EXPERIMENT Radiative Heating in UnderExplored Bands Campaign (RHUBC) Period: February 15 – March 15, 2007 Location: ARM NSA, Barrow, Alaska GOALS Comparison of Microwave and Millimeter wavelength radiometers in deriving PWV and LWP Retrieval of Temperature and Humidity Profiles Remote Sensing of Water Vapor, Cloud Liquid, and Temperature during RHUBC by Microwave and Millimeter Wave Radiometers E. R. Westwater 1,4, D. Cimini 2, V. Mattioli 3, M. Klein 4, V. Leuski 4, A. J. Gasiewski 1,4 and D. Turner 5 1 Department of Electrical and Computer Engineering, University of Colorado at Boulder, USA 2 CETEMPS, University of L’Aquila, L’Aquila, Italy 3 Dipartimento di Ingegneria Elettronica e dell'Informazione, Università di Perugia, Perugia, Italy 4 Center for Environmental Technology, University of Colorado, USA 5 University of Wisconsin, Madison, Wisconsin, USA MOTIVATION Retrievals of PWV Fig.1 List of instruments and experimental set-up deployed during RHUBC. Fig.2 Real time display during RHUBC of GSR Tb data. Note the menu of available choices of available data. Fig.4 Scatter plot comparisons between the GSR (blue) and the MWR LOS retreivals of PWV compared with RS92 Radiosondes MWR MWRP GSR RETRIEVALS OF LWP Corresponding author: Fig.3 Comparison of PWV retrievals from the MWR LOS, the GSR, and RS92 Sondes on Julian day 65, 2007 ARM Science Team Meeting, March 10-14, 2008, Norfolk, VA RETRIEVALS OF LWP AND T AND Q PROFILES CONCLUSIONS As a continuation of our 1999 and 2004 NSA experiments, we participated In RHUBC, where the principal focus was on low amounts of Precipitable Water Vapor (PWV < 2 mm), and a secondary goal of small amounts of cloud liquid. Several improvements were made in the GSR, both in number of frequencies, and performance of selected channels. The GSR was successfully operated from February 20 to July 1, PWV retrievals of the GSR compared well with RS92 Radiosondes and yield a relative accuracy of about 5%. Comparisons of LWP from the GSR, as well as MIXCRA and MWRRET are quite encouraging for LWP > 20 g/m 2. The use of the 340 GHz channels is promising for the smaller LWP amount. Also encouraging are the preliminary 1DVAR retrievals of temperature and specific humidity. Further development will focus on cloud liquid and the complete set of 27 GSR channels. InstrumentFrequencies (GHz)Parameters ARM Microwave Radiometer (MWR) 23.8, 31.4PWV, LWP CET Ground-based Scanning Radiometer (GSR) , , , , , , , , , , T(z), LWP ARM Microwave Radiometer Profiler (MWRP) , ,23.835, , , , , , , , , PWV, LWP, T(z) CET GSR89 (H & V)LWP CET GSR ± ( 0.55, ± 1.0, ± 3.05, ± 4.7, ± 7.0, ± 12.0, ± 16.0) PWV CET GSR340 (H & V)LWP CET GSR ± ( 4.0, ± 9.0, ± 17.0)PWV ARM GVR ± ( 1,3,7, 14)PWV, LWP CET GSR 10  m Cloud ARM AERI cm- 1 Cloud GSR RETRIEVAL METHOD A Priori Linear Statistical Retrieval using Tb’s as predictors Historical data set of Vaisala RS90/RS92 taken at NSA (Substantial QC was necessary) RTE model based on Liljegren et al. (2005) Tb’s adjusted to Liljegren et al model based on WVIOP_2004 data comparisons Covariance matrix of experimental errors determined from WVIOP_2004 data MWR LOS RETRIEVAL METHOD A priori Linear Statistical Retrieval using τ (optical depth) as predictors. Monthly values of Mean Radiating Temperature RTE model based on Liljegren et al. (2005) CLEAR CONDITIONS FROM VCEIL AND IRT Fig. 5. Left. Scatter Plots of LWP retrievals from the MWR-LOS (red), MWRRET(blue) and the MIXCRA (BLACK) vs. the GSR. Right: MIXCRA VS. GSR. Note the excellent agreement between MIXCRA and the GSR Fig. 6. Left:GSR vs. MIXCRA. Right: MIXCRA vs. MWRRET. Note the outliers associated with the MIXCRA in both figures. This could be due to either an algorithm or an AERI hatch problem. LWP LESS THAN 60 g/m 2 In Fig. 6, we showed LWP retrieval for contents < 60 g/m 2. However, on Julian day 73, there was a significant amount of liquid shown by the MWR, the GSR, and the AERI. Unfortunately, the MWRRET data did not pass quality control and are not available for this day. We show in Figs. 7 retrieval comparisons for the higher liquid amounts. Fig. 7. Left Retrievals of GSR-MIXCRA. Right: LOS-GSR Fig. 8. 1DVAR retrievals profiles of Temperature and Specific Humidity. We have recently developed One Dimensional Variational (1D-VAR) retrievals of GSR data. This method is fully physical and is based on the Liljegren et al. (2005) RTE model. It initial guess is the NCEP forecast model, and the algorithm iterates until the residuals are less that the estimated GSR noise levels. These retrievals use zenith GSR data up to GHz.