAO- phases.This analysis revealed distinct wet and dry spatio-temporal signatures in streamflow. The winter months are characterised by a north-west and south-east divide in this relationship; catchments in the northern and western regions show strong positive correlations between the NAOI and SSI and NAO+ is associated with higher than normal flows in many north-western catchments, and vice versa under NAO-. While catchments in the south-eastern and central regions are negatively correlated and therefore show and opposite wet-dry response. However, during the summer months, while there are some wet-dry signatures under NAO positive/negative phases - the reverse to that seen in winter, almost all catchments show weak NAOI-SSI negative correlation values. Finally, we compare the wet-dry responses to the NAO observed in streamflow to NAO-precipitation patterns, measured via correlations between the NAOI and Standardised Precipitation Index with a 1-month accumulation period over the same study period. The two sets of correlations (NAO-SPI and NAO-SSI) were analysed for spatio-temporal similarity through a Geographically Weighted Regression (GWR) analysis and a space-time clustering analysis. This revealed that in winter, as described above, the correlations with SPI and SSI generally behave similarly during the winter months – i.e. the wet-dry signatures in rainfall cascade down and are identifiable in streamflow patterns. In the summer months the NAOI-SPI correlations for the majority of catchments are negative. In the NAOI-SSI correlations, the summer values, while still negative, are notably weaker. The catchments with the weakest NAOI-SSI correlations are those generally in the central/southern region. These catchments have very slow response times due to their characteristics which may moderate the NAO wet/dry rainfall deviation.