IDENTIFYING ICE HYDROMETEOR SIGNATURES ABOVE SUMMIT, GREENLAND USING A MULTI-INSTRUMENT APPROACH By CLAIRE PETTERSEN A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science (Atmospheric and Oceanic Sciences) at the UNIVERSITY OF WISCONSIN-MADISON 2014 APPROVED         Advisor  Title:     Ralf  Bennartz,  Ph.D.     University  of  Wisconsin  –  Madison     Department  of  Atmospheric  and  Oceanic  Sciences                 ___________________________   Advisor  Signature         ___________________________   Date i   ABSTRACT Ground-based microwave radiometers are commonly used to retrieve precipitable water vapor and liquid water path. These retrievals, however, may be adversely affected by ice hydrometeors commonly observed in mixed phase clouds. Research on the effect of ice hydrometeors on the microwave signal is insufficient. We establish that ice hydrometeors produce enhanced brightness temperatures in high frequency ground-based passive microwave observations. This effect is evident in several years of summer season microwave radiometer data collected at Summit Station, Greenland. Using a multi- instrument suite and coupling measurements with well-established gas and liquid absorption models, we can quantify the ice hydrometeor signature. Better knowledge of these ice effects on the passive microwave observations aids in improvement of retrieved properties, such as liquid water path, when ice is present in the column. Additionally, the use of the active cloud radar guides what regimes exhibit predominately ice precipitation. By clearly identifying the ice signature in the high frequency microwave, we have established a standard by which to compare ice habit models and particle size distributions. ii   ACKNOWLEDGEMENTS First, I would like to thank my advisor, Professor Ralf Bennartz, who exudes an enthusiasm for atmospheric science that is contagious and whose encouragement was key to my involvement with the Atmospheric and Oceanic Sciences Department and the ICECAPS Project. Researcher Mark Kulie spent many an hour (of which he had few) helping me sort through the details of the radiative transfer and ice models. Mark radiates excitement for our field of study that is energizing and helped me keep on trying new avenues when it felt like all possibilities were exhausted. Co-Principal Investigators with the ICECAPS Project, Dave Turner and Matt Shupe, lent their expertise to many instruments and retrievals and science related to this project and both had excellent suggestions for further research and related topics. Professor Grant Petty aided me with questions about the ice habits and scattering properties and is excited to continue to collaborate on further ice-related studies. Professor Tristan L’Ecuyer is not only a close friend, but also an excellent sounding board over a beer with limitless excitement about and ideas for this and future work. I am super fortunate to have a best friend and partner who works in the same field of study: Researcher Aronne Merrelli and I spend many a meal, beer, walk, etc. chatting about atmospheric science including a lot related to this research and whose help without which this research would not have been possible. Finally, my supervisor Fred Best (Associate Director of Technology at SSEC) has not only been supportive, but actively interested in the evolution of this work and has encouraged me to pursue scientific questions which are of interest me, even if they are not directly related to his projects. iii   TABLE OF CONTENTS ABSTRACT  ...................................................................................................................................  i   ACKNOWLEDGEMENTS  ..........................................................................................................  ii   TABLE  OF  CONTENTS  ...........................................................................................................  iii   1.  Introduction  ..........................................................................................................................  1   1.1  Arctic  Importance  ......................................................................................................................  1   1.2  Enhanced  Downwelling  Radiance  in  the  Presence  of  Ice  .............................................  2   2.  Datasets  and  Methods  .......................................................................................................  8   2.1  ICECAPS  Project  and  Instrument  Suite  ...............................................................................  8   2.2  Radiative  Transfer  Model  for  Gas  and  Liquid  ................................................................  12   2.3    Successive  Order  of  Interaction  Radiative  Transfer  Model  .....................................  13   2.3  Tables  and  Figures  ..................................................................................................................  14   3.  Ice  Hydrometeor  Behavior  as  Observed  by  ICECAPS  ...........................................  18   3.1  Characterization  of  Ice  Precipitation  at  Summit  ..........................................................  18   3.2  Enhanced  Brightness  Temperatures  at  150GHz  ...........................................................  20   3.3  Depressed  Brightness  Temperatures  in  Other  Channels  ..........................................  21   3.5  Figures  ........................................................................................................................................  23   4.  Liquid  Water  Path  Retrieval  Influenced  by  Ice  ......................................................  28   4.1  Ice  Signature  Influence  on  Retrieved  Liquid  Water  ....................................................  28   4.2  Ice  Influenced  Liquid  Water  Path  Correction  ................................................................  30   4.3  Figures  ........................................................................................................................................  33   5.  Brightness  Temperatures  Differences  as  Measureable  Ice  Signature  ...........  36   5.1  Brightness  Temperature  Differences  with  Corrected  LWP  ......................................  36   5.2    Comparison  of  Ice  Signatures  Observed  with  Scattering  Model  Results  .............  36   5.3  Tables  and  Figures  ..................................................................................................................  40   6.  Conclusions  ........................................................................................................................  45   Appendix  A:  Acronyms  ........................................................................................................  47   REFERENCES  ...........................................................................................................................  48 1   1. Introduction   Quantifying the effect of ice hydrometeors on microwave radiation in the atmosphere is a non-trivial task, even with modern high-resolution active and passive instruments. Ice hydrometeors change the path and net effect of downwelling radiation, but isolating the signature of the ice is challenging. In many cases the signature is small relative to the signatures of liquid water and gas absorption. Additionally, the ice hydrometeor signal can interfere with retrievals of other atmospheric properties. By better understanding ice hydrometeor characteristics, we can separate their effect and improve atmospheric retrievals based on microwave remote sensing instruments. In turn, this will improve the derived climatologies of cloud properties from microwave remote sensing, especially from ground- based sensors. To address these topics, this study will focus on observations from an instrument suite located in the Arctic on the Greenland ice cap, as it is a unique and isolated environment in which to observe ice hydrometeor characteristics. 1.1 Arctic Importance   The Greenland Ice Sheet (GIS) is of particular interest as it has relatively large impacts on the Earth’s climate system (Church et al., 2001). Understanding the characteristics of precipitation above the GIS is a key factor in quantifying the full radiation and ice mass balance. The site of the Greenland Ice Sheet Project 2 (GISP2) ice core project has expanded to a continuously operational science facility, Summit Station, dedicated to studying the atmosphere and ice sheet properties of the GIS (see Figure 1.1), which has been key to temperature and chemical dating throughout Earth’s history as well as understanding 2   climate processes (Dansgaard et al., 1993). Summit Station is home to many atmospheric and snow science instruments, including the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS; Shupe et al., 2013) suite purposely co-located at Summit Station to continue to aid in understanding how the GIS cryosphere and atmosphere change over time. Since 2010, the ICECAPS suite of instruments has been monitoring a variety of atmospheric parameters to further our knowledge of atmospheric processes above the GIS (Shupe et al., 2013). The ICECAPS project will remain at Summit until at least 2018, thus providing a comprehensive dataset and analyses of the atmosphere over central Greenland and expanding the network of past and existing high-latitude atmospheric suites (i.e., Eureka, Canada and Barrow, Alaska) already helping to characterize Arctic atmospheric processes (Shupe et al., 2011). 1.2 Enhanced Downwelling Radiance in the Presence of Ice A commonly implemented technique for characterizing ice hydrometers from satellites is to use high-frequency channels (89GHz and greater) in passive microwave instruments and look for depressed brightness temperatures (Hong et al., 2005; Kulie et al., 2010). This technique is based on the idea that while liquid and gas in the atmospheric column will emit a relatively warm brightness temperature, the ice hydrometeors will scatter surface emission away from the satellite sensor and therefore depress the brightness temperature artificially. The same technique can be used from the ground looking up, however, with the opposite effect. Kneifel et al. (2010) demonstrated the presence of a signature from ice hydrometeors for a case study of snowfall in the Alps using ground-based microwave radiometers (MWRs). The high-frequency MWR, 90 and 150 GHz, channels are 3   “window channels” that see through the atmosphere nearly unimpeded to space; however, when ice or liquid water is present these channels see a higher brightness temperature (see Figure 1.2). Consequently, if there are ice hydrometeors present, they will have two effects on the observed brightness temperatures: emission of radiation and scattering some of the surface radiation back at the instrument. These two effects will thus enhance the measured brightness temperature compared to a column with no ice. Since some of the ice signature is the scattered surface radiation, it is related to both the surface temperature and emissivity. Therefore, this makes the ice signature challenging to model because it depends on both properties of the ice hydrometeors and the surface. In general, the ice hydrometeors will have fairly high single scatter albedo (SSA) at high microwave frequencies, regardless of habit and size distribution (see Figure 1.3), and will therefore scatter some of the surface radiation back to the instrument. The surface emissivity of different types of snow seen at Summit varies in the range of 0.60 to 0.91 for the higher frequency passive microwave channels used in this study (Yan, 2008). Additionally, the ice will have some emission, which will increase the brightness temperature a small amount. Due to the combination of these two effects – the scattering of radiation back to the surface and the slight emission from the ice hydrometeors – the measurements from ground-based high frequency MWRs will exhibit an enhanced brightness temperature. We propose that by combining the observed data from instruments in the ICECAPS suite with radiative transfer models of the gas and liquid in the atmosphere, this enhanced brightness temperature from the ice hydrometeors can be isolated and quantified. Because the ice signature is also dependent on ice crystal habit and size distribution, relying on a 4   small number of precipitation events to derive the ice signature may bias the result toward specific precipitation situations. The large dataset from the ICECAPS Project allows for the average ice signature to be computed over many precipitation events, thus reducing this potential sampling bias. 5   1.4 Figures   Figure  1.1:  Location of ICECAPS Suite at Summit Station, Greenland (Figure 1. from Shupe et al., 2013).