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Global surface air temperature increased by ca. 0.5 °C from the 1900s to the mid-1940s, also known as Early 20th Century Warming (ETCW). However, the ETCW started from a particularly cold phase, peaking in 1908–1911. The cold phase was global but more pronounced in the Southern Hemisphere than in the Northern Hemisphere and most pronounced in the Southern Ocean, raising the question of whether uncertainties in the data might play a role. Here we analyse this period based on reanalysis data and reconstructions, complemented with newly digitised ship data from 1903–1916, as well as land observations. The cooling is seen consistently in different data sets, though with some differences. Results suggest that the cooling was related to a La-Niña-like pattern in the Pacific, a cold tropical and subtropical South Atlantic, a cold extratropical South Pacific, and cool southern midlatitude land areas. The Southern Annular Mode was positive, with a strengthened Amundsen–Bellingshausen seas low, although the spread of the data products is considerable. All results point to a real climatic phenomenon as the cause of this anomaly and not a data artefact. Atmospheric model simulations are able to reproduce temperature and pressure patterns, consistent with a real and perhaps ocean-forced signal. Together with two volcanic eruptions just before and after the 1908–1911 period, the early 1900s provided a cold start into the ETCW. [ABSTRACT FROM AUTHOR]

Central Europe is among the regions with the largest availability of pre-industrial meteorological records. In the Alps, however, such records are relatively rare, especially in the southern slope. We recently found and digitized two new pressure and temperature series for the Alpine cities of Rovereto (1800--1839) and Bolzano/Bozen (1842--1849) covering together the FIrst half of the 19th century, a period characterized by large climate variability and important extreme events. The meteorological record of Rovereto, in particular, is the oldest available for the southeastern Alps. We used the shorter record of Bolzano/Bozen as a testbed for different digitization methods, namely citizen science and machine-learning based Optical Character Recognition. The data are converted to modern units, quality controlled, and homogenized. We also provide daily and monthly means together with an estimation of their uncertainty. [ABSTRACT FROM AUTHOR]

This study explores the teleconnection between the boreal summer precipitation for the central highlands of Eritrea, with respect to global sea‐surface temperature (SST) and atmospheric parameters (winds, pressure, humidity, and vertical velocity) as indirect indicators of atmospheric circulation. The central‐highland summer (Jul–Aug) precipitation (1914–2015) is significantly negatively correlated with the Atlantic Niño (ATL3) index. Similarly, with a 2‐month (May) or 1‐month lead (Jun), SSTs over the equatorial Atlantic (Gulf of Guinea) are inversely correlated with the central‐highland summer precipitation. Moreover, the regional atmospheric circulation reveals that the boreal summer precipitation series has a significant positive correlation with the westerly wind over the Gulf of Guinea at 700 hPa and a negative correlation with the Tropical Easterly Jet (TEJ) at 200 hPa. Overall, these findings depict the African Walker circulation cell, whereby a low‐level westerly wind flows from the Gulf of Guinea across central Africa, coupled with a rising branch over north‐eastern Africa, and reverses as an easterly wind at a higher level. These significant correlations between Atlantic Ocean SST as the precipitation‐driving factor enabled the development and validation of an area‐specific seasonal precipitation prediction model, as precipitation in this region is temporally and spatially highly variable. [ABSTRACT FROM AUTHOR]

Day-to-day variations in surface air temperature affect society in many ways, but daily surface air temperature measurements are not available everywhere. Therefore, a global daily picture cannot be achieved with measurements made in situ alone and needs to incorporate estimates from satellite retrievals. This article presents the science developed in the EU Horizon 2020-funded EUSTACE project (2015-19, www.eustaceproject.org) to produce global and European multidecadal ensembles of daily analyses of surface air temperature complementary to those from dynamical reanalyses, integrating different ground-based and satellite-borne data types. Relationships between surface air temperature measurements and satellite-based estimates of surface skin temperature over all surfaces of Earth (land, ocean, ice, and lakes) are quantified. Information contained in the satellite retrievals then helps to estimate air temperature and create global fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place; this needs efficient statistical analysis methods to cope with the considerable data volumes. Daily fields are presented as ensembles to enable propagation of uncertainties through applications. Estimated temperatures and their uncertainties are evaluated against independent measurements and other surface temperature datasets. Achievements in the EUSTACE project have also included fundamental preparatory work useful to others, for example, gathering user requirements, identifying inhomogeneities in daily surface air temperature measurement series from weather stations, carefully quantifying uncertainties in satellite skin and air temperature estimates, exploring the interaction between air temperature and lakes, developing statistical models relevant to non-Gaussian variables, and methods for efficient computation. [ABSTRACT FROM AUTHOR]

Meteorological series (daily precipitation, minimum and maximum air temperature) for Asmara (Eritrea) for the last 100 years (1914–2015) are analysed. The data were quality‐controlled and homogenized using publicly available data from surrounding countries as well as newly recovered data from 12 stations in Eritrea. Overall, the Asmara data showed a consistent pattern and there were no outliers outside of four standard deviations from the corresponding reference. Climate indices were calculated using the program RClimDex. Overall, 8 indices for description of the air temperature data and 10 for precipitation data were calculated. The analyses of averages and indices reveal large climatic variations in the central highlands of Eritrea. The results indicate significant changes in air temperature since 1943, with daily minimum and maximum air temperature increasing at a similar rate of 0.22 and 0.19°C/decade, respectively. The diurnal air temperature range shows a non‐significant decreasing trend over the study period. No significant variation was found in the annual total and the seasonal precipitation over the last century. Significant trends were detected for some daily precipitation indices, although the lack of reference series prevents an evaluation of their reliability. [ABSTRACT FROM AUTHOR]

We describe a global dataset of quality‐controlled in situ daily air temperature observations covering the period 1850–2015, developed in the framework of the EUSTACE (EU Surface Temperature for All Corners of Earth) project (www.eustaceproject.org). The dataset includes a total of 35,364 daily series of maximum and minimum temperature obtained from seven different collections. About 97% of the series are publicly available in a common format, while the remaining 3% can be obtained from the original data providers. Unlike other similar products, duplicates have been removed without blending of series, which simplifies data traceability and improves the temporal homogeneity of the individual series at the cost of a smaller average length. Residual artificial signals (breakpoints) in the series caused by station relocations, changes in instrumentation, etc., have been detected by means of the combination of four breakpoint detection tests, four variables and three temporal aggregations. The combined results give not only the most probable position of the breakpoints, but also a measure of their likelihood. The reliability of the detection was estimated for each year of each target series, based on the number of reference series and on their correlation with the target series. Moreover, its general performance was evaluated through a benchmark of synthetic series. This product will be combined with datasets of marine and ice in situ air temperature observations and with measurements from satellite to produce the first complete global statistical reconstruction of daily near‐surface air temperature. [ABSTRACT FROM AUTHOR]