The GloSAT project is developing a new observational analysis of global air temperature change over land and ocean since the late 18th century. A new global analysis processing system has been developed that uses a computationally efficient spatial statistical method to estimate air temperature anomaly fields from historical observations. This will be the first presentation of this analysis approach. This method, based on Gaussian Markov Random Fields, jointly estimates temperature anomaly fields over land and ocean based on weather station and ship-based air temperature observations. The increased computational efficiency of the approach compared to conventional kriging-based estimates allows for increased spatial resolution in the analysis. Observational uncertainties are represented within the analysis framework to propagate uncertainty into the output ensemble data set. This accounts for errors arising from uncorrelated effects and structured errors such as residual biases in observations from an individual weather station or ship after correction. Observational error models have been co-developed with project partners providing the input land and marine data products. Initial results from the application of the analysis system to GloSAT air temperature observation data will be demonstrated.

<p>We present a new data set of air temperature change across land and ocean extending back to the late-18<sup>th</sup> century. This new data set uses marine air temperature observations rather than the sea surface temperature measurements typically used by pre-existing data sets. This allows the new data set to extend further into the past than existing instrumental temperature records, which typically have start dates in the mid-to-late 19<sup>th</sup> century. The new data set brings together advances in understanding of measurement biases affecting all-day marine air temperature observations with a new assessment of the effects of non-standard thermometer enclosures used at land meteorological stations in the early instrumental record. A further innovation is the use of kriging to obtain localised temperature estimates that allow land air temperature records to be converted into anomalies even for stations without observations during the baseline period. Global and hemispheric series show close agreement with those based on sea-surface temperature for much of the overlapping period of their records, some of the interesting differences will be presented. This data set has been developed under the GloSAT project (https://www.glosat.org/).</p>

Marine air temperatures recorded on ships during the daytime are known to be biased warm on average due to energy storage by the superstructure of the vessels. This makes unadjusted daytime observations unsuitable for many applications including for the monitoring of long-term temperature change over the oceans. In this paper a physics -based approach is used to estimate this heating bias in ship observations from ICOADS. Under this approach, empirically determined coefficients represent the energy transfer terms of a heat budget model that quantifies the heating bias and is applied as a function of cloud cover and the relative wind speed over individual ships. The coefficients for each ship are derived from the anomalous diurnal heating relative to nighttime air temperature. Model coefficients, cloud cover, and relative wind speed are then used to estimate the heating bias ship by ship and generate nighttime-equivalent time series. A variety of methodological approaches were tested. Application of this method enables the inclusion of some daytime observations in climate records based on marine air temperatures, allowing an earlier start date and giving an increase in spatial coverage compared to existing records that exclude daytime observations.SIGNIFICANCE STATEMENT: Currently, the longest available record of air temperature over the oceans starts in 1880. We present an approach that enables observations of air temperatures over the oceans to be used in the creation of long-term climate records that are presently excluded. We do this by estimating the biases inherent in daytime tem-perature reports from ships, and adjust for these biases by implementing a numerical heat-budget model. The adjust-ment can be applied to the variety of ship types present in observational archives. The resulting adjusted temperatures can be used to create a more spatially complete record over the oceans, that extends further back in time, potentially into the late eighteenth century.

Based on newly-available meteorological reanalysis, we compile and present extended seasonal series of the North Atlantic Oscillation (NAO) and Greenland Blocking indices spanning 1800–2020, which we analyse for evidence of significant trends. This represents a major backward extension of the previously available instrumental-/reanalysis-based Azores–Iceland and principal component-based NAO indices, and allows us to evaluate the potential effect of natural climate perturbations, especially the 1809 and 1815 major volcanic eruptions and ~1790s–1830 Dalton solar minimum, on North Atlantic atmospheric circulation. We find that winters 1809/10 and 1816/17 mark positive NAO peaks, relative to several years before and afterwards, which is in accordance with the theory of volcanic forcing of climate. However, there is little evidence of a summer NAO volcanic signature. Overall, based on the significantly longer new reanalysis time series, the new series presented here corroborate and extend our previous results of: (1) a significantly more variable year-to-year NAO with a recent exceptional clustering of extreme events since 2000 for winter; (2) a significant increasing trend in blocking over Greenland in summer. These trends have major repercussions for the probability of the occurrence of extreme weather events over northwest Europe and for the sensitivity and response of the Greenland Ice Sheet to global warming, especially if they continue as an integral part of anthropogenic climate change.

Caption: Lightning discharges appear in various colours depending on the scatter of light inside the thundercloud and in the atmosphere.The intracloud lightning discharges in the centre of the thundercloud appear to be white with a bluish tint, and the cloud-to-ground discharge below appears to be orange.The right hand side of the thundercloud exhibits a green tint that is attributed to the unique composition of hydrometeors inside the thundercloud.The photo was taken in the late evening of 10 September 2013, near Tarragona in northeastern Spain.

Accurate, long-term time series of near-surface air temperature (AT) are the fundamental datasets on which the magnitude of anthropogenic climate change is scientifically and societally addressed. Across the ocean, these (near-surface) climate records use Sea Surface Temperature (SST) instead of Marine Air Temperature (MAT) and blend the SST and AT over land to create datasets. MAT has often been overlooked as a data choice as daytime MAT observations from ships are known to contain warm biases due to the storage of accumulated solar energy. Two recent MAT datasets, CLASSnmat (1881 – 2019) and UAHNMAT (1900 – 2018), both use night-time MAT observations only. Daytime MAT observations in the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) account for over half of the MAT observations in ICOADS, and this proportion increases further back in time (i.e. pre-1850s). If long-term MAT records over the ocean are to be extended, the use of daytime MAT is vital. To adjust for the daytime MAT heating bias, and apply it to ICOADS, we present the application of a physics-based model, which accounts for the accumulated energy storage throughout the day. As the ‘true’ diurnal cycle of MAT over the ocean has not been, to-date, adequately quantified, our approach also removes the diurnal cycle from ICOADS observations and generates a night-time equivalent MAT for all observations. We fit this model to MAT observations from groups of ships in ICOADS that share similar heating biases and metadata characteristics. This enables us to use the empirically derived coefficients (representing the physical energy transfer terms of the heating model) obtained from the fit for use in removal of the heating bias and diurnal cycle from ship-based MAT observations throughout ICOADS which share similar characteristics (i.e. we can remove the diurnal cycle from a ship which only reports once daily at noon). This adjustment will create an MAT record of night-time-equivalent temperatures that will enable an extension of the marine surface AT record back into the 18th century.

Using the criterion of one Bergeron (24 hPa change over 24 h at 60°), we present the creation of a Eulerian explosive cyclogenesis climatology using hourly-temporal resolution data from the European Centre for Medium Range Weather Forecasting’s ERA5 reanalysis (1979-2018). This approach differs to the typically used Lagrangian methodologies adopted by many studies. The climatology created by this approach results in similar patterns to previous studies. Assessments on the dataset are undertaken to analyse the influence of seasonality, teleconnections, climate change and individual events (the method picks up tropical cyclones as well as mid-latitude storms). The location experiencing the most consistent explosive cyclongenesis conditions (15% of the time during the Northern Hemisphere winter) is to the east of the Avalon Peninsula, Newfoundland. The preferred location of explosive cyclogenesis is shown to change in relation to patterns such as the El Niño Southern Oscillation and North Atlantic Oscillation. Potential applications of the dataset are suggested.

With the polar regions opening up to more marine activities but iceberg numbers more likely to increase than decline as a result of global warming, the risk from icebergs to shipping and offshore facilities is increasing. The NW Atlantic iceberg hazard has been well monitored by the International Ice Patrol for a century, but many other polar regions have little detailed climatological knowledge of the iceberg risk. Here, we develop a modelling approach to assessing iceberg hazard. This uses the region of the Falklands Plateau and its shipping routes for a case study, but the approach has general geographical applicability and can be used for assessing iceberg hazard for routes or fixed locations. The iceberg risk for a number of locations selected from the main shipping routes in the SW Atlantic is assessed by using an iceberg model, forced by the output from a high-resolution ocean model. The iceberg model was seeded with icebergs around the edge of the modelled region using a number of scenarios for the seeding distribution, based on a combination of idealised, modelled and observed iceberg fluxes from the Southern Ocean. This enabled us to determine measures of iceberg risk linked to a mix of starting location and the likelihood of icebergs being encountered in such a position. For our study area, the main area of iceberg risk is linked to the East Falklands Current, but small, yet nonzero, risk covers much of the east and north of the region.

ABSTRACTThe Arctic marine environment is undergoing a transition from thick multi-year to first-year sea-ice cover with coincident lengthening of the melt season. Such changes are evident in the Baffin Bay-Davis Strait-Labrador Sea (BDL) region where melt onset has occurred ~8 days decade−1 earlier from 1979 to 2015. A series of anomalously early events has occurred since the mid-1990s, overlapping a period of increased upper-air ridging across Greenland and the northwestern North Atlantic. We investigate an extreme early melt event observed in spring 2013. (~6σ below the 1981–2010 melt climatology), with respect to preceding sub-seasonal mid-tropospheric circulation conditions as described by a daily Greenland Blocking Index (GBI). The 40-days prior to the 2013 BDL melt onset are characterized by a persistent, strong 500 hPa anticyclone over the region (GBI >+1 on >75% of days). This circulation pattern advected warm air from northeastern Canada and the northwestern Atlantic poleward onto the thin, first-year sea ice and caused melt ~50 days earlier than normal. The episodic increase in the ridging atmospheric pattern near western Greenland as in 2013, exemplified by large positive GBI values, is an important recent process impacting the atmospheric circulation over a North Atlantic cryosphere undergoing accelerated regional climate change.

We present a homogenized Greenland blocking index (GBI) daily record from 1851 to 2015, therefore significantly extending our previously published monthly/seasonal GBI analysis. This new time series is analysed for evidence of changes in extreme events, and we investigate the underlying thermodynamic and dynamic precursors. We compare occurrences and changes in extreme events between our GBI record and a recently published, temporally similar daily North Atlantic Oscillation (NAO) series, and use this comparison to test dynamic meteorology hypotheses relating negative NAO to Greenland blocking. We also compare daily GBI changes and extreme events with long‐running indices of England and Wales temperature and precipitation, to assess potential downstream effects of Greenland blocking on UK extreme weather events and climate change. In this extended analysis we show that there have been sustained periods of positive GBI during 1870–1900 and from the late 1990s to present. A clustering of extreme high GBI events since 2000 is not consistently reflected by a similar grouping of extreme low NAO events. Case studies of North Atlantic atmospheric circulation changes linked with extreme high and low daily GBI episodes are used to shed light on potential linkages between Greenland blocking and jet‐stream changes. Particularly noteworthy is a clustering of extreme high GBI events during mid‐October in 4 out of 5 years during 2002–2006, which we investigate from both cryospheric and dynamic meteorology perspectives. Supporting evidence suggests that these autumn extreme GBI episodes may have been influenced by regional sea‐ice anomalies off west Greenland but were probably largely forced by increases in Rossby‐wave train activity originating from the tropical Pacific. However, more generally our results indicate that high GBI winter anomalies are co‐located with sea‐ice anomalies, while there seems to be minimal influence of sea‐ice anomalies on the recent significant increase in summer GBI.

Abstract Many variations in the weather in the European and North Atlantic regions are linked with changes in the North Atlantic Oscillation (NAO). The NAO is measured using a south-minus-north index of atmospheric surface pressure variation across the North Atlantic and is closely connected with changes in the North Atlantic atmospheric polar jet stream and wider changes in atmospheric circulation. The physical, human, and biological impacts of NAO changes extend well beyond weather and climate, with major economic, social, and environmental effects. The NAO index based on barometric pressure records now extends as far back as 1850, based on recent work. Although there are few significant overall trends in monthly or seasonal NAO (i.e., for the whole record), there are many shorter-term multidecadal variations. A prominent increase in the NAO between the 1960s and 1990s was widely noted in previous work and was thought to be related to human-induced greenhouse gas forcing. However, since then this trend has reversed, with a significant decrease in the summer NAO since the 1990s and a striking increase in variability of the winter—especially December—NAO that has resulted in four of the six highest and two of the five lowest NAO Decembers occurring during 2004–2015 in the 116-year record, with accompanying more variable year-to-year winter weather conditions over the United Kingdom. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI; equals high pressure over Greenland) in summer and a significantly more variable GBI in December. Such NAO and related jet stream and blocking changes are not generally present in the current generation of global climate models, although recent process studies offer insights into their possible causes. Several plausible climate forcings and feedbacks, including changes in the sun’s energy output and the Arctic amplification of global warming with accompanying reductions in sea ice, may help explain the recent NAO changes. Recent research also suggests significant skill in being able to make seasonal NAO predictions and therefore long-range weather forecasts for up to several months ahead for northwest Europe. However, global climate models remain unclear on longer-term NAO predictions for the remainder of the 21st century.

A 133-year length (1883–2015) daily climate record from Sheffield, England (53.38°N, 1.49°W) is analysed. Across the entire length of the record, there are significant warming trends annually and for all seasons, whereas precipitation shows a significant annual increase but the seasonal trends, whilst all positive, are not significant. Trends in extreme indices mirror the mean long-term warming and wetting signal. Record hot and cold daily temperatures and precipitation amounts are associated with summer anticyclonic conditions, an anomalous easterly winter jet stream and summer cyclonic activity, respectively. Whilst there are large uncertainties surrounding the calculation of return periods for the daily maximum, minimum and precipitation records from a single record, our best estimates suggest that in the current climate (2015), the existing records have return periods of 38, 529 and 252 years, respectively. The influence of several climate indices on mean and extreme indices are considered on seasonal scales, with the North Atlantic Oscillation displaying the strongest relationship. Future mean maximum temperature and precipitation alongside extreme indices representing the warmest and wettest day of the year are analysed from two downscaled climate model output archives under analysis periods of a 1.5 and 2 degree warmer world and the 2080–2099 end of 21st century period. For this mid-latitude location, there is minimal difference in model projections between a 1.5 and 2 degree world, but a significant difference between the 1.5/2 degree world and the end of century 2080–2099 period under the most severe climate warming scenarios.

ABSTRACTWithin the scope of the two major international projects of long‐term reanalysis for the 20th century coordinated by the National Oceanic and Atmospheric Administration and European Centre for Medium‐Range Weather Forecasts, the Instituto Dom Luiz from the University of Lisbon has digitized a large number of long‐term daily and monthly climate records from stations in Portugal and former Portuguese colonies. We have recently finished the digitization of precipitation values from Ponta Delgada (capital of the Azores Archipelago), obtaining an almost complete daily precipitation series, with the exception of some years (1864–1872; 1878–1879; 1888–1905; 1931; 1936; and 1938) for which only monthly values are available. At daily resolution, we have used a comprehensive assessment on different characteristics of rain spells (consecutive days with rainfall accumulation). The distribution of precipitation presents an evident seasonal pattern and reveals large inter‐annual and intra‐annual variability, increasing considerably in the last 3 decades. The frequency of dry years decreases almost by half between the first and the second part of the record, whereas wet years increase up to three times. This is mainly due to more intense events that are reflected by higher rain‐spell yields (amount of precipitation) and rain‐spell intensity (amount of precipitation per day) values. Most of the extreme precipitation events occurred during the last 2 decades, and they generally correspond to dates with cyclonic conditions over the North Atlantic. We have also looked into the influence of large‐scale modes of climate variability on the precipitation regime of the Azores Archipelago. As expected, theNorth Atlantic Oscillation (NAO) has a major impact on the precipitation regime of Ponta Delgada both in winter and summer. However, our results show a non‐stationary NAO influence and the impact of other large‐scale modes (including the Atlantic Multidecadal Oscillation and El Niño‐Southern Oscillation) increases when this influence becomes weaker.

ABSTRACTWe present an extended monthly and seasonal Greenland Blocking Index (GBI) from January 1851 to December 2015, which more than doubles the length of the existing published GBI series. We achieve this by homogenizing the Twentieth Century Reanalysis version 2c‐based GBI and splicing it with the NCEP/NCAR Reanalysis‐based GBI. For the whole time period, there are significant decreases in GBI in autumn, October and November, and no significant monthly, seasonal or annual increases. More recently, since 1981 there are significant GBI increases in all seasons and annually, with the strongest monthly increases in July and August. A recent clustering of high GBI values is evident in summer, when 7 of the top 11 values in the last 165 years – including the two latest years 2014 and 2015 – occurred since 2007. Also, 2010 is the highest GBI year in the annual, spring, winter and December series but 2011 is the record low GBI value in the spring and April series. Moreover, since 1851 there have been significant increases in GBI variability in May and especially December. December has also shown a significant clustering of extreme high and low GBI values since 2001, mirroring a similar, recently identified phenomenon in the December North Atlantic Oscillation index, suggesting a related driving mechanism. We discuss changes in hemispheric circulation that are associated with high compared with low GBI conditions. Our GBI time series should be useful for climatologists and other scientists interested in aspects and impacts of Arctic variability and change.

We present the construction of a continuous, daily (09:00 UTC), station‐based (Azores–Iceland) North Atlantic Oscillation (NAO) Index back to 1871 which is extended back to 1850 with additional daily mean data. The constructed index more than doubles the length of previously existing, widely available, daily NAO time series. The index is created using entirely observational sea‐level pressure (SLP) data from Iceland and 73.5% of observational SLP data from the Azores – the remainder being filled in via reanalysis (Twentieth Century Reanalysis Project and European Mean Sea Level Pressure) SLP data. Icelandic data are taken from the Southwest Iceland pressure series. We construct and document a new Ponta Delgada SLP time series based on recently digitized and newly available data that extend back to 1872. The Ponta Delgada time series is created by splicing together several fractured records (from Ponta Delgada, Lajes, and Santa Maria) and filling in the major gaps (pre‐1872, 1888–1905, and 1940–1941) and occasional days (145) with reanalysis data. Further homogeneity corrections are applied to the Azores record, and the daily (09:00 UTC) NAO index is then calculated. The resulting index, with its extended temporal length and daily resolution, is the first reconstruction of daily NAO back into the 19th Century and therefore is useful for researchers across multiple disciplines.

Recent changes are found in the means and variability of the North Atlantic Oscillation (NAO) index. There has been a sustained significant recent decrease in the summer NAO since the 1990s and, at the same time, a striking increase in variability of the winter-especially December-NAO that resulted in three of five (two of five) record high (record low) NAO Decembers occurring during 2004-2013 in the 115-year record. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI, high pressure over Greenland) in summer and a more variable GBI in December. The enhanced early winter NAO variability originates mainly at the southern node of the NAO but is also related to the more variable GBI in December. Transition seasons (spring and autumn) have remained relatively unchanged over the last 30years. These results are corroborated using several NAO indices. The Arctic Oscillation (AO) index, although strongly correlated with the NAO, does not show the recent sustained significant summer decrease, but it does show enhanced early winter variability. These recent observed changes are not present in the current generation of global climate models, although the latest process studies do offer insight into their causes. We invoke several plausible climate forcings and feedbacks to explain the recent NAO changes.

New monthly, long-running, continuous surface air temperature records for four island chains throughout the Macaronesian biogeographical zone in the North Atlantic Ocean are presented. The records run from 1865 for the Azores and Madeira, 1885 for the Canary Islands and 1895 for Cape Verde. Recent (1981-2010) warming across these islands is significant in summer (JJA) for the Canary Islands, Cape Verde and Madeira, ranging from 0.40 to 0.46 degrees C per decade. Annually, the temperature trends across this period range from 0.30 to 0.38 degrees C per decade across all four island chains (significant for all but the Canary Islands), which exceed the station-based, average global temperature rise by up to 0.10 degrees C per decade. Precipitation records from multiple islands across Macaronesia are also presented in addition to sea-level pressure records from the Azores and Cape Verde. Cape Verde wet season (ASO) precipitation is found to have significantly increased at two of our three sites from 1981 to 2010. The Azores, Canary Islands and Madeira precipitation trends display no significant changes, although the three Azores stations display a recent positive tendency. The extended Azores pressure record allows us to construct an entirely station-based Azores-Iceland North Atlantic Oscillation index (NAOI) from 1865 to 2012 and extend the daily station-based index back to 1944, further than the longest previous daily NAOI by 6 years. In addition, we use the sea-level pressure difference between the Azores and Cape Verde to create a novel method of characterizing trade wind strength across Macaronesia, the Trade Wind index (TWI), which points towards a recent, statistically significant increase (since 1973) throughout the region. Links between the winter and summer NAOI, TWI and Macaronesian temperature and precipitation are explored, as are the differences in warming trends between Macaronesia and analogous subtropical island chains, most of which are found to be warming at slower rates than the Macaronesia stations. (c) 2013 Royal Meteorological Society

Seasonal coastal upwelling was analyzed along the NW African coastline (11–35°N) from 1981 to 2012. Upwelling magnitudes are calculated by wind speed indices, sea-surface temperature indices and inferred from meteorological station, sea-surface height and vertical water column transport data. A permanent annual upwelling regime is documented across 21–35°N and a seasonal regime across 12–19°N, in accordance with the climatology of previous studies. Upwelling regions were split into three zones: (1) the Mauritania–Senegalese upwelling zone (12–19°N), (2) the strong permanent annual upwelling zone (21–26°N) and (3) the weak permanent upwelling zone (26–35°N). We find compelling evidence in our various indices for the Bakun upwelling intensification hypothesis due to a significant coastal summer wind speed increase, resulting in an increase in upwelling-favorable wind speeds north of 20°N and an increase in downwelling-favorable winds south of 20°N. The North Atlantic Oscillation plays a leading role in modifying interannual variability during the other seasons (autumn–spring), with its influence dominating in winter. The East Atlantic pattern shows a strong correlation with upwelling during spring, while El Niño Southern Oscillation and Atlantic Multi-decadal Oscillation teleconnections were not found. A disagreement between observationally-based wind speed products and reanalysis-derived data is explored. A modification to the Bakun upwelling intensification hypothesis for NW Africa is presented, which accounts for the latitudinal divide in summer wind regimes.