Alexander Stickler

ERA-CLIM: Historical Surface and Upper-Air Data for Future Reanalyses

Future reanalyses might profit from assimilating additional historical surface as well as upper-air data. In the framework of the European Reanalysis of Global Climate Observations (ERACLIM; www.era-clim.eu) project, significant amounts of pre-1957 upper-air and surface data have been cataloged (>2.5 million station days), imaged (>450,000 images), and digitized (>1.25 million station days) to prepare new input datasets for upcoming reanalyses. These data cover large parts of the globe, focusing henceforth on less well-covered regions such as the tropics, the polar regions, and the oceans and on very early twentieth-century upper-air data from Europe and the United States. The total numbers of digitized/inventoried records (i.e., time series of meteorological data at fixed stations or from moving observational platforms) are 80/214 (surface), 735/1,783 (upper air), and 61/101 [moving upper-air (i.e., data from ships, etc.)]. Here, the authors give an overview of the data rescue activities, the data, and t...

The Comprehensive Historical Upper-Air Network

To better understand variability in weather and climate, it is vital to address past atmospheric circulation. This need requires meteorological information not just from the surface but also at upper levels. Current global upper-level datasets only reach back to the 1940s or 1950s and do not cover some important periods in the first half of the twentieth century. Extending the observational record is therefore considered important in order to analyze climate variability in the past and verify global climate models used to predict future climate change. Although earlier upper-air data from platforms such as radiosondes, aircraft, pilot balloons, registering balloons, and kites are available from various sources, no systematic compilation and quality assessment of upper-level data prior to the International Geophysical Year (1957/58) has ever been performed. Here we present the Comprehensive Historical Upper-Air Network (CHUAN). It is a consistent global historical upper-air dataset that has been derived fr...

A multi-data set comparison of the vertical structure of temperature variability and change over the Arctic during the past 100 years

We compare the daily, interannual, and decadal variability and trends in the thermal structure of the Arctic troposphere using eight observation-based, vertically resolved data sets, four of which have data prior to 1948. Comparisons on the daily scale between historical reanalysis data and historical upper-air observations were performed for Svalbard for the cold winters 1911/1912 and 1988/1989, the warm winters 1944/1945 and 2005/2006, and the International Geophysical Year 1957/1958. Excellent agreement is found at mid-tropospheric levels. Near the ground and at the tropopause level, however, systematic differences are identified. On the interannual time scale, the correlations between all data sets are high, but there are systematic biases in terms of absolute values as well as discrepancies in the magnitude of the variability. The causes of these differences are discussed. While none of the data sets individually may be suitable for trend analysis, consistent features can be identified from analyzing all data sets together. To illustrate this, we examine trends and 20-year averages for those regions and seasons that exhibit large sea-ice changes and have enough data for comparison. In the summertime Pacific Arctic and the autumn eastern Canadian Arctic, the lower tropospheric temperature anomalies for the recent two decades are higher than in any previous 20-year period. In contrast, mid-tropospheric temperatures of the European Arctic in the wintertime of the 1920s and 1930s may have reached values as high as those of the late 20th and early 21st centuries.

Exceptional atmospheric circulation during the “Dust Bowl”

[1]xa0The three-dimensional, regional and large-scale atmospheric circulation during the “Dust Bowl” is analyzed based on newly available historical upper-air data and reconstructed upper-level fields. The Great Plains Low Level Jet, transporting moisture into the region, was weakened on its eastern side, shallower, and penetrated less far north than during wet years. Nocturnal convection was likely suppressed by increased stability. Strong mid-tropospheric ridging was found over the Great Plains, and upper-tropospheric flow anomalies extended from the North Pacific across North America to the Atlantic. These findings provide a dynamical view of the “Dust Bowl” droughts, some aspects of which are distinct from other droughts. It is demonstrated that this is important for assessing predictive capabilities of current modeling systems.

Variability of large-scale atmospheric circulation indices for the northern hemisphere during the past 100 years

We present an analysis of the large-scale atmospheric circulation variability since 1900 based on various circulation indices. They represent the main features of the zonal mean circulation in the northern hemisphere in boreal winter (such as the Hadley circulation, the subtropical jet, and the polar vortex in the lower stratosphere) as well as aspects of the regional and large-scale circulation (the Pacific Walker Circulation, the Indian monsoon, the North Atlantic Oscillation, NAO, and the Pacific North American pattern, PNA). For the past decades we calculate the indices from different reanalyses (NCEP/NCAR, ERA-40, JRA-25, ERA- Interim). For the first half of the 20 th century the indices are statistically reconstructed based on historical upper-air and surface data as well as calculated from the Twentieth Century Reanalysis. The indices from all these observation-based data sets are compared to indices calculated from a 9-member ensemble of all forcings simulations performed with the chemistry-climate model SOCOL. After discussing the agreement among different data products, we analyse the interannual-to-decadal variability of the indices in the context of possible driving factors, such as El Nino/Southern Oscillation (ENSO), volcanic eruptions, and solar activity. The interannual variability of the Hadley cell strength, the subtropical jet strength, or the PNA is well reproduced by the model ensemble mean, i.e., it is predictable in the context of the specified forcings. The source of this predictability is mainly related to ENSO (or more generally, tropical sea-surface temperatures). For other indices such as the strength of the stratospheric polar vortex, the NAO, or the poleward extent of the Hadley cell the correlations between observations and model ensemble mean are much lower, but so are the correlations within the model ensemble. Multidecadal variability and trends in the individual series are discussed in the context of the underlying anthropogenic and natural forcings. While consistent trends were found for some of the indices, results also indicate that care should be taken when analysing trends in reconstructions or reanalysis data. Zusammenfassung Diese Studie prasentiert Ergebnisse einer Analyse der Variabilitat der grosraumigen, atmospharischen Zirkulation seit 1900, basierend auf verschiedenen Zirkulationsindizes. Die Indizes umfassen sowohl die Hauptcharakteristika der zonal gemittelten, nordhemispharischen Zirkulation im Nordwinter (z.B. Hadley- Zirkulation, Subtropenjet und polarer Vortex in der unteren Stratosphare) als auch Aspekte der regionalen und grosraumigen Zirkulation (pazifische Walker-Zirkulation, indischer Monsun, nordatlantische Oszilla- tion (NAO) und das Pacific North American-Muster (PNA)). Die Indizes wurden fur die letzten Dekaden aus verschiedenen Reanalysen berechnet (NCEP/NCAR, ERA-40, JRA-25, ERA-Interim). Fur die erste Halfte des 20. Jahrhunderts wurden sie dagegen, basierend auf historischen Bodendaten und Messdaten aus der freien Troposphare, statistisch rekonstruiert und zusatzlich aus der Twentieth Century-Reanalyse berechnet. All diese auf Messungen basierenden Indizeszeitreihen werden in der vorliegenden Studie mit entsprechenden, aus einem Ensemble von 9 Simulationen gewonnenen Indizeszeitreihen verglichen (alle ex- ternen Forcings aktiviert, Chemie-Klimamodell SOCOL). Nach der genaueren Betrachtung des Grades der ¨ Ubereinstimmung zwischen den verschiedenen Produkten wird die interannuelle und dekadale Vari- abilitat der Indizes im Kontext moglicher Einflussfaktoren wie El Nino/Southern Oscillation (ENSO), Vulkanausbruchen und Sonnenaktivitat analysiert. Die interannuelle Variabilitat der Hadleyzellstarke, des Subtropenjets oder des PNA-Musters wird vom Ensemblemittel des Modells erfolgreich reproduziert, d.h. sie ist vorhersagbar bei Kenntnis der spezifischen Forcings. Die Quelle der Vorhersagbarkeit liegt im Wesentlichen in der ENSO-Variabilitat. Fur andere Indizes wie die Starke des stratospharischen, po- laren Vortex, die NAO oder die polwartige Ausdehnung der Hadleyzelle sind die Korrelationen zwischen Beobachtungen und dem Ensemblemittel des Modells viel kleiner. Dasselbe gilt aber gleichermasen fur die Korrelationen innerhalb des Ensembles. Multidekadale Variabilitat und Trends in den Zeitreihen werden im Zusammenhang mit zugrunde liegenden anthropogenen als auch naturlichen Antriebsfaktoren besprochen. Obwohl fur einige Indizes konsistente Trends gefunden werden konnten, zeigen die Ergeb- nisse auch, dass beim Ableiten von Trends aus Reanalyse- oder Rekonstruktionsdaten Vorsicht geboten ist.

Reconstruction of Global Monthly Upper-Level Temperature and Geopotential Height Fields Back to 1880

Abstract This work presents statistically reconstructed global monthly mean fields of temperature and geopotential height (GPH) up to 100 hPa for the period 1880–1957. For the statistical model several thousand predictors were used, comprising a large amount of historical upper-air data as well as data from the earth’s surface. In the calibration period (1958–2001), the statistical models were fit using the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as the predictand. After the weighting of the predictors, principal component (PC) analyses were performed on both the predictand and predictor dataset. Multiple linear regression models relate each principal component time series from the predictand with an optimal subset of principal component time series from the predictor. To assess the quality of the reconstructions, statistical split-sample validation (SSV) experiments were performed within the calibration period. Furthermore, the reconstructions were compared w...

The early twentieth century warm period in the European Arctic

The European Arctic experienced a pronounced warming around 1920 and a sustained warm period in the 1920s and 1930s. The causes of this climatic event are not fully known. However, understanding this event is considered important for assessing current and future climate change in the Arctic. Here we investigate the role of atmospheric circulation variability based on newly available historical upper-air data and statistical reconstructions of atmospheric circulation. The strongest warming at the ground from the 1910s to the 1920s and 1930s was found in wintertime. Historical upper-air data in this region from the 1930s show warm temperatures also in the lower troposphere. Reconstructed geopotential height fields suggest stronger than normal meridional transport of warm air into the European Arctic during the warm period compared to the preceding cold period. We propose that the 1920-1940 warm period can be subdivided into two periods with distinct circulation regimes: During the 1920s, warm, relatively clean air masses from the North Atlantic lead to a warming, while during the 1930s warm, rather polluted air masses from Western Europe played an important role. This is reflected in a sudden increase in sulphate concentrations in an ice core from Svalbard around 1930. The aerosols might have amplified the warming via changing cloud long wave emissivity, but this mechanism remains to be further studied. The circulation anomalies in the North Atlantic region during the early 20 th century warm period that are shown in this paper form an observation-based counterpart against which model studies can be compared.

A gridded monthly upper-air data set from 1918 to 1957

Significant efforts have been devoted in recent years towards extending observation-based three-dimensional atmospheric data sets back in time. Such data sets form an important basis for a better understanding of the climate system. Here we present a new monthly three-dimensional global data set that is based on historical upper-air data and surface data. We use statistical reconstruction techniques, calibrated using ERA-40 data, to obtain gridded data from the numerous, but scattered and heterogeneous historical upper-air observations. In contrast to previous work, in which we used hemispheric principal components on both the predictor and the predictand side to reconstruct spatially complete fields back to 1880, we restrict the procedure to places and times where upper-air observations are available. Each grid column (consisting of four variables at six levels) is then reconstructed independently using only predictor variables in the vicinity (i.e., only local stationarity is required rather than stationary large-scale patterns). The product, termed REC2, is a gridded, global monthly data set of geopotential height, temperature, and u and v wind from 850 to 100xa0hPa back to 1918. The data set is sparse (i.e., many grid cells are empty), but provides an alternative to large-scale reconstructions as it allows for non-stationary teleconnections. We show the results of several validation experiments, compare our new data set with a number of existing data sets, and demonstrate that it is suitable for analysing large-scale climate variability on interannual time-scales.

Aerological observations in the Tropics in the Early Twentieth Century

In the first decades of the 20 th century, aerological observations were for the first time performed in tropical regions. One of the most prominent endeavours in this respect was ARTHUR BERSONx90s aerological expedition to East Africa. Although the main target was the East African monsoon circulation, the expedition provided also other insights that profoundly changed meteorology and climatology. BERSON observed that the tropical tropopause was much higher and colder than that over midlatitudes. Moreover, westerly winds were observed in the lower stratosphere, apparently contradicting the high-altitude equatorial easterly winds that were known since the Krakatoa eruption (x8fx8fKrakatoa easterliesx90x90). The puzzle was only resolved five decades later with the discovery of the Quasi-Biennial Oscillation (QBO). In this paper we briefly summarize the expedition of BERSON and review the results in a historical context and in the light of the current research. In the second part of the paper we re-visit BERSONx90s early aerological observations, which we have digitized. We compare the observed wind profiles with corresponding profiles extracted from the x8fx8fTwentieth Century Reanalysisx90x90, which provides global three-dimensional weather information back to 1871 based on an assimilation of sea-level and surface pressure data. The comparison shows a good agreement at the coast but less good agreement further inland, at the shore of Lake Victoria, where the circulation is more complex. These results demonstrate that BERSONx90s observations are still valuable today as input to current reanalysis systems or for their validation.

Observation errors in early historical upper‐air observations

[1]xa0Upper-air observations are a fundamental data source for global atmospheric data products, but uncertainties, particularly in the early years, are not well known. Most of the early observations, which have now been digitized, are prone to a large variety of undocumented uncertainties (errors) that need to be quantified, e.g., for their assimilation in reanalysis projects. We apply a novel approach to estimate errors in upper-air temperature, geopotential height, and wind observations from the Comprehensive Historical Upper-Air Network for the time period from 1923 to 1966. We distinguish between random errors, biases, and a term that quantifies the representativity of the observations. The method is based on a comparison of neighboring observations and is hence independent of metadata, making it applicable to a wide scope of observational data sets. The estimated mean random errors for all observations within the study period are 1.5 K for air temperature, 1.3 hPa for pressure, 3.0 ms−1for wind speed, and 21.4° for wind direction. The estimates are compared to results of previous studies and analyzed with respect to their spatial and temporal variability.