A Novel Method for the Homogenization of Daily Temperature Series and Its Relevance for Climate Change Analysis

Instrumental daily series of temperature are often affected by inhomogeneities. Several methods are available for their correction at monthly and annual scales, whereas few exist for daily data. Here, an improved version of the higher-order moments (HOM) method, the higher-order moments for autocorrelated data (HOMAD), is proposed. HOMAD addresses the main weaknesses of HOM, namely, data autocorrelation and the subjective choice of regression parameters. Simulated series are used for the comparison of both methodologies. The results highlight and reveal that HOMAD outperforms HOM for small samples. Additionally, three daily temperature time series from stations in the eastern Mediterranean are used to show the impact of homogenization procedures on trend estimation and the assessment of extremes. HOMAD provides an improved correction of daily temperature time series and further supports the use of corrected daily temperature time series prior to climate change assessment.

A physics-based correction model for homogenizing sub-daily temperature series

A new physics-based technique for correcting inhomogeneities present in sub-daily temperature records is proposed. The approach accounts for changes in the sensor-shield characteristics that affect the energy balance dependent on ambient weather conditions (radiation, wind). An empirical model is formulated that reflects the main atmospheric processes and can be used in the correction step of a homogenization procedure. The model accounts for short- and long-wave radiation fluxes (including a snow cover component for albedo calculation) of a measurement system, such as a radiation shield. One part of the flux is further modulated by ventilation. The model requires only cloud cover and wind speed for each day, but detailed site-specific information is necessary. The final model has three free parameters, one of which is a constant offset. The three parameters can be determined, e.g., using the mean offsets for three observation times. The model is developed using the example of the change from the Wild screen to the Stevenson screen in the temperature record of Basel, Switzerland, in 1966. It is evaluated based on parallel measurements of both systems during a sub-period at this location, which were discovered during the writing of this paper. The model can be used in the correction step of homogenization to distribute a known mean step-size to every single measurement, thus providing a reasonable alternative correction procedure for high-resolution historical climate series. It also constitutes an error model, which may be applied, e.g., in data assimilation approaches.

Break detection of annual Swiss temperature series

[1] Instrumental temperature series are often affected by artificial breaks (“break points”) due to (e.g.,) changes in station location, land-use, or instrumentation. The Swiss climate observation network offers a high number and density of stations, many long and relatively complete daily to sub-daily temperature series, and well-documented station histories (i.e., metadata). However, for many climate observation networks outside of Switzerland, detailed station histories are missing, incomplete, or inaccessible. To correct these records, the use of reliable statistical break detection methods is necessary. Here, we apply three statistical break detection methods to high-quality Swiss temperature series and use the available metadata to assess the methods. Due to the complex terrain in Switzerland, we are able to assess these methods under specific local conditions such as the Foehn or crest situations. We find that the temperature series of all stations are affected by artificial breaks (average = 1 break point / 48 years) with discrepancies in the abilities of the methods to detect breaks. However, by combining the three statistical methods, almost all of the detected break points are confirmed by metadata. In most cases, these break points are ascribed to a combination of factors in the station history.

Analysis of Hail and Temperature Series for Peninsular Spain

Hail is a serious concern for agriculture on the Iberian Peninsula. Hailstorms affect crop yield and/or quality to a degree that depends on the crop species and the phenological time. In Europe, Spain is one of the countries that experience relatively high agricultural losses related to hailstorms. It is of high interest to study models that can support calculations of the probabilities of economic losses due to hail damage and of the tendency over time for such losses. Some studies developed in France and the Netherdlands show that the summer mean temperature was highly correlated with a yearly hail severity index developed from hailrelated parameters obtained for insurance purposes. Meanwhile, other studies in the USA point out that a highly significant correlation between both is not possible to find due to high climatic variability. The aim of this work is to test the correlation between average minimum temperatures and hail damage intensity over the Spanish Iberian Peninsula. With this purpose, correlation analyses on both variables were performed for the 47 Spanish provinces (as individuals and single set) and for all crops and four individual crops: grapes, wheat, barley and winter grains. Suitable crop insurance data are available from 1981 until 2007 and based on this period, temperature data were obtained. This study does not confirm the results previously obtained for France and the Netherlands that relate observed hail damage to the average minimum temperature. The reason for this difference and the nature of the cases observed are discussed.

Homogenization of Portuguese long-term temperature data series: Lisbon, Coimbra and Porto

Three long-term temperature data series measured in Portugal were studied to detect and correct non-climatic homogeneity breaks and are now available for future studies of climate variability. Series of monthly minimum (Tmin) and maximum (Tmax) temperatures measured in the three Portuguese meteorological stations of Lisbon (from 1856 to 2008), Coimbra (from 1865 to 2005) and Porto (from 1888 to 2001) were studied to detect and correct non-climatic homogeneity breaks. These series together with monthly series of average temperature (Taver) and temperature range (DTR) derived from them were tested in order to detect homogeneity breaks, using, firstly, metadata, secondly, a visual analysis and, thirdly, four widely used homogeneity tests: von Neumann ratio test, Buishand test, standard normal homogeneity test and Pettitt test. The homogeneity tests were used in absolute (using temperature series themselves) and relative (using sea-surface temperature anomalies series obtained from HadISST2 close to the Portuguese coast or already corrected temperature series as reference series) modes. We considered the Tmin, Tmax and DTR series as most informative for the detection of homogeneity breaks due to the fact that Tmin and Tmax could respond differently to changes in position of a thermometer or other changes in the instrument's environment; Taver series have been used, mainly, as control. The homogeneity tests show strong inhomogeneity of the original data series, which could have both internal climatic and non-climatic origins. Homogeneity breaks which have been identified by the last three mentioned homogeneity tests were compared with available metadata containing data, such as instrument changes, changes in station location and environment, observing procedures, etc. Significant homogeneity breaks (significance 95% or more) that coincide with known dates of instrumental changes have been corrected using standard procedures. It was also noted that some significant homogeneity breaks, which could not be connected to the known dates of any changes in the park of instruments or stations location and environment, could be caused by large volcanic eruptions. The corrected series were again tested for homogeneity: the corrected series were considered free of non-climatic breaks when the tests of most of monthly series showed no significant (significance 95% or more) homogeneity breaks that coincide with dates of known instrument changes. Corrected series are now available in the frame of ERA-CLIM FP7 project for future studies of climate variability.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

How stable are 20th century calibration models? A high-resolution summer temperature reconstruction for the eastern Swiss Alps back to A.D. 1580 derived from proglacial varved sediments

We found a significant positive correlation between local summer air temperature (May-September) and the annual sediment mass accumulation rate (MAR) in Lake Silvaplana (46°N, 9°E, 1800 m a.s.l.) during the twentieth century (r = 0.69, p < 0.001 for decadal smoothed series). Sediment trap data (2001-2005) confirm this relation with exceptionally high particle yields during the hottest summer of the last 140 years in 2003. On this base we developed a decadal-scale summer temperature reconstruction back to AD 1580. Surprisingly, the comparison of our reconstruction with two other independent regional summer temperature reconstructions (based on tree-rings and documentary data) revealed a significant negative correlation for the pre-1900 data (ie, late ‘Little Ice Age’). This demonstrates that the correlation between MAR and summer temperature is not stable in time and the actualistic principle does not apply in this case. We suggest that different climatic regimes (modern/‘Little Ice Age’) lead to changing state conditions in the catchment and thus to considerably different sediment transport mechanisms. Therefore, we calibrated our MAR data with gridded early instrumental temperature series from AD 1760-1880 (r = -0.48, p < 0.01 for decadal smoothed series) to properly reconstruct the late LIA climatic conditions. We found exceptionally low temperatures between AD 1580 and 1610 (0.75°C below twentieth-century mean) and during the late Maunder Minimum from AD 1680 to 1710 (0.5°C below twentieth-century mean). In general, summer temperatures did not experience major negative departures from the twentieth-century mean during the late ‘Little Ice Age’. This compares well with the two existing independent regional reconstructions suggesting that the LIA in the Alps was mainly a phenomenon of the cold season.

Long-range correlations in rectal temperature fluctuations of healthy infants during maturation

BACKGROUND: Control of breathing, heart rate, and body temperature are interdependent in infants, where instabilities in thermoregulation can contribute to apneas or even life-threatening events. Identifying abnormalities in thermoregulation is particularly important in the first 6 months of life, where autonomic regulation undergoes critical development. Fluctuations in body temperature have been shown to be sensitive to maturational stage as well as system failure in critically ill patients. We thus aimed to investigate the existence of fractal-like long-range correlations, indicative of temperature control, in night time rectal temperature (T(rec)) patterns in maturing infants. METHODOLOGY/PRINCIPAL FINDINGS: We measured T(rec) fluctuations in infants every 4 weeks from 4 to 20 weeks of age and before and after immunization. Long-range correlations in the temperature series were quantified by the correlation exponent, alpha using detrended fluctuation analysis. The effects of maturation, room temperature, and immunization on the strength of correlation were investigated. We found that T(rec) fluctuations exhibit fractal long-range correlations with a mean (SD) alpha of 1.51 (0.11), indicating that T(rec) is regulated in a highly correlated and hence deterministic manner. A significant increase in alpha with age from 1.42 (0.07) at 4 weeks to 1.58 (0.04) at 20 weeks reflects a change in long-range correlation behavior with maturation towards a smoother and more deterministic temperature regulation, potentially due to the decrease in surface area to body weight ratio in the maturing infant. alpha was not associated with mean room temperature or influenced by immunization CONCLUSIONS: This study shows that the quantification of long-range correlations using alpha derived from detrended fluctuation analysis is an observer-independent tool which can distinguish developmental stages of night time T(rec) pattern in young infants, reflective of maturation of the autonomic system. Detrended fluctuation analysis may prove useful for characterizing thermoregulation in premature and other infants at risk for life-threatening events.

Northern Hemisphere temperature reconstruction during the last millennium using multiple annual proxies

Previous studies have either exclusively used annual tree-ring data or have combined tree-ring series with other, lower temporal resolution proxy series. Both approaches can lead to significant uncertainties, as tree-rings may underestimate the amplitude of past temperature variations, and the validity of non-annual records cannot be clearly assessed. In this study, we assembled 45 published Northern Hemisphere (NH) temperature proxy records covering the past millennium, each of which satisfied 3 essential criteria: the series must be of annual resolution, span at least a thousand years, and represent an explicit temperature signal. Suitable climate archives included ice cores, varved lake sediments, tree-rings and speleothems. We reconstructed the average annual land temperature series for the NH over the last millennium by applying 3 different reconstruction techniques: (1) principal components (PC) plus second-order autoregressive model (AR2), (2) composite plus scale (CPS) and (3) regularized errors-in-variables approach (EIV). Our reconstruction is in excellent agreement with 6 climate model simulations (including the first 5 models derived from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and an earth system model of intermediate complexity (LOVECLIM), showing similar temperatures at multi-decadal timescales; however, all simulations appear to underestimate the temperature during the Medieval Warm Period (MWP). A comparison with other NH reconstructions shows that our results are consistent with earlier studies. These results indicate that well-validated annual proxy series should be used to minimize proxy-based artifacts, and that these proxy series contain sufficient information to reconstruct the low-frequency climate variability over the past millennium.

New insights into the reconstructed temperature in Portugal over the last 400 years

The consistency of an existing reconstructed annual (December–November) temperature series for the Lisbon region (Portugal) from 1600 onwards, based on a European-wide reconstruction, with (1) five local borehole temperature–depth profiles; (2) synthetic temperature– depth profiles, generated from both reconstructed temperatures and two regional paleoclimate simulations in Portugal; (3) instrumental data sources over the twentieth century; and (4) temperature indices from documentary sources during the late Maunder Minimum (1675–1715) is assessed. The low-frequency variability in the reconstructed temperature in Portugal is not entirely consistent with local borehole temperature–depth profiles and with the simulated response of temperature in two regional paleoclimate simulations driven by reconstructions of various climate forcings. Therefore, the existing reconstructed series is calibrated by adjusting its low-frequency variability to the simulations (first-stage adjustment). The annual reconstructed series is then calibrated in its location and scale parameters, using the instrumental series and a linear regression between them (second-stage adjustment). This calibrated series shows clear footprints of the Maunder and Dalton minima, commonly related to changes in solar activity and explosive volcanic eruptions, and a strong recent-past warming, commonly related to human-driven forcing. Lastly, it is also in overall agreement with annual temperature indices over the late Maunder Minimum in Portugal. The series resulting from this post-reconstruction adjustment can be of foremost relevance to improve the current understanding of the driving mechanisms of climate variability in Portugal.

Magnetism, exchange and crystal field parameters in the orbitally unquenched Ising antiferromagnet FePS3

FePS3 is a layered antiferromagnet (T N=123 K) with a marked Ising anisotropy in magnetic properties. The anisotropy arises from the combined effect of the trigonal distortion from octahedral symmetry and spin-orbit coupling on the orbitally degenerate5 T 2g ground state of the Fe2+ ion. The anisotropic paramagnetic susceptibilities are interpreted in terms of the zero field Hamiltonian, ?=?i [?(L iz 2 ?2)+|?|L i .S i ]?? ij J ij S i .S j . The crystal field trigonal distortion parameter ?, the spin-orbit coupling ? and the isotropic Heisenberg exchange,J ij, were evaluated from an analysis of the high temperature paramagnetic susceptibility data using the Correlated Effective Field (CEF) theory for many-body magnetism developed by Lines. Good agreement with experiment were obtained for ?/k=215.5 K; ?/k=166.5 K;J nn k=27.7 K; andJ nnn k=?2.3 K. Using these values of the crystal field and exchange parameters the CEF predicts aT N=122 K for FePS3, which is remarkably close to the observed value of theT N. The accuracy of the CEF approximation was also ascertained by comparing the calculated susceptibilities in the CEF with the experimental susceptibility for the isotropic Heisenberg layered antiferromagnet MnPS3, for which the high temperature series expansion susceptibility is available.

Estudo comparativo da estrutura da turbulência atmosférica na camada limite superficial acima da floresta primária e região desmatada da Amazônia: análise de ondeletas aplicadas à detecção de estruturas correntes

Foram analisados dados turbulentos de resposta rápida, coletados em torres micrometeorológicas de 54 metros de altura em Caxiuanã-Pa, de 60 metros de altura na Rebio-Jarú-Ro e em torre de 4,04 metros de altura na Fazenda Nossa Senhora-Ro. Foi desenvolvido estudo comparativo de detecção de estruturas coerentes em dados obtidos acima de florestas e pastagem, portanto sob diferentes condições de rugosidade superficial. Aplicou-se a Transformada em Ondeletas de Morlet para identificar a escala de ocorrência das estruturas coerentes nos sinais de temperatura. Comparou-se a duração média e o comprimento médio das estruturas coerentes para duas.superfícies com rugosidades superficiais diferentes: Caxiuanã e Fazenda Nossa Senhora. Parâmetros de estabilidade atmosférica foram calculados para propiciar um estudo da variabilidade das estruturas coerentes em função das condições de estabilidade atmosférica. Foi calculado sobre a Rebio-Jarú a altura do ponto de inflexão do perfil vertical da velocidade do vento médio e a partir do valor do mesmo observou-se uma nítida correlação deste com a escala de ocorrência das estruturas coerentes. Finalmente, foram calculados os coeficientes de correlação para os sinais brutos e na escala de ocorrência das estruturas coerentes com a finalidade de melhor compreender os resultados de um ponto de vista da ação das estruturas coerentes na mistura turbulenta. Os resultados mostram um comportamento marcadamente diferente, no que diz respeito à floresta e à pastagem. Observou-se que em superfícies rugosas, tais com florestas, em condições próximas da neutralidade, predominam padrões de oscilações associados as escalas temporais da ordem de 80 s, as quais provavelmente, são manifestações de estruturas do tipo "rolos". No entanto, à medida que a altura do ponto de inflexão se aproximou do topo do dossel ocorreu uma diminuição na duração das estruturas coerentes. Além disso, foi observado que o coeficiente de correlação calculado na escala de ocorrência das estruturas coerentes foi consideravelmente maior que o mesmo calculado para o sinal bruto. Tais resultados sugerem mudanças significativas na estrutura da turbulência em regiões desmatadas comparativamente àquelas em que foram mantidas as florestas primárias da Amazônia.

Glaciers and climate in northern Sweden during the 19th and 20th century

Our understanding of the climate of northern Sweden during the late Holocene is largely dependent on proxy-data series. These datasets remain spatially and temporally sparse and instrumental series are rare prior to the mid 19th century. Nevertheless, the glaciology and paleo-glaciology of the region has a strong potential significance for the exploration of climate change scenarios, past and future. The aim of this thesis is to investigate the 19th and 20th century climate in the northern Swedish mountain range. This provides a good opportunity to analyse the natural variability of the climate before the onset of the industrial epoch. Developing a temporal understanding of fluctuations in glacier front positions and glacier mass balance that is linked to a better understanding of their interaction and relative significance to climate is fundamental in the assessment of past climate. I have chosen to investigate previously unexplored temperature data from northern Sweden from between 1802 and 1860 and combined it with a temperature series from a synoptic station in Haparanda, which began operation in 1859, in order to create a reliable long temperature series for the period 1802 to 2002. I have also investigated two different glaciers, Pårteglaciären and Salajekna, which are located in different climatic environments. These glaciers have, from a Swedish perspective, long observational records. Furthermore, I have investigated a recurring jökulhlaup at the glacier Sälkaglaciären in order to analyse glacier-climate relationships with respect to the jökulhlaups. A number of datasets are presented, including: glacier frontal changes, in situ and photogrammetric mass balance data, in situ and satellite radar interferometry measurements of surface velocity, radar measurements, ice volume data and a temperature series. All these datasets are analysed in order to investigate the response of the glaciers to climatic stimuli, to attribute specific behaviour to particular climates and to analyse the 19th and 20th century glacier/climate relationships in northern Sweden. The 19th century was characterized by cold conditions in northern Sweden, particularly in winter. Significant changes in the amplitude of the annual temperature cycle are evident. Through the 19th century there is a marked decreasing trend in the amplitude of the data, suggesting a change towards a prevalence of maritime (westerly) air masses, something which has characterised the 20th century. The investigations on Salajekna support the conclusion that the major part of the 19th century was cold and dry. The 19th century advance of Salajekna was probably caused by colder climate in the late 18th and early 19th centuries, coupled with a weakening of the westerly airflow. The investigations on Pårteglaciären show that the glacier has a response time of ~200 years. It also suggests that there was a relatively high frequency of easterly winds providing the glacier with winter precipitation during the 19th century. Glaciers have very different response times and are sensitive to different climatic parameters. Glaciers in rather continental areas of the Subarctic and Arctic can have very long response times because of mass balance considerations and not primarily the glacier dynamics. This is of vital importance for analyzing Arctic and Subarctic glacier behaviour in a global change perspective. It is far from evident that the behaviour of the glacier fronts today reflects the present climate.