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Copenhagen, Denmark

The Danish Meteorological Institute is the official Danish meteorological institute, administrated by the Ministry of Transport and Energy. The institute makes weather forecasts and observations for Denmark, Greenland, and the Faroe Islands.It was founded in 1872, largely through the efforts of Ludwig A. Colding.The Danish Meteorological Institute – DMI – encompasses the combined knowledge of the former Meteorological Institute, the Meteorological Service for Civil Aviation and the Meteorological Service for Defence. The Meteorological Institute was founded in 1872 under the Ministry of the Navy. The Meteorological Service for Civil Aviation was established in 1926, and used to be part of the Civil Aviation Administration. The Meteorological Service for Defence was established in 1953. The present-day DMI was established in 1990 through the merger of the three above-mentioned institutions. DMI is organized under the Ministry of Transport, and has a staff of about 380. In addition, DMI has around 450 voluntary weather and climate observers.The institute was founded for the purpose of “making observations, communicating them to the general public, and developing scientific meteorology”. These remain DMI’s most important tasks, even though society and means of communication have developed enormously in the intervening period, as too has the need for qualified meteorological advice. DMI presently possesses comprehensive, internationally acclaimed knowledge about every aspect of weather and climate.DMI is responsible for serving the meteorological needs of society within the kingdom of Denmark including territorial waters and airspace. This entails monitoring weather, climate and environmental conditions in the atmosphere, on the land and at sea. The primary aim of these activities is to safeguard human life and property, as well as to provide a foundation for economic and environmental planning – especially within the armed forces, aviation, shipping and road traffic.DMI’s most familiar services are the media weather forecasts, but the institute also assists the business community, institutions and members of the public in making sound decisions from the economic, environment and safety points of view. A wide range of services is also utilized by the fishery and agricultural sectors, by sports associations and others.DMI’s expertise and service is to some extent founded on advanced new technology within super computers, satellites, radar and automatic measuring equipment. Solid research and development work ensures that DMI is run economically and rationally, and that the quality of the products meets modern expectations.DMI runs an ice patrol service based in Narsarsuaq that observes the sea ice and icebergs along the coasts of Greenland, draws up ice charts and solves other safety-related tasks for navigation in Greenland marine waters. Wikipedia.

Christiansen B.,Danish Meteorological Institute
Journal of Climate | Year: 2011

There are indications that hemispheric-mean climate reconstructions seriously underestimate the amplitude of low-frequency variability and trends. Some of the theory of linear regression and error-in-variables models is reviewed to identify the sources of this problem. On the basis of the insight gained, a reconstruction method that is supposed to minimize the underestimation is formulated. The method consists of reconstructing the local temperatures at the geographical locations of the proxies, followed by calculating the hemispheric average. The method is tested by applying it to an ensemble of surrogate temperature fields based on two climate simulations covering the last 500 and 1000 yr. Compared to the regularized expectation maximization (RegEM) truncated total least squares (TTLS) method and a composite-plus-scale method-two methods recently used in the literature-the new method strongly improves the behavior regarding lowfrequency variability and trends. The potential importance in real-world situations is demonstrated by applying the methods to a set of 14 decadally smoothed proxies. Here the new method shows much larger low-frequency variability and a much colder preindustrial temperature level than the other reconstruction methods. However, this should mainly be seen as a demonstration of the potential losses and gains of variability, as the reconstructions based on the 14 decadally smoothed proxies are not very robust. © 2011 American Meteorological Society. Source

Even in the simple case of univariate linear regression and prediction there are important choices to be made regarding the origins of the noise terms and regarding which of the two variables under consideration that should be treated as the independent variable. These decisions are often not easy to make but they may have a considerable impact on the results. A unified probabilistic (i.e., Bayesian with flat priors) treatment of univariate linear regression and prediction is given by taking, as starting point, the general errors-in-variables model. Other versions of linear regression can be obtained as limits of this model. The likelihood of the model parameters and predictands of the general errors-in-variables model is derived by marginalizing over the nuisance parameters. The resulting likelihood is relatively simple and easy to analyze and calculate. The wellknown unidentifiability of the errors-in-variables model is manifested as the absence of a well-defined maximum in the likelihood. However, this does not mean that probabilistic inference cannot be made; the marginal likelihoods of model parameters and the predictands have, in general, well-defined maxima. A probabilistic version of classical calibration is also included and it is shown how it is related to the errors-invariablesmodel. The results are illustrated by an example fromthe coupling between the lower stratosphere and the troposphere in the Northern Hemisphere winter. © 2014 American Meteorological Society. Source

Christiansen B.,Danish Meteorological Institute
Journal of Climate | Year: 2013

The author investigates whether the increasing numbers of warm records and warm extremes in the extratropical Northern Hemisphere over the last decade are statistically significant. For the extremes, the focus is on summer mean temperatures; for warm records it is on daily andmonthly means. Statistical significance is a highly nontrivial problem because the atmosphere is both spatially and temporally strongly autocorrelated. Therefore, a method is applied to produce an ensemble of surrogate fields that are statistically similar to the observed temperature field except that the surrogates are stationary. The significance is then estimated by comparing the number of records or extremes in the observations to similar numbers in the surrogates. The number of warm records and the number of extreme summers are found to have the same general temporal development, with a slow decrease fromthe late 1940s to aminimum in the 1970s followed by an increase to the present high values. However, there is a strong difference in the statistical significance of the different quantities. With very strong statistical significance, the recent large number ofwarm daily records and the number of extremely warm summers cannot be explained as chance occurrences. Both of these quantities show numbers of recent consecutive years with values above the 95% level that aremuch larger than any similar numbers found in the ensemble of 1000 surrogates. No significant change in the number of monthly warm records is found. The statistical significance weakens when considering the individual seasons or smaller regions like Europe. © 2013 American Meteorological Society. Source

Christiansen B.,Danish Meteorological Institute | Ljungqvist F.C.,University of Stockholm
Climate of the Past | Year: 2012

We present two new multi-proxy reconstructions of the extra-tropical Northern Hemisphere (30-90°N) mean temperature: a two-millennia long reconstruction reaching back to 1 AD and a 500-yr long reconstruction reaching back to 1500 AD. The reconstructions are based on compilations of 32 and 91 proxies, respectively, of which only little more than half pass a screening procedure and are included in the actual reconstructions. The proxies are of different types and of different resolutions (annual, annual-to-decadal, and decadal) but all have previously been shown to relate to local or regional temperature. We use a reconstruction method, LOCal (LOC), that recently has been shown to confidently reproduce low-frequency variability. Confidence intervals are obtained by an ensemble pseudo-proxy method that both estimates the variance and the bias of the reconstructions. The two-millennia long reconstruction shows a well defined Medieval Warm Period, with a peak warming ca. 950-1050 AD reaching 0.6 °C relative to the reference period 1880-1960 AD. The 500-yr long reconstruction confirms previous results obtained with the LOC method applied to a smaller proxy compilation; in particular it shows the Little Ice Age cumulating in 1580-1720 AD with a temperature minimum of g -1.0 °C below the reference period. The reconstructed local temperatures, the magnitude of which are subject to wide confidence intervals, show a rather geographically homogeneous Little Ice Age, while more geographical inhomogeneities are found for the Medieval Warm Period. Reconstructions based on different subsets of proxies show only small differences, suggesting that LOC reconstructs 50-yr smoothed extra-tropical NH mean temperatures well and that low-frequency noise in the proxies is a relatively small problem. © Author(s) 2012. CC Attribution 3.0 License. Source

Christiansen B.,Danish Meteorological Institute
Journal of Climate | Year: 2010

The Northern Hemisphere extended winter mean stratospheric vortex alternates between a strong and a weak state, which is manifested in a statistically significant bimodal distribution. In the end of the 1970s a regime change took place, increasing the frequency of the strong phase relative to the weak phase. This paper investigates the connection between the regime behavior of the vortex and the equatorial quasi-biennial oscillation (QBO) in three different datasets. Although there are some differences between the datasets, they agree regarding the general picture. It is found that stratospheric equatorial wind between 70 and 8 hPa shows a bimodal structure in the Northern Hemisphere winter. Such bimodality is nontrivial as it requires only weak variability in the amplitude. Unimodality is found above 8 hPa, where the semiannual oscillation dominates. A strong coincidence is found between strong (weak) vortex winters and winter in the westerly (easterly) QBO regime. Furthermore, the change of the vortex in the late 1970s can be related to a change in the QBO from a period with strong bimodality to a period with weak bimodality. Careful consideration of the statistical significance shows that this change in the QBO can be a random process simply related to the annual sampling of the QBO. Finally, previous findings of phase locking between the QBO and the annual cycle are considered; it is shown that the phase locking is related to the seasonal variations in the bimodality of the QBO. © 2010 American Meteorological Society. Source

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