ALBERT

Description: Airborne microwave radiometric measurements in the framework of the HAPEX-Sahel Experiment were performed by the Push Broom Microwave Radiometer (PBMR) and the PORTOS radiometer. The flights of both radiometers produced an original set of data covering the 1.4-90 GHz range of frequency. The East and West Central Super Sites were the areas most intensively observed by the microwave radiometers. Over those sites, several brightness temperature (TB) maps are available at seven dates distributed over a 1 month period in the middle of the rainy season. A comparison of the two radiometers demonstrates their radiometric quality and the precision of the localization of the microwave observations. At 1.4 GHz, the vegetation had very little effect on the soil microwave emission. Maps of soil moisture were developed using a single linear relationship between TB and the surface soil moisture. There is an important spatial heterogeneity in the soil moisture distribution, which is explained by both the soil moisture hydrodynamic properties and the localization of the precipitation fields. At 5.05 GHz, the vegetation must be accounted for to infer soil moisture from the microwave observations. A method based on a simple radiative transfer model and on microwave data has shown encouraging results.

Description: Six SIR-C L-band measurements over the Little Washita River watershed in Chickasha, Oklahoma during 11-17 April 1994 have been analyzed for studying the change of soil moisture in the region. Two algorithms developed recently for estimation of moisture content in bare soil were applied to these measurements and the results were compared with those sampled on the ground. There is a good agreement between the values of soil moisture estimated by either one of the algorithms and those measured from ground sampling for bare or sparsely vegetated fields. The standard error from this comparison is on the order of 0.05-0.06 cu cm/cu cm, which is comparable to that expected from a regression between backscattering coefficients and measured soil moisture. Both algorithms provide a poor estimation of soil moisture or fail to give solutions to areas covered with moderate or dense vegetation. Even for bare soils the number of pixels that bear no numerical solution from the application of either one of the two algorithms to the data is not negligible. Results from using one of these algorithms indicate that the fraction of these pixels becomes larger as the bare soils become drier. The other algorithm generally gives a larger fraction of these pixels when the fields are vegetation-covered. The implication and impact of these features are discussed in this article.

Description: The first copy of the SSMIS (Special Sensor Microwave/Imager/Sounder) was launched on board the DMSP (Defense Meteorological Satellite Project) F-16 satellite in October 2003. During March-April 2004, six 5-hour SSMIS under-flights were conducted with the CoSMIR on board the NASA ER-2 aircraft over the coastal region of California. CoSMIR has nine channels at the frequencies of 50.3, 52.8, 53.6, 91.665 (V and H polarization), 150, 183.3+/-1, 183.3+/-3, and 183.3+/-6.6 GHz. All except the two 91.665 GHz channels are horizontally polarized. The instrument was carefully calibrated with LN2 target in the laboratory before the flights. Three of the aircraft flights passed over Lakes Pyramid and Tahoe that could be used to validate the in-flight sensor calibration. Immediately after these flights, an inter-comparison of the calibrated SSMIS and CoSMIR brightness temperatures (T(sub b)) followed. The results showed that, for channels at frequencies 〉 or equal to 91.665 GHz, the SSMIS and CoSMIR T(sub b) values tracked each other very well; for some channels there were some bias with magnitude generally less than 3-4 K (SSMIS values were higher). For the three 50-54 GHz channels, the SSMIS T(sub b) values were higher and frequency-dependent. For the least opaque channel at 50.3 GHz, the SSMIS T(sub b)'s over the ocean surface were higher than those of CoSMIR by more than 20 K under the clear-sky conditions. The most plausible explanation for this to happen is to assume that the 50-54 GHx channels of the SSMIS are vertically polarized. This assumption appears to be consistent with independent radiative transfer calculations. Attempts to estimate vertically polarized radiometric responses for 50-54 GHz channels of the SSMIS based on the CoSMIR observations are not plausible and results not reliable because of the highly variable ocean surface conditions (e.g., wind-induced emissivity changes). A conversion of the CoSMIR 50-54 GHz channels from horizontal to vertical polarization, and a subsequent repetition of the SSMIS under-flights are the right approach for the calibration/validation of the 50-54 GHz channels of the SSMIS. Details of the SSMIS-CoSMIR inter-comparison will be presented.

Description: In this paper we explore the application of combined millimeter-wave radar and radiometry to remotely measure snowfall. During January-February of 2003, a field campaign was conducted with the NASA P-3 aircraft in Wakasa Bay, Japan for the validation of the AMSRE microwave radiometer on board the Aqua satellite. Among the suite of instruments-on board the P-3 aircraft were the Millimeter-wave Imaging Radiometer (MIR) from the NASA Goddard Space Flight Center and the 94 GHz Airborne Cloud Radar (ACR) which is co-owned and operated by NASA Jet Propulsion Laboratory/University of Massachusetts. MIR is a total power, across-track scanning radiometer that measures radiation at the frequencies of 89, 150, 183.3 +/- 1, 183.3 +/- 3, 183.3 +/-7, 220, and 340 GHz. The MIR has flown many successful missions since its completion in May 1992. ACR is a newer instrument and flew only a few times prior to the Wakasa Bay deployment. These two instruments which are particularly well suited for the detection of snowfall functioned normally during flights over snowfall and excellent data sets were acquired. On January 14, 28, and 29 flights were conducted over snowfall events. The MIR and ACR detected strong signals during periods of snowfall over ocean and land. Results from the analysis of these concurrent data sets show that (1) the scattering of millimeter-wave radiation as detected by the MIR is strongly correlated with ACR radar reflectivity profiles, and (2) the scattering is highly frequency-dependent, the higher the frequency the stronger the scattering. Additionally, the more transparent channels of the MIR (e.g., 89, 150, and 220 GHz) are found to display ambiguous signatures of snowfall because of their exposure to surface features. Thus, the snowfall detection and retrievals of snowfall parameters, such as the ice water path (IWP) and median mass diameter (D(me)) are best conducted at the more opaque channels near 183.3 GHz and 340 GHz. Retrievals of IWP and D(me) using the MIR measurements at 183.3 and 340 GHZ are currently in progress, and the results will be compared with those derived from the ACR reflectivity profiles. Implication from this comparison will be discussed.

Description: A rich dataset was obtained with observations from the MIR (Millimeter-wave Imaging Radiometer, 89, 150, 183.3$\pm$1, 183.3$\pm$3,183.3$\pm$7, and 220 apprx.GHz), the AMPR (Advanced Microwave Precipitation Radiometer, 10.7, 19.35, 37, and 85 approx. GHz), and the EDOP (ER-2 Doppler Radar, 9.6 approx. GHz) on board the ER-2 aircraft during the CAMEX-3/TEFLUN-B (Convection and Moisture Experiment/Texas and Florida Underflights) TRMM (Tropical Rainfall Measuring Mission) field campaign. Measurements over the ocean from these three instruments on 26 August 1998 were used in our iterative retrieval algorithm to estimate hydrometeor drop size profiles, The algorithm attempts to minimize the difference between the observations and forward radiometer and radar calculations based on the estimated profile. The high frequency MIR observations provide detailed information about the high altitude ice microphysics, while the AMPR is mostly used to define liquid hydrometeor characteristics. The EDOP provides an initial estimate of the profile and as a consistency check throughout the iterative cycle. The retrieval algorithm, specific results for convective and anvil cases, and general implications of this work will be presented.

Description: Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG). Its 100-year global warming potential (GWP) is 25 times larger than that for carbon dioxide. The 100-yr integrated GWP of CH4 is sensitive to changes in OH levels. Methane's atmospheric growth rate was estimated to be more than 10 ppb yr(exp -1) in 1998 but less than zero in 2001, 2004 and 2005 (Kirschke et al., 2013). Since 2006, the CH4 is increasing again. This phenomena is yet not well understood. Oxidation of CH4 by OH is the main loss process, thus affecting the oxidizing capacity of the atmosphere and contributing to the global ozone background. Current models typically use an annual cycle of offline OH fields to simulate CH4. The implemented OH fields in these models are typically tuned so that simulated CH4 growth rates match that measured. For future and climate simulations, the OH tuning technique may not be suitable. In addition, running full chemistry, multi-decadal CH4 simulations is a serious challenge and currently, due to computational intensity, almost impossible.

Description: Volcanic SO2 column amount and injection height retrieved from the Ozone Monitoring Instrument (OMI) with the Extended Iterative Spectral Fitting (EISF) technique are used to initialize a global chemistry transport model (GEOS-Chem) to simulate the atmospheric transport and lifecycle of volcanic SO2 and sulfate aerosol from the 2008 Kasatochi eruption, and to subsequently estimate the direct shortwave, top-of-the-atmosphere radiative forcing of the volcanic sulfate aerosol. Analysis shows that the integrated use of OMI SO2 plume height in GEOS-Chem yields: (a) good agreement of the temporal evolution of 3-D volcanic sulfate distributions between model simulations and satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP), and (b) an e-folding time for volcanic SO2 that is consistent with OMI measurements, reflecting SO2 oxidation in the upper troposphere and stratosphere is reliably represented in the model. However, a consistent (approx. 25 %) low bias is found in the GEOS-Chem simulated SO2 burden, and is likely due to a high (approx.20 %) bias of cloud liquid water amount (as compared to the MODIS cloud product) and the resultant stronger SO2 oxidation in the GEOS meteorological data during the first week after eruption when part of SO2 underwent aqueous-phase oxidation in clouds. Radiative transfer calculations show that the forcing by Kasatochi volcanic sulfate aerosol becomes negligible 6 months after the eruption, but its global average over the first month is -1.3W/sq m, with the majority of the forcing-influenced region located north of 20degN, and with daily peak values up to -2W/sq m on days 16-17. Sensitivity experiments show that every 2 km decrease of SO2 injection height in the GEOS-Chem simulations will result in a approx.25% decrease in volcanic sulfate forcing; similar sensitivity but opposite sign also holds for a 0.03 m increase of geometric radius of the volcanic aerosol particles. Both sensitivities highlight the need to characterize the SO2 plume height and aerosol particle size from space. While more research efforts are warranted, this study is among the first to assimilate both satellite-based SO2 plume height and amount into a chemical transport model for an improved simulation of volcanic SO2 and sulfate transport.

Description: In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.

Description: Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

Description: This paper demonstrates the technique to estimate ground surface and vegetation scattering components, based on the backscattering model and the radar decomposition theory, under configuration of multi-temporal L-band polarimetric SAR measurement. This technique can be used to estimate soil moisture of vegetated surface.