In a report issued in 2009 entitled “Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks”, the National Research Council (NRC) highlighted the need to have profiles of water vapor and temperature in the boundary layer from a network of ground-based instruments at high temporal (<15 min) and vertical (order 100 to 200 m) resolution. This report suggested that the network needed to have approximately 400 stations in the continental US, providing an average spacing of about 150 km between stations. A thermodynamic profiling network such as this would be a great benefit to a wide range of public, academic, and private sector interests.

There are several different remote sensing technologies that have the capability to provide thermodynamic profiles in the boundary layer and thus meet the need outlined in the NRC report. These technologies include both active and passive techniques. The active techniques, water vapor Raman lidar (RL) and water vapor differential absorption lidar (DIAL), are both laser-based techniques and are capable of providing excellent data in research environments. However, since there are only a few (<5) truly operational water vapor RLs in the world and currently no operational water vapor DlALs, there is significant risk associated with a hypothetical network of these systems.

Passive remote sensors have an advanced level of operational readiness compared to RL and DIAL systems. Passive spectral microwave radiometers (MWRs) and spectral infrared radiometers (IRRs) are environmentally hardened systems and have been deployed in a wide range of locations from the tropics to the high latitudes over the last decade or longer. These instruments sense the downwelling radiance emitted by the atmosphere in water vapor, oxygen, and carbon dioxide absorption bands at high temporal resolution; these spectral observations are then inverted to retrieve profiles of water vapor and temperature. These retrieved profiles have lower vertical resolution and less information content than the active techniques, and there can be significant correlated errors in the retrieved profiles. However, MWR and IRR based techniques are attractive because of their operational readiness. Furthermore, an initial observation system simulation experiment (OSSE) demonstrated that a network of MWRs and/or IRRs collocated together with boundary layer wind profilers significantly improved the forecast of both the location and intensity of a convective wintertime convective event.

Even though the MWR and IRR techniques have been available for a decade, there remains a significant amount of research to be conducted. Research interests include (1) characterizing and improving the accuracy of the forward models used in the microwave and infrared, especially associated with the water vapor continuum; (2) developing synergistic retrieval techniques that use data from multiple sources (e.g., ground-based passive and active remote sensors, satellite instruments such as the newly launched CrlS and IASI, NWP model output); (3) evaluating the information content of the MWR and IRR spectral radiance observations; (4) improving the accuracy and quality of the retrievals in sub-optimal conditions (e.g., cloudy conditions for IRR methods, light precipitating conditions for MWR methods); (5) building methods to retrieve cloud properties in addition to thermodynamic profiles; (6) developing faster computational methods to improve timeliness of the retrievals; (7) characterizing the covariance in the instrument observations and retrieved products; (8) appraising different techniques to assimilating these profiles into numerical weather prediction models; (9) quantifying the cost/benefit ratio of having a network of MWRs, lRRs, and/or other instruments deployed across the continental US through the use of OSSEs in different synoptic and mesoscale situations to evaluate network density, instrument composition, and other parameters that would be important for the National Weather Service; (10) using data from these passive profilers to characterize the thermodynamic profiles during dynamically active weather conditions (e.g., during the Mid-Continental Convective Cloud Experiment [MC3E]); (11) investigating small-scale horizontal gradients from a small network of these instruments deployed during a field experiment; (12) evaluating tomographic retrieval methods to retrieve a “curtain” of water vapor and temperature along a line of passive thermodynamic profilers deployed during a field experiment; and (13) retrieving trace gas (e.g., carbon dioxide, methane) mixing ratios simultaneously with the thermodynamic profiles.

 

References

Loehnert U, Turner DD, Crewell S: Journal of Applied Meteorology and Climatology 48: 1017, doi:10.1175/2008JAMC2060.1, 2009

Hartung DC, et al: Monthly Weather Review 139: 2327, doi:10.1175/2011MWR3623.1, 2011

 

key words

Thermodynamic profiling; Passive remote sensing; Infrared spectral radiance; Microwave spectral radiance; Retrieval theory; Information content; Ground-based;

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Level:  Open to Postdoctoral and Senior applicants