Testing Climate Models Using Infrared Spectra and GNSS Radio Occultation

Exploration of Climate Data Using Interactive Visualization*

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2009jtecha1374.1 ◽

2010 ◽

Vol 27 (4) ◽

pp. 667-679 ◽

Cited By ~ 28

Author(s):

Florian Ladstädter ◽

Andrea K. Steiner ◽

Bettina C. Lackner ◽

Barbara Pirscher ◽

Gottfried Kirchengast ◽

...

Keyword(s):

Radio Occultation ◽

Climate Models ◽

Statistical Treatment ◽

Visual Exploration ◽

Climate Data ◽

Classical Statistics ◽

The Common ◽

To Come ◽

Interactive Browsing ◽

Different Sources

Abstract 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.

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Prioritizing Data for Improving the Multidecadal Predictive Capability of Atmospheric Models

Journal of Climate ◽

10.1175/jcli-d-14-00444.1 ◽

2015 ◽

Vol 28 (13) ◽

pp. 5077-5090 ◽

Cited By ~ 2

Author(s):

Stephen S. Leroy ◽

Gianluca Redaelli ◽

Barbara Grassi

Keyword(s):

Radio Occultation ◽

Climate Models ◽

Coupled Model ◽

Surface Air Temperature ◽

Longwave Radiation ◽

Climate Prediction ◽

Atmospheric Models ◽

Predictive Capability ◽

Long Term Trends

Abstract The prioritization accorded to observation types currently being considered for a space-based climate observing system is extended from a previous study. Hindcast averages and trends from 1970 through 2005 of longitude–latitude maps of 200-hPa geopotential height and of net downward shortwave and longwave radiation at the top of the atmosphere are investigated as relevant tests of climate models for predicting multidecadal surface air temperature change. To discover the strongest tests of climate models, Bayes’s theorem is applied to the output provided by phase 5 of the Coupled Model Intercomparison, and correlations of hindcasts and multidecadal climate prediction are used to rank the observation types and long-term averages versus long-term trends. Spatial patterns in data are shown to contain more information for improving climate prediction than do global averages of data, but no statistically significant test is found by considering select locations on the globe. Eigenmodes of intermodel differences in hindcasts may likely serve as tests of climate models that can improve interdecadal climate prediction, in particular the rate of Arctic tropospheric expansion, which is measurable by Earth radio occultation.

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Tropical temperature variability in the UTLS: New insights from GPS radio occultation observations

Journal of Climate ◽

10.1175/jcli-d-20-0385.1 ◽

2020 ◽

pp. 1-92

Author(s):

Barbara Scherllin-Pirscher ◽

Andrea K. Steiner ◽

Richard A. Anthes ◽

M. Joan Alexander ◽

Simon P. Alexander ◽

...

Keyword(s):

Gravity Waves ◽

Radio Occultation ◽

Climate Models ◽

Southern Oscillation ◽

Thermal Structure ◽

Chemical Constituents ◽

Dimensional Structure ◽

Quasi Biennial Oscillation ◽

Radiative Balance ◽

Gps Radio Occultation

AbstractGlobal Positioning System (GPS) radio occultation (RO) observations, first made of Earth’s atmosphere in 1995, have contributed in new ways to the understanding of the thermal structure and variability of the tropical upper troposphere–lower stratosphere (UTLS), an important component of the climate system. The UTLS plays an essential role in the global radiative balance, the exchange of water vapor, ozone and other chemical constituents between the troposphere and stratosphere, and the transfer of energy from the troposphere to the stratosphere. With their high accuracy, precision, vertical resolution, and global coverage, RO observations are uniquely suited for studying the UTLS and a broad range of equatorial waves, including gravity waves, Kelvin waves, Rossby and mixed Rossby gravity waves, and thermal tides. Because RO measurements are nearly unaffected by clouds, they also resolve the upper-level thermal structure of deep convection and tropical cyclones, as well as volcanic clouds. Their low biases and stability from mission to mission make RO observations powerful tools for studying climate variability and trends, including the annual cycle and intra-seasonal to inter-annual atmospheric modes of variability such as the quasi-biennial oscillation (QBO), Madden-Julian oscillation (MJO), and El Niño-Southern oscillation (ENSO). These properties also make them useful for evaluating climate models and detection of small trends in the UTLS temperature, key indicators of climate change. This paper reviews the contributions of RO observations to the understanding of the three-dimensional structure of tropical UTLS phenomena and their variability over time scales ranging from hours to decades and longer.

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