Hans Gleisner

Patterns of tropospheric response to solar variability

meteorological data set from which El Nino and volcanic effects are removed together with the effects of any forcing factors that primarily are expressed as trends in the climate data, e.g., tropospheric aerosols or greenhouse gases. This correction of the data results in an increased clarity of the solar signals, and allows us to rule out the two most important competing forcing factors as a cause of the apparent solar effects. We show that significant solar signals are found in all major observables throughout the low- and mid-latitude troposphere, and that a spatially heterogenous response pattern emerges in which water vapor and the large-scale tropospheric circulation systems play important roles. These findings have implications for the question of where and how solar variability affects the climate system.

On correlations between the North Atlantic Oscillation, geopotential heights, and geomagnetic activity

We investigate correlations between geomagnetic activity indices, theNorth Atlantic Oscillation (NAO), and stratospheric geopotentialheights. It is shown that the correlation between the geomagnetic indexAp and the NAO index is high and significant since about 1970, that itis significant during winter only, that it was not significant beforeabout 1970, and that the correlations are dominated by quasi-decadalscales of variability. Analysis of the spatial pattern of correlations,restricted to the Northern Hemisphere and wintertime, shows thatsignificant correlations between Ap and sea-level pressures and betweenAp and stratospheric geopotential heights are found for the period1973-2000. However, for the period 1949-1972 no significant correlationsare found at the surface while significant correlations still are foundin the stratosphere. This might indicate that a solar forcing, primarilyacting in the stratosphere, is propagating its influence downward in thelater period but not in the earlier. (Less)

A neural network‐based local model for prediction of geomagnetic disturbances

This study shows how locally observed geomagnetic disturbances can bepredicted from solar wind data with artificial neural network (ANN)techniques. After subtraction of a secularly varying base level, thehorizontal components XSq and YSq of the quiettime daily variations are modeled with radial basis function networkstaking into account seasonal and solar activity modulations. Theremaining horizontal disturbance components DeltaX and DeltaY aremodeled with gated time delay networks taking local time and solar winddata as input. The observed geomagnetic field is not used as input tothe networks, which thus constitute explicit nonlinear mappings from thesolar wind to the locally observed geomagnetic disturbances. The ANNsare applied to data from Sodankyla Geomagnetic Observatory locatednear the peak of the auroral zone. It is shown that 73% of the DeltaXvariance, but only 34% of the DeltaY variance, is predicted from asequence of solar wind data. The corresponding results for prediction ofall transient variations XSq+DeltaX andYSq+DeltaY are 74% and 51%, respectively. The local timemodulations of the prediction accuracies are shown, and the qualitativeagreement between observed and predicted values are discussed. If drivenby real-time data measured upstream in the solar wind, the ANNs heredeveloped can be used for short-term forecasting of the locally observedgeomagnetic activity. (Less)

Auroral electrojet predictions with dynamic neural networks

Neural networks with internal feedback from the hidden nodes to theinput [Elman, 1990 are developed for prediction of the auroralelectrojet index AE from solar wind data. Unlike linear and nonlinearautoregressive moving-average (ARMA) models, such networks are free todevelop their own internal representation of the recurrent statevariables. Further, they do not incorporate an explicit memory for paststates; the memory is implicitly given by the feedback structure of thenetworks. It is shown that an Elman recurrent network can predict around70 of the observed AE variance using a single sample of solar winddensity, velocity, and magnetic field as input. A neural network withidentical solar wind input, but without a feedback mechanism, onlypredicts around 45 of the AE variance. It is also shown that fourrecurrent state variables are optimal: the use of more than four hiddennodes does not improve the predictions, but with less than that theprediction accuracy drops. This provides an indication that theglobal-scale auroral electrojet dynamics can be characterized by a smallnumber of degrees of freedom. (Less)

Recent global warming hiatus dominated by low‐latitude temperature trends in surface and troposphere data

Over the last 15 years, global mean surface temperatures exhibit only weak trends. Recent studies have attempted to attribute this so called temperature hiatus to several causes, amongst them incomplete sampling of the rapidly warming Arctic region. We here examine zonal mean temperature trends in satellite-based tropospheric data sets (based on data from (Advanced) Microwave Sounding Unit and Global Navigation Satellite System Radio Occultation instruments) and in global surface temperatures (HadCRUT4). Omission of successively larger polar regions from the global mean temperature calculations, in both tropospheric and surface data sets, shows that data gaps at high latitudes cannot explain the observed differences between the hiatus and the prehiatus period. Instead, the dominating causes of the global temperature hiatus are found at low latitudes. The combined use of several independent data sets, representing completely different measurement techniques and sampling characteristics, strengthens the conclusions.

Postmillennium changes in stratospheric temperature consistently resolved by GPS radio occultation and AMSU observations

Temperature changes in the lower and middle stratosphere during 2001-2016 are evaluated using measurements from GPS Radio Occultation (RO) and Advanced Microwave Sounding Unit (AMSU) aboard the Aqua satellite. After downsampling of GPS-RO profiles according to the AMSU weighting functions, the spatially and seasonally resolved trends from the two data sets are in excellent agreement. The observations indicate that the middle stratosphere has cooled in the time period 2002-2016 at an average rate of –0.14±0.12 to –0.36±0.14 K/decade, while no significant change was found in the lower stratosphere. The meridionally and vertically resolved trends from high-resolution GPS-RO data exhibit a marked inter-hemispheric asymmetry and highlight a distinct boundary between tropospheric and stratospheric temperature change regimes matching the tropical thermal tropopause. The seasonal pattern of trend reveals significant opposite-sign structures at high and low latitudes, providing indication of seasonally varying change in stratospheric circulation.

The Robotic Earthshine Telescope

Lund Observatory is presently designing and constructing a robotic telescope dedicated to studies of the Earths albedo by measuring the ratio between the intensity of the dark and bright sides of the Moon. The telescope will operate both in broadband and narrow-band modes over the entire visible wavelength range and will transmit observational results back to the operation team over the Internet. Design challenges, in particular related to choice of CCD and stray light suppression, are described, together with the design of the optics, control system, and enclosure. Finally we present results from laboratory tests. The telescope will go into operation in the first half of 2011.

Comparison study of COSMIC RO dry air climatologies based on average profile inversion

Global Navigation Satellite System (GNSS) Radio Occultation (RO) data enable the retrieval of near vertical profiles of atmospheric parameters like bending angle, refractivity, pressure and temperature. The retrieval step from bending angle to refractivity, however, involves an Abel integral, whose upper limit is infinity. RO data are practically limited to altitudes below about 80 km and the observed bending angle profiles show decreasing signal-to-noise ratio with increasing altitude. Some kind 5 of high-altitude background data are therefore needed, in order to perform this retrieval step (this approach is known as “highaltitude initialization”). Any bias in the background data will affect all RO data products beyond bending angle. A reduction of the influence of the background is therefore desirable in particular for climate applications. Recently a new approach for the production of GNSS radio occultation climatologies has been proposed. The idea is to perform the averaging of individual profiles in bending angle space and then propagate the mean bending angle profiles through 10 the Abel transform. Climatological products of refractivity, density, pressure, and temperature are directly retrieved from the mean bending angles. The averaging of a large number of profiles suppresses noise in the data, enabling observed bending angle data to be used up to 80 km without the need of a priori information. Some background information for the Abel integral is still necessary above 80 km. 15 This work is a follow-up study, having the focus on the comparison of the average profile inversion climatologies (API) from the two processing centers WEGC and DMI, studying monthly COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) data from January to March 2011. The impact of different backgrounds above 80 km is tested, and different implementations of the Abel integral are investigated. Results are compared for the climatological products against ECMWF analyses, MIPAS, and SABER data. 20 It is shown that different implementations of the Abel integral have little impact on the API climatologies. On the other hand, different extrapolations of the bending angle profile above 80 km play a key role on the resulting monthly mean refractivities above 35 km altitude. Below that respective altitude the API climatologies show a good agreement between the two processing centers WEGC and DMI. Due to the downward propagation within the retrieval, effects of the high altitude initialization lead to differences in dry temperature climatologies down to 20 km altitude. 25

The Earthshine Telescope Project

The Earthshine telescope project is a collaborative effort between Lund Observatory (LO) in Sweden and The Institute of Meteorology in Demark (DMI) with the purpose of constructing one or more robotic telescopes to record the albedo of the Earth over a long time. The objective is to measure long-term development of the global cloud coverage and reflectivity for climate modeling. A 1% change in the Earths albedo will result in an average temperature change of 0.5 K of the Earth, calling for high precision of the albedo measurements. This poses strict demands on the telescope design, in particular with respect to suppression of straylight. The paper describes our proposed optical and mechanical design of the Earthshine telescope, and presents a preliminary straylight analysis of the design.