The Determination of Surface Salinity with the European SMOS Space Mission

The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission aims at obtaining global maps of soil moisture and sea surface salinity from space for large-scale and climatic studies. It uses an L-band (1400–1427 MHz) Microwave Interferometric Radiometer by Aperture Synthesis to measure brightness temperature of the earth’s surface at horizontal and vertical polarizations ( h and v). These two parameters will be used together to retrieve the geophysical parameters. The retrieval of salinity is a complex process that requires the knowledge of other environmental information and an accurate processing of the radiometer measurements. Here, we present recent results obtained from several studies and field experiments that were part of the SMOS mission, and highlight the issues still to be solved

Quantitative comparisons of satellite observations and cloud models

2011 Fall.Includes bibliographical references.Microwave radiation interacts directly with precipitating particles and can therefore be used to compare microphysical properties found in models with those found in nature. Lower frequencies (< 37 GHz) can detect the emission signals from the raining clouds over radiometrically cold ocean surfaces while higher frequencies (≥ 37 GHz) are more sensitive to the scattering of the precipitating-sized ice particles in the convective storms over high-emissivity land, which lend them particular capabilities for different applications. Both are explored with a different scenario for each case: a comparison of two rainfall retrievals over ocean and a comparison of a cloud model simulation to satellite observations over land. Both the Goddard Profiling algorithm (GPROF) and European Centre for Medium-Range Weather Forecasts (ECMWF) one-dimensional + four-dimensional variational analysis (1D+4D-Var) rainfall retrievals are inversion algorithms based on the Bayes' theorem. Differences stem primarily from the a-priori information. GPROF uses an observationally generated a-priori database while ECMWF 1D-Var uses the model forecast First Guess (FG) fields. The relative similarity in the two approaches means that comparisons can shed light on the differences that are produced by the a-priori information. Case studies have found that differences can be classified into four categories based upon the agreement in the brightness temperatures (Tbs) and in the microphysical properties of Cloud Water Path (CWP) and Rain Water Path (RWP) space. We found a category of special interest in which both retrievals converge to similar Tb through minimization procedures but produce different CWP and RWP. The similarity in Tb can be attributed to comparable Total Water Path (TWP) between the two retrievals while the disagreement in the microphysics is caused by their different degrees of constraint of the cloud/rain ratio by the observations. This situation occurs frequently and takes up 46.9% in the one month 1D-Var retrievals examined. To attain better constrained cloud/rain ratios and improved retrieval quality, this study suggests the implementation of higher microwave frequency channels in the 1D-Var algorithm. Cloud Resolving Models (CRMs) offer an important pathway to interpret satellite observations of microphysical properties of storms. High frequency microwave brightness temperatures (Tbs) respond to precipitating-sized ice particles and can, therefore, be compared with simulated Tbs at the same frequencies. By clustering the Tb vectors at these frequencies, the scene can be classified into distinct microphysical regimes, in other words, cloud types. The properties for each cloud type in the simulated scene are compared to those in the observation scene to identify the discrepancies in microphysics within that cloud type. A convective storm over the Amazon observed by the Tropical Rainfall Measuring Mission (TRMM) is simulated using the Regional Atmospheric Modeling System (RAMS) in a semi-ideal setting, and four regimes are defined within the scene using cluster analysis: the 'clear sky/thin cirrus' cluster, the 'cloudy' cluster, the 'stratiform anvil' cluster and the 'convective' cluster. The relationship between Tb difference of 37 and 85 GHz and Tb at 85 GHz is found to contain important information of microphysical properties such as hydrometeor species and size distributions. Cluster-by-cluster comparison between the observations and the simulations discloses biases in the model including overproduction of supercooled water and large hail particles. The detected biases shed light on how the model should be adjusted to generate more realistic microphysical relationships for each cluster. Guided by the model/observation discrepancies in the 'convective' cloud cluster, a new simulation is performed to provide dynamic adjustments by generating more but smaller hail particles

Effects of foam on ocean surface microwave emission inferred from radiometric observations of reproducible breaking waves

Includes bibliographical references.WindSat, the first satellite polarimetric microwave radiometer, and the NPOESS Conical Microwave Imager/Sounder both have as a key objective the retrieval of the ocean surface wind vector from radiometric brightness temperatures. Available observations and models to date show that the wind direction signal is only 1-3 K peak-to-peak at 19 and 37 GHz, much smaller than the wind speed signal. In order to obtain sufficient accuracy for reliable wind direction retrieval, uncertainties in geophysical modeling of the sea surface emission on the order of 0.2 K need to be removed. The surface roughness spectrum has been addressed by many studies, but the azimuthal signature of the microwave emission from breaking waves and foam has not been adequately addressed. RECENtly, a number of experiments have been conducted to quantify the increase in sea surface microwave emission due to foam. Measurements from the Floating Instrumentation Platform indicated that the increase in ocean surface emission due to breaking waves may depend on the incidence and azimuth angles of observation. The need to quantify this dependence motivated systematic measurement of the microwave emission from reproducible breaking waves as a function of incidence and azimuth angles. A number of empirical parameterizations of whitecap coverage with wind speed were used to estimate the increase in brightness temperatures measured by a satellite microwave radiometer due to wave breaking in the field of view. These results provide the first empirically based parameterization with wind speed of the effect of breaking waves and foam on satellite brightness temperatures at 10.8, 19, and 37 GHz.This work was supported in part by the Department of the Navy, Office of Naval Research under Awards N00014-00-1-0615 (ONR/YIP) and N00014-03-1-0044 (Space and Remote Sensing) to the University of Massachusetts Amherst, and N00014-00-1-0152 (Space and Remote Sensing) to the University of Washington. The National Polar-orbiting Operational environmental Satellite System Integrated Program Office supported the Naval Research Laboratory's participation through Award NA02AANEG0338 and supported data analysis at Colorado State University and the University of Washington through Award NA05AANEG0153

Satellite microwave sensing of oceanic cloud liquid water: application to the earth radiation budget and climate

March 1995.Sponsored by NASA Graduate Student Fellowship in Global Change Research NGT-30046.Sponsored by NASA Research NAG-8-981.Sponsored by NOAA NA37RJ0202

Potential of millimeter- and submillimeter-wave satellite observations for hydrometeor studies

The distribution of hydrometeors is highly variable in space and time, since it is the result of a complex chain of processes with scales from microphysical (1e-6 m) to synoptical (1e3 m). It is a challenging task to observe these highly variable atmospheric constituents on a global scale with a temporal and spatial resolution sufficient for numerical weather prediction (NWP) and hydrological purposes. This study investigates the potential of the millimeter- and submillimeter-wavelength range on space-borne sensors for hydrometeor and surface precipitation rate observations. The approach is based on simulations with cloud resolving models (CRMs) coupled to a radiative transfer (RT) model. The simulations are performed for mid-latitude cases covering a broad band of precipitation events such as heavy convective and light stratiform winter precipitation. Realistic atmospheric conditions were simulated with two mesoscale CRMs: the Meso-scale NonHydrostatic model (Meso-NH) on a 10 km and the COSMO-DE (COnsortium for Small-scale MOdeling-DEutschland) on a 2.8 km horizontal resolution. When calculating brightness temperatures for satellite observations with the one-dimensional radiative transfer model MWMOD (MicroWave MODel), the detailed cloud microphysics and the three-dimensional fields of temperature, humidity, and pressure of the CRMs are considered in the calculation of the interaction parameters. The model framework has been evaluated by comparing the simulated brightness temperature fields to observations of the Special Sensor Microwave Imager (SSM/I) as well as to those of the Advanced Microwave Sounding Unit-B (AMSU-B). The results show a good agreement as long as the CRMs capture the atmospheric situation correctly. Consequently, by coupling the radiative transfer model for microwave radiation to CRMs it is possible to evaluate these models through comparison to microwave satellite observations. Brightness temperatures for frequencies between 50 and 428 GHz at nine observation angles have been simulated for five mid-latitude cases at two time steps. In combination with the vertically integrated hydrometeor contents, these brightness temperature simulations have been used to set up a database. On the basis of this database simple retrieval algorithms have been developed to estimate the potential of the millimeter- and submillimeter-wavelength region for precipitation and hydrometeor observations. The results show, that especially for snow and graupel, the total column content can be retrieved accurately with relative errors smaller than 20% in stratiform precipitation cases over land and ocean surfaces. The performance for rain water path is similar to the one for graupel and snow in light precipitation cases. For the cases with higher precipitation amounts, the relative errors for rain water path are larger especially over land. The same behavior can be seen in the surface rain rate retrieval with the difference that the relative errors are doubled in comparison to the rain water path. Algorithms with a reduced number of frequencies show that window channels at higher frequencies are important for the surface rain rate retrieval. These are sensitive to the scattering in the ice phase related to the rain below. For the frozen hydrometeor retrieval, good results can be achieved by retrieval algorithms based only on frequencies at 150 GHz and above which are suitable for geostationary applications due to their reduced demands concerning the antenna size

Use of satellite-derived heterogeneous surface soil moisture for numerical weather prediction, The

Summer 1996.Bibliography: pages [296]-320