B. C. Lackner

Atmospheric temperature change detection with GPS radio occultation 1995 to 2008

[1] Existing upper air records of radiosonde and operational satellite data recently showed a reconciliation of temperature trends but structural uncertainties remain. GPS radio occultation (RO) provides a new high-quality record, profiling the upper troposphere and lower stratosphere with stability and homogeneity. Here we show that climate trends are since recently detected by RO data, consistent with earliest detection times estimated by simulations. Based on a temperature change detection study using the RO record within 1995―2008 we found a significant cooling trend in the tropical lower stratosphere in February while in the upper troposphere an emerging warming trend is obscured by El Nino variability. The observed trends and warming/cooling contrast across the tropopause agree well with radiosonde data and basically with climate model simulations, the latter tentatively showing less contrast. The performance of the short RO record to date underpins its capability to become a climate benchmark record in the future.

Atmospheric Climate Change Detection by Radio Occultation Data Using a Fingerprinting Method

The detection of climate change signals in rather short satellite datasets is a challenging task in climate research and requires high-quality data with good error characterization. Global Navigation Satellite System (GNSS) radio occultation (RO) provides a novel record of high-quality measurements of atmospheric parameters of the upper-troposphere‐lower-stratosphere (UTLS) region. Because of characteristics such as long-term stability, self calibration, and a very good height resolution, RO data are well suited to investigate atmosphericclimatechange.ThisstudydescribesthesignalsofENSOandthequasi-biennialoscillation (QBO) in the data and investigates whether the data already show evidence of a forced climate change signal, using an optimal-fingerprint technique. RO refractivity, geopotential height, and temperature within two trend periods (1995‐2010 intermittently and 2001‐10 continuously) are investigated. The data show that an emerging climate change signal consistent with the projections of three global climate models from the Coupled Model Intercomparison Projectcycle 3 (CMIP3)archive isdetectedfor geopotentialheightofpressure levelsat a 90% confidence level both for the intermittent and continuous period, for the latterso far in a broad 508S‐508 Nb and only. Such UTLS geopotential height changes reflect an overall tropospheric warming. 90% confidence is not achieved for the temperature record when only large-scale aspects of the pattern are resolved. When resolving smaller-scale aspects, RO temperature trends appear stronger than GCM-projected trends, the difference stemming mainly from the tropical lower stratosphere, allowing for climate change detection at a 95% confidence level. Overall, an emerging trend signal is thus detected in the RO climate record, which is expected to increase further in significance as the record grows over the coming years. Small natural changes during the period suggest that the detected change is mainly caused by anthropogenic influence on climate.

Exploration of Climate Data Using Interactive Visualization

In atmospheric and climate research, the increasing amount of data available from climate models and observations provides new challenges for data analysis. The authors present interactive visual exploration as an innovative approach to handle large datasets. Visual exploration does not require any previous knowledge about the data, as is usually the case with classical statistics. It facilitates iterative and interactive browsing of the parameter space to quickly understand the data characteristics, to identify deficiencies, to easily focus on interesting features, and to come up with new hypotheses about the data. These properties extend the common statistical treatment of data, and provide a fundamentally different approach. The authors demonstrate the potential of this technology by exploring atmospheric climate data from different sources including reanalysis datasets, climate models, and radio occultation satellite data. Results are compared to those from classical statistics, revealing the complementary advantages of visual exploration. Combining both the analytical precision of classical statistics and the holistic power of interactive visual exploration, the usual workflow of studying climate data can be enhanced.

Trend Indicators of Atmospheric Climate Change Based on Global Climate Model Scenarios

The upper troposphere-lower stratosphere (UTLS) region is reacting particularly sensitive to climate change and variations of its key parameters are very good candidates for the monitoring and diagnosis of climate change. This study aims at revealing the most promising atmospheric climate change indicators in this region which are accessible by radio occultation (RO) observations. RO based climatologies show the highest data quality in the UTLS. Due to the availability of continuous RO data only since the end of 2001, longer-term climatologies of three representative global climate models were investigated in this respect. We demonstrate that the RO method can valuably contribute to climate monitoring by providing climatologies of a set of atmospheric parameters such as refractivity, geopotential height, and temperature, which differ in sensitivity at different heights and in different regions and cover the UTLS as a whole.

SimVis: An Interactive Visual Field Exploration Tool Applied to Climate Research

Climate research often deals with large multi-dimensional fields describing the state of the atmosphere. A novel approach to gain information about these large data sets has become feasible only recently using 4D visualization techniques. The Simulation Visualization (SimVis) software tool, developed by the VRVis Research Center (Vienna, Austria), uses such techniques to provide access to the data interactively and to explore and analyze large three-dimensional time-dependent fields. Non-trivial visualization approaches are applied to provide a responsive and useful interactive experience for the user. In this study we used SimVis for the investigation of climate research data sets. An ECHAM5 climate model run and the ERA-40 reanalysis data sets were explored, with the ultimate goal to identify parameters and regions reacting most sensitive to climate change, representing robust indicators. The focus lies on the upper troposphere-lower stratosphere (UTLS) region, in view of future applications of the findings to radio occultation (RO) climatologies. First results showing the capability of SimVis to deal with climate data, including trend time series and spatial distributions of RO parameters are presented.

Communicating Climate Change in a Museum Setting—A Case Study

Climate change receives ample attention in academia and media. However, the dissemination of scientific findings to decision makers and the general public is often found wanting. Therefore, it is crucial to effectively communicate climate science, the impacts of climate change, possible solutions, and individual and collective responsibilities to warrant action. The bilingual exhibition “KliMacht | CliMatters” strove to tackle these very challenges, putting young people on the forefront as the primary target audience. The exhibition had over 30 exhibits with an emphasis on interactive objects and games, but also included standalone exhibits and posters. This paper discusses the potential of a museum exhibition to communicate climate change to a general public and spur action against climate change. It describes the scientific design, development and lessons learnt. In specific, it addresses the process of conceptualizing a coherent message and deciding on an exhibition as the medium of communication; challenges faced during preparation of exhibits; collaboration in an interdisciplinary team; and experiences from visitor interaction. Specific exhibits are discussed in detail to help identify effective and non-effective elements with respect to the transfer of knowledge. These insights can serve as a model for future endeavours aimed at communicating climate change.

Correction to “Atmospheric temperature change detection with GPS radio occultation 1995 to 2008”

Citation: Steiner, A. K., G. Kirchengast, B. C. Lackner, B. Pirscher, M. Borsche, and U. Foelsche (2010), Correction to “Atmospheric temperature change detection with GPS radio occultation 1995 to 2008,” Geophys. Res. Lett., 37, L03704, doi:10.1029/2010GL042427. [1] In the paper “Atmospheric temperature change detection with GPS radio occultation 1995 to 2008” by A. K. Steiner et al. (Geophys. Res. Lett., 36, L18702, doi:10.1029/2009GL039777), Figure S7 of the auxiliary material is incorrect and the corrected version appears here.

The GPS radio occultation record – a novel dataset for atmospheric change detection

Fig. 1: Radio signals from a GPS satellite are received onboard a LEO satellite such as CHAMP. An occultation occurs whenever a GPS satellite sets (or rises from) behind the horizon and is occulted by the Earth’s limb as viewed from the receiver. The relative movement of the satellites provides a scan through the atmosphere. Inserts illustrate a retrieved RO CHAMP temperature profile for a particular RO event (A), a distribution of RO events in February 2004 (B), and a monthly mean temperature field for February 2004 (C). TRANSMITTER A