Satellite Microwave Radiometer Research Articles

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

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.

Determination of an Amazon Hot Reference Target for the On-Orbit Calibration of Microwave Radiometers

Abstract A physically based model is developed to determine hot calibration reference brightness temperatures (TBs) over depolarized regions in the Amazon rain forest. The model can be used to evaluate the end-to-end calibration of any satellite microwave radiometer operating at a frequency between 18 and 40 GHz and angle of incidence between nadir and 55°. The model is constrained by Special Sensor Microwave Imager (SSM/I) TBs measured at 19.35, 22.2, and 37.0 GHz at a 53° angle of incidence and extrapolates/interpolates those measurements to other frequencies and incidence angles. The rms uncertainty in the physically based model is estimated to be 0.57 K. For instances in which coincident SSM/I measurements are not available, an empirical formula has been fit to the physical model to provide hot reference brightness temperature as a function of frequency, incidence angle, time of day, and day of year. The empirical formula has a 0.1-K rms deviation from the physically based model for annual averaged measurements and at most a 0.6-K deviation from the model for any specific time of day or day of year.

DEVELOPMENT OF 1-D CLOUD MICROPHYSICS DATA ASSIMILATION SYSTEM (CMDAS) BY USING AMSR-E DATA

In this paper, an 1-D Cloud Microphysics Data Assimilation System (CMDAS) is developed for retrieving reasonable cloud distribution. The general framework of CMDAS includes the Kesslerwarm-rain cloud microphysics scheme, a microwave radiative transfer model in the atmosphere and a global minimization method of Shuffled Complex Evolution (SCE). The paper investigates potentials of the CMDAS to modify the cloud properties by considering integrated cloud liquid water content as a assimilation parameter and to introduce the heterogeneity into the initial state of the atmosphere, by applying the CMDAS to the satellite microwave radiometer data set obtained by the international cooperative observation experiment, “Wakasa Bay Experiment 2003”, in Japan. The simulated microwave brightness temperature by CMDAS is in good qualitative and quantitative agreement with the observed one.

Water column particulate organic carbon modeled fluxes in the ice-frequented Southern Ocean

Nine sediment traps deployed in part of the ice-frequented Southern Ocean (Weddell Sea, Ross Sea, and Bransfield Strait) provide the necessary data to compare vertical annual particulate organic carbon (POC) fluxes with ambient ice regimes (annual mean ice concentration) as can be observed by satellite microwave radiometers. Sedimentation in these seasonally ice-covered regions is primarily dependent upon the mean annual ice concentration. We used a similar approach as the Greenland Sea Is Odden–Nordbukta model to develop a semi-empirical model for the Southern Ocean, and found that the vertical POC fluxes are a factor of two smaller than in the Greenland Sea. Applying the model for each individual trap for the years 1979 to 1999 shows that within the biological marginal ice zone (BMIZ), most of the sedimentation takes place within a mean annual ice concentration range of 9–<67%. This range accounts for 77% of the entire sedimentation as compared to 23% for the other sub-areas of the BMIZ, which account for 16% for the range 67–<85%, 2% for the range 85–100%, and 5% for the range 0–<9%. The inter-annual variations in flux are small (2%) ranging from 1.74 to 1.94 g m −2 year −1 at a depth of 500 m, with the fluxes of the western Weddell Sea being similar in magnitude as the Ross Sea (northwest and northeast). The mean annual amount of sedimentation for the years 1979 to 1999 is 32.45±1.06 Mt.

Assessment of the Jason-1 and TOPEX/Poseidon Microwave Radiometer Performance Using GPS from Offshore Sites in the North Sea

The accuracy and drift of atmospheric path delay due to water vapor as derived from satellite microwave radiometers (MWR) is vital to altimetric measures of sea-level change. In this study a continuous time series of dual frequency GPS data from a number of offshore sites is used to examine the long term stability of the TOPEX/Poseidon radiometer and investigate initial performance of that of Jason-1. The location offshore eliminates the problems associated with land based/coastal locations where extrapolation of the GPS tropospheric correction to subsatellite points offshore are required to avoid background surface heat emissions contaminating the MWR delay measurement.

Relationships between Water Vapor Path and Precipitation over the Tropical Oceans

The relationship between water vapor path W and surface precipitation rate P over tropical oceanic regions is analyzed using 4 yr of gridded daily SSM/I satellite microwave radiometer data. A tight monthly mean relationship P (mm day21) 5 exp[11.4(r 2 0.522)] for all tropical ocean regions and seasons is found between P and a column-relative humidity r obtained by dividing W by the corresponding saturation water vapor path. A similar relation, albeit with more scatter, also holds at daily time scales, and can be interpreted as a moisture adjustment time scale of 12 h for convective rainfall to affect humidity anomalies on 300-km space scales. Cross-spectral analysis shows statistically significant covariability of actual and r-predicted precipitation at all frequencies, with negligible phase lag. The correlation of actual and r-predicted precipitation exceeds 0.5 on intraseasonal and longer time scales. The SSM/I retrievals of W and P are found to be skillful even at daily time scales when compared with in situ radiosonde and radar-derived area-averaged precipitation data from Kwajalein Island, but the microwave estimates of daily P scatter considerably about the radar estimates (which are considered to be more reliable). Using the radar-derived precipitation in combination with microwave-derived W yields a daily r‐P relationship at Kwajalein similar to that derived solely from microwave measurements, but with somewhat less P associated with the highest values of r. This emphasizes that the absolute calibration of the r‐P relationship is somewhat dependent on the datasets used to derive r and especially P. Nevertheless, the results provide a useful constraint on conceptual models and parameterizations of tropical deep convection.

30‐Year satellite record reveals contrasting Arctic and Antarctic decadal sea ice variability

A 30‐year satellite record of sea ice extents derived mostly from satellite microwave radiometer observations reveals that the Arctic sea ice extent decreased by 0.30 ± 0.03 × 106 km2/10 yr from 1972 through 2002, but by 0.36 ± 0.05 × 106km2/10yr from 1979 through 2002, indicating an acceleration of 20% in the rate of decrease. In contrast, the Antarctic sea ice extent decreased dramatically over the period 1973–1977, then gradually increased. Over the full 30‐year period, the Antarctic ice extent decreased by 0.15 ± 0.08 × 106 km2/10 yr. The trend reversal is attributed to a large positive anomaly in Antarctic sea ice extent in the early 1970's, an anomaly that apparently began in the late 1960's, as observed in early visible and infrared satellite images.

Microwave remote sensing of soil moisture in southern Ontario: Aircraft and satellite measurements at 19 and 37 GHz

Aircraft microwave radiometer measurements at 19 and 37 GHz were made over a 40 km2 agricultural area in southern Ontario on 16 and 23 May 2001 when the average soil moisture in the area was 28 and 40%, respectively. SSM/I satellite data and ground‐based measurements of soil moisture were collected over the period 2 May to 25 July 2001. The emissivity of a water body (Lake Huron) calculated from the aircraft and satellite microwave radiometer measurements agreed with model calculations to within 0.02, except for the aircraft 37 GHz V channel. The 19 GHz emissivity measured by the SSM/I was higher than coincident aircraft measurements by 0.02 in moister soil conditions and 0.04 in drier conditions. Vegetation height increased from a maximum of 40 cm in hay fields in May to up to 200 cm in corn fields in July. There was a statistically significant relationship between soil moisture and 19 GHz H data for aircraft and SSM/I measurements in May. However, the standard error in the soil moisture estimate was 7%. Soil moisture seemed to have very little influence on 19 and 37 GHz emission during June and July. When the mean monthly emissivity for the May to July period was calculated from the SSM/I data, there was found to be no significant variation from month to month.

Diurnal cycle of liquid water path over the subtropical and tropical oceans

The diurnal cycle of liquid water path (LWP) over the subtropical and tropical oceans is examined using two complete years of TMI (Tropical Rainfall Measuring Mission Microwave Imager) satellite microwave radiometer data. Diurnal amplitudes are a considerable fraction of the mean, especially in low cloud regions to the west of continents, where values of 15–35% are typical. Early morning maxima occur throughout most of the subtropics, consistent with a diurnal cycle driven largely by cloud solar absorption. In deep convective regions of the west Pacific the diurnal cycle is also strong and peaks slightly later. Interestingly, the diurnal amplitude in the SE Pacific and Atlantic stratus regions is considerably larger than in their northern hemisphere counterparts, suggesting differences in the dynamics and structure of low clouds may exist from region to region. The data provide important constraints for models simulating the diurnal cycle of clouds.

Priroda microwave radiometer observations in the Southern Great Plains 1997 hydrology experiment

Priroda microwave radiometer satellite observations were acquired and analysed in conjunction with soil moisture and other important ground and meteorological observations. Priroda was a remote sensing module on the MIR Space Station. The experiment was a component of the Southern Great Plains 1997 (SGP97) hydrology experiment. Problems with the MIR platform during the experiment resulted in a very limited set of data. Priroda sensor performance and some analyses of soil moisture conditions were conducted. These results provide important information for utilizing Priroda data and for soil moisture algorithm development.

The beamfilling algorithm for retrieval of hydrometeor profile parameters from passive microwave measurements

The horizontal inhomogeneity of the atmosphere within a satellite microwave radiometer's field of view (FOV) has always been considered as a source of rainfall retrieval errors. The hydrometeor profile retrieval algorithm presented exploits it to obtain an approximation of a radiative transfer model, which allows relatively simple inversion. The atmosphere within the FOV is treated as a combination of horizontally homogeneous domains. Assuming that one of known "basic" hydrometeor profiles occurs in each domain, the inverse problem is reduced to a determination of "beamfilling coefficients." The online procedure includes determination of beamfilling coefficients and a footprint-averaged hydrometeor profile as a linear combination of "basic" ones. Off-line procedures involve the selection of a minimum number of necessary "basic" brightness temperature vectors and correction of "basic" hydrometeor profiles to provide the best retrieval accuracy for a given cloud/radiative simulation. The performance of the algorithm is tested for both numerical simulations and TRMM/TMI data. Numerical simulation has allowed a comparison of the information content of radiometer measurements from SSM/I, TMI, and the future AMSR. The effectiveness of the algorithm is being tested for rain water integral and rain rate retrievals from TRMM TMI measurements.

PIn. I. An operational nonlinear physical inversion algorithm for precipitable and cloud liquid water estimate in nonraining conditions over sea

For pt.II see ibid., vol.39, no.12, p.2575-86 (2001). An operational nonlinear physical inversion (PIn) algorithm for precipitable and cloud liquid water estimate is described. It is suited for a generic conical scanning satellite microwave radiometer acquisition over sea in nonraining conditions. The algorithm does not need any calibration phase and is independent of the availability of in situ data, being consistent in different geographical and climatological situations. Adopted formulation is addressed to provide observational data to help in validating water vapor and cloud fields produced by a numerical weather prediction model. Furthermore, such a technique can be utilized for the purpose of global reanalysis, improving estimates of primary fields of the hydrological cycle. A sensitivity study of the forward model and a comparison between output brightness temperatures and those from a robust numerical code are also reported. The discrepancies that result are considered acceptable with respect to instrumental constraints and computation time.

A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz H and V polarized brightness temperature observations from the scanning multichannel microwave radiometer (SMMR) over several test sites in Illinois. Results using only nighttime data are presented at this time due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a nonlinear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness, and that vegetation optical depth for H-polarization is the same as for V-polarization. Surface temperature is derived by a procedure using high frequency V-polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and may be applied to other wavelengths. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Retrieval of land surface parameters using passive microwave measurements at 6-18 GHz

An approach is evaluated for retrieval of land surface parameters (soil moisture, vegetation water content, and surface temperature) using satellite microwave radiometer data in the 6-18 GHz frequency range. The approach is applicable to data that will be acquired by the Advanced Microwave Scanning Radiometer (AMSR), planned for launch on the Japanese Advanced Earth Observing Satellite (ADEOS)-II and Earth Observing System (EOS) PM-1 platforms in 1999 and 2000, respectively. The retrieval method is based on a radiative transfer (RT) model for land-surface and atmospheric emission, with model coefficients that can be tuned over specific calibration regions and applied globally. The method uses an iterative, least-squares algorithm, based on six channels of radiometric data. Simulations using this algorithm indicate that, for an assumed sensor noise of 0.3 K in all channels, soil moisture and vegetation water content retrieval accuracies of 0.06 g cm/sup -3/ and 0.15 kg m/sup -2/, respectively, should be achievable in regions of vegetation water content less than approximately 1.5 kg m/sup -2/. A surface temperature accuracy of 2 C should be achievable, except for bare soils, where discrimination between moisture and temperature variability is difficult using this algorithm. These accuracies are for retrievals averaged over the sensor footprint, and they exclude conditions of precipitation, open water, snow cover, frozen ground, or high topographic relief within the footprint. The algorithm has been tested using data from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) for the years 1982-1985, over the African Sahel, and the retrieval results compared to output from an operational numerical weather prediction model.

SSM/I Rain Retrievals within a Unified All-Weather Ocean Algorithm

A new method for the physical retrieval of rain rates from satellite microwave radiometers is presented. The method is part of a unified ocean parameter retrieval algorithm that is based on the fundamental principles of radiative transfer. The algorithm simultaneously finds near-surface wind speed W, columnar water vapor V, columnar cloud liquid water L, rain rate R, and effective radiating temperature TU for the upwelling radiation. Comparisons with radiosondes demonstrate that the algorithm is able to retrieve water vapor when rain is present. For rain rates from 1 to 15 mm h−1, the rms difference between the retrieved water vapor and the radiosonde value is 5 mm. A novel feature of the rain retrieval method is a beamfilling correction that is based upon the ratio of the retrieved liquid water absorption coefficients at 37 and 19 GHz. This spectral ratio decreases by about 40% when heavy and light rain coexist within the SSM/I footprint as compared to the case of uniform rain. This correction increases the rain rate when the spectral ratio is small. However, even with this beamfilling correction, tropical rainfall is still unrealistically low when the freezing level in the Tropics (∼5 km) is used to specify the rain layer thickness. Realism is restored by reducing the assumed tropical rain-layer thickness to 3 km. This adjustment is probably compensating for two processes: 1) the existence of warm rain for which the rain layer does not extend to the freezing level and 2) very heavy rain for which the 19-GHz channels saturate. Global rain rates are produced for the 1991–94 period from two SSM/Is. The authors find that approximately 6% of the SSM/I observations detect measurable rain rates (R > 0.2 mm h−1). The global rain maps show features that are, in general, similar to those reported in previously published rain climatologies. However, some differences that seem to be related to nonprecipitating cloud water are apparent.

Radiobrightness of prairie soil and grassland during dry‐down simulations

We present 60‐day summer dry‐down simulations for prairie grassland based upon a one‐dimensional hydrology and radiobrightness models for northern prairie. Our objective is to examine the effect of scaling upon the interpretability of mixed pixel radiobrightnesses. Even for relatively homogeneous regions like North American prairie, there are significant variations in land cover within the relatively large footprints of satellite microwave radiometers. In this paper we specifically address 1.4‐ and 19‐GHz brightness in the presence of subpixel variability in canopy density. Bare soil and a densecanopy grassland can be viewed as extreme examples of prairie land cover. If land cover within any pixel is viewed as a mixture of these two extremes, then the terrain within that pixel can be modeled as some combination of the hydrology and radiobrightness models for bare soil and dense‐canopy grassland. We examined two combination schemes: (1) a homogeneous combination where the dense‐canopy grasses are simply spread uniformly over the pixel to achieve a desired vegetation column density between that of bare soil and dense‐canopy grass, and (2) a tiled combination where the pixel is divided into a region of bare soil and a region of dense‐canopy grassland. We examined H‐polarized, 53° incidence angle, 19.35‐ and 1.4‐GHz pixel brightnesses and found the 19‐GHz brightness to be significantly greater for homogeneous pixels than for tiled pixels throughout the dry‐down period. For example, a 19‐GHz, 50% homogeneous pixel is 50 K brighter than a 50% tiled pixel at the beginning of the dry‐down and 40 K brighter at 60 days. In contrast, the 1.4‐GHz brightnesses are essentially identical for homogeneous and tiled pixels. Within the constraints of our simulation, subpixel variation in canopy density is a significant factor in the quantitative interpretation of the 19‐GHz brightness of prairie grassland but is not a factor in the interpretation of the 1.4‐GHz brightness.

Vertical observation of snowfall by using the combination of radar and the microwave radiometer

Radar is a powerful instrument in meteorology not only for research but for operational use. For quantitative measurements of precipitation, however, further studies need to be done for reducing measurement errors. Satellite microwave radiometer begins to be used for estimation of precipitation not only over sea but over land by using scattering models. To improve the accuracy of estimation, information vertical profile of size distribution of rain and snow derived from radar process should be combined data observed by passive microwave sensors. This study shows the possibility of snowfall observation with the combination of the radar and the microwave radiometer.

A Simple Method for Testing Brightness Temperatures from Satellite Microwave Radiometers

Abstract A method is proposed for testing microwave measurements from spaceborne sensors by computing collocated simulated brightness temperatures from the ECMWF numerical weather meteorological model using an atmospheric radiative transfer model and the Stogryn model for the surface emissivity. In this paper this method is tested on Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) data. The comparison with observed brightness temperature underlines a rather good agreement for SSM/I but a significant discrepancy for SMMR in the vertical polarization, confirming that the SMMR was biased (up to 10 K). Correcting functions are proposed for SMMR 18- and 21-GHz channels, which are validated by comparing Wilheit and Chang's water vapor algorithm results and radiosonde measurements. Small biases in the SSM/I 19- and 22-GHz brightness temperatures comparison can be similarly eliminated. This calibration is validated in the same way by applying water vapor and surface w...

Assimilation of Satellite Precipitable Water in a Meteorological Forecast Model

Abstract The lack of local humidity observations over a large portion of the globe hinders any improvement of humidity forecasting in meteorological models. However, satellite microwave radiometers routinely provide fields of precipitable water content over the means, with a horizontal resolution of a few tens of kilometers. The aim of this paper is therefore to establish the feasibility of the assimilation of microwave radiometer precipitable water content in a forecast model. This preliminary study presents the assimilation method, which is based on optimal interpolation, and results of analysis and forecast runs over 12 h for one case. The Special Sensor Microwave/Imager (SSM/I) radiometer (the scanning microwave radiometer aboard the U.S. Navy Defense Meteorological Satellite Program satellite) and the Prevision a Echeance Rapprochee, Integrant des Donnees Observees et Teledetectees (PERIDOT) model (operational limited-area model of the French Meteorological Office) were used to perform this test. We ...

Interpretation of Bhaskara-II satellite microwave radiometer data in terms of land features

Abstract Studies on brightness temperature (TB) data of 325 passes acquired by Bhaskara-II satellite microwave radiometers (SAMIR) at 19 [sdot] 35, 22 [sdot] 235 and 31 [sdot] 4 GHz indicate that certain passes have interesting TB data trends over land and sea in spite of coarse ground resolution. Here an attempt is made to analyse such passes in terms of the ground features and agrochmatic conditions. Certain passes have shown more or less constant TB values over a long stretch of the pass. Average TB data values have been extracted from such passes and are summarized.