Advanced Microwave Sounding Unit Measurements Research Articles

Rapid Intensification of Tropical Cyclones Observed by AMSU Satellites

AbstractThis study examines the vertical structures of temperature and convection associated with rapid intensification of tropical cyclones using collocated Advanced Microwave Sounding Unit (AMSU) and HURSAT‐B1 satellite observations for 2003–2015. We used AMSU measurements from six satellites: AQUA, MetOp, NOAA‐15, NOAA‐16, NOAA‐17, and NOAA‐18. Eighteen thousand three hundred sixty nine collocated satellite overpasses of tropical cyclones were obtained. Vertical structures of temperature and convection are analyzed for different categories of tropical cyclone intensity, for the composite lifecycles of tropical cyclones in different ocean basins, and for the rapid intensification events. Tropical cyclones reaching hurricane intensity are generally associated with warm core above eyewall cloud top extending into the stratosphere, suggesting the existence of warm stratospheric downdrafts penetrating into the central eye. Rapid intensification of tropical cyclones are generally associated with strong warming rate above eyewall cloud top that extends into the stratosphere, suggesting that stratospheric downdrafts are involved in rapid intensification of tropical cyclones.

Estimation of cloud liquid water over oceans from dual oxygen absorption band to support the assimilation of second generation of microwave observation on board the Chinese FY-3 satellite

ABSTRACTTo make up for the absence of observation-based information of cloud liquid water (CLW) in assimilation of second generation of microwave observation on board the Chinese FengYun-3 satellite, two algorithms using double oxygen-absorption band microwave sounding observation at 52.80 and 118.75 ± 2.5 GHz, one using brightness temperatures directly and the other utilizing a cloud emission and scattering index derived from the brightness temperature, are proposed to estimate CLW over oceans. Their performance was evaluated by verifying the estimations from FY-3C double oxygen absorption band microwave observations and that from the traditional Grody scheme applied to microwave measurements at 23.8 and 31.4 GHz from the MetOp-B satellite. An additional experiment was conducted to investigate the impact of regression analysis on the actual brightness temperature and reanalysis data, or the simulated measurements. It is demonstrated that CLW can be retrieved from double oxygen absorption band microwave sounding measurements. The estimations are comparable to the results obtained using the traditional scheme applied to Advanced Microwave Sounding Unit measurements. While total precipitable water was not well obtained as the traditional scheme did, it is feasible to perform regression analysis on actual brightness temperature and reanalysis data; however, for all estimations that the regression was conducted on, the results obtained using actual brightness temperature and reanalysis data were weaker than those obtained using regression coefficients from the simulated data set. The results could be improved by better matching the satellite observations and CLW data used in the regression analysis.

Investigations of stratospheric temperature regional variability with lidar and Advanced Microwave Sounding Unit

[1] Seasonal and interannual stratospheric temperature variability at two relatively close-by lidar stations, the Observatoire de Haute-Provence (France) and the Hohenpeissenberg Observatory (Germany), are investigated using lidars and the Advanced Microwave Sounding Unit (AMSU) satellite data to examine possible causes of temperature trend discrepancies between these two sites. We first examined data measured by lidar and AMSU at each station and found that temperature anomalies observed with lidar have larger spread than those with AMSU probably as a result of distinct vertical sampling. Lidar and AMSU measurements have correlation typically higher than 0.7; however, correlation is decreased to 0.4–0.5 in summer at the French station. Lidar measurements have good correlation between the two stations, around 0.9 in winter and 0.45 in summer, while AMSU data show correlations between both stations of about 0.94 year-round. Data from coincident measurement dates at both sites have then been taken from the integral series in order to isolate local geophysical effects. A comparison between lidar and AMSU measurements of coincident dates suggests that in wintertime measurement discrepancies are to a great extent a result of different local atmospheric dynamics. These are important on the estimation of stratospheric trends and can partially explain discrepancies observed in trends estimates based on lidars in distinct locations or on satellite data. The present results have implications on the planning of measurement strategies using lidars involved in the Network for the Detection of Atmospheric Composition Changes (NDACC), as well as on methodologies for satellite data use for stratospheric monitoring purposes.

A New Sea-Ice Concentration Algorithm Based on Microwave Surface Emissivities—Application to AMSU Measurements

Passive microwave sea-ice retrieval algorithms are typically tuned to brightness temperature measurements with simple treatments of weather effects. The new technique presented is a two-step algorithm that variationally retrieves surface emissivities from microwave remote sensing observations, followed by the retrieval of sea-ice concentration from surface emissivities. Surface emissivity spectra are interpreted for determining sea-ice fraction by comparison with a catalog of sea-ice emissivities to find the closest match. This catalog was computed off-line from known ocean, first-year, and multiyear sea-ice reference emissivities for a range of fractions. The technique was adjusted for application to the Advanced Microwave Sounding Unit (AMSU)/Microwave Humidity Sensor observations, and its performance was compared to the National Oceanic and Atmospheric Administration (NOAA)'s AMSU heritage sea-ice algorithm and to NOAA's operational Interactive Multi-sensor Snow and Ice Mapping System taken as ground truth. Assessment results indicate a performance that is superior to the heritage algorithm particularly over multiyear ice and during the warm season.

On the use of Advanced Microwave Sounding Unit‐A and ‐B measurements for studying the monsoon variability over West Africa

The advanced microwave sounding unit (AMSU) ‐A and ‐B sensors provide observations of humidity and temperature that are relevant for meteorological and climate studies. The use of these observations in numerical weather prediction models has increased in the past 10 years because of some improvements in data assimilation. However, an appropriate use of AMSU measurements apart from assimilation context is rather difficult and depends for the most part on how successfully the instrumental characteristics are accounted for. In particular, atmosphere humidity and temperature variations can be completely hidden by features because of the effect of the observation zenith angle. In this paper, 8 years of AMSU‐A and ‐B observations have been corrected from the observations zenith angle effect and have been used to study temperature and humidity variations over West Africa. Comparisons have been made between AMSU observations and selected atmospheric fields from European Centre for Medium‐Range Weather Forecasts analyses as well as outgoing longwave radiation estimates. It has been found that observations from AMSU‐A channel 5 can be used to monitor the heat low evolution and that AMSU‐B observations from channels 3 and 5 are well adapted to study the humidity variations in direct link with the African monsoon from intraseasonal to interannual scales.

Calibration of Temperature in the Lower Stratosphere from Microwave Measurements Using COSMIC Radio Occultation Data: Preliminary Results

Accurate, consistent, and stable observations from different satellite missions are crucial for climate change detection. In this study, we use Global Positioning System (GPS) Radio Occultation (RO) data from the early phase of the FORMOSAT-3/Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission, which was successfully launched on 15 April 2006, to inter-calibrate Temperature in the Lower Stratosphere (TLS) taken from Advanced Microwave Sounding Unit (AMSU) microwave measurements from different satellites for potential improvements of stratospheric temperature trend analysis. With a limited number of COSMIC soundings in the early phase of the mission, these results are considered preliminary. In this study, we use COSMIC RO data to simulate microwave brightness temperatures, for comparison with AMSU Ch9 measurements (e.g., TLS) on board NOAA15, 16 and 18. Excellent correlation was found between synthetic COSMIC brightness temperatures (Tbs) and Tbs from NOAA15, NOAA16 and NOAA18, respectively. However, systematic differences on the order of 0.7 K to 2 K were found between COSMIC and AMSU observations over Antarctica. Our results demonstrate that synthetic COSMIC Tbs are very useful in identifying inter-satellite offsets among AMSU measurements from different satellites. To demonstrate the long-term stability of GPS RO data, we compare COSMIC dry temperature profiles to those from collocated CHAMP profiles, where CHAMP was launched in 2001. The fact that the CHAMP and COSMIC dry temperature difference between 500 hPa and 10 hPa ranges from -0.35 K (at 10 hPa) to 0.25 K (at 30 hPa) and their mean difference is about -0.034 K demonstrates the long-term stability of GPS RO signals. In order to demonstrate the potential usage of the GPS RO calibrated AMSU Tbs to inter-calibrate other overlapping AMSU Tbs, we examine the uncertainty of the calibration coefficients derived from AMSU-GPS RO pairs. We found the difference between COSMIC calibrated AMSU Tbs and those from CHAMP to be in the range of ±0.07 K with 0.1 K standard deviation. This demonstrates the robustness of the calibration

Relationship between snow parameters and microwave satellite measurements: Theory compared with Advanced Microwave Sounding Unit observations from 23 to 150 GHz

A theoretical model is used to examine the relationship between snow parameters and satellite‐based microwave radiometer measurements between 23 and 150 GHz. The model is based on the two‐stream radiative transfer equation whose optical parameters are obtained from dense media theory. Model simulations are used to show how the grain size, density, snow depth, and an ice crust affect the emissivity and brightness temperatures measured by the Advanced Microwave Sounding Unit (AMSU). The AMSU channels at 23, 31, 89, and 150 GHz are shown to be more sensitive to grain size variations than the other snow parameters. For ice particle diameters less than 1 mm the emissivity and brightness temperatures are found to decrease continuously up to 150 GHz. However, for larger particles, the emissivity and brightness temperature results in a flatter frequency response beyond 89 GHz as the wavelength approaches the particle size. Model results are tested using AMSU measurements for snow events over the central United States during a 2‐week period in the late fall. In agreement with model simulations, the brightness temperature is shown to decrease continuously up to 150 GHz for the small grain size associated with new snow, whereas the brightness temperature no longer decreases beyond 89 GHz as the snow ages and larger grains form owing to snow metamorphosis. Most importantly, the difference between the 89 and 150 GHz AMSU measurements is shown to provide a unique signature for identifying and separating new from aged snow. Consequently, it is now possible to identify four different snow types (wet, new, aged, and stratified snow) from AMSU.

Development of a neural network algorithm for the retrieval of TPW from NOAA16 AMSU measurements

A neural‐network‐based algorithm for the retrieval of Total Precipitable Water (TPW) using Advanced Microwave Sounding Unit (AMSU) data available in real time from NOAA16 satellite has been developed. The retrieval method benefits from reliable surface observations, which includes the skin temperature and ocean surface wind speed and direction. The algorithm uses the simulated brightness temperatures at four frequencies, 23.4 Ghz, 31.4 Ghz, 50.3 Ghz, and 89.0 Ghz, of AMSU‐A as input and TPW derived from Radiosonde Observations (RAOB) profiles as output. The pairs of input and output are restricted to the homogeneous emitting areas, e.g. over Bay of Bengal and Arabian Sea. The performance of the algorithm is assessed using independent RAOB measurements. The bias and rms differences are found to be 0.21 mm and 2.03 mm respectively over the range of 15 and 75 mm. Further, extensive comparisons are made between the TPW obtained from the neural network algorithm and those obtained using other satellite instruments like the Tropical Rainfall Measuring Mission Microwave Imager, Advanced Infrared Sounder, and Moderate Resolution Imaging Spectroradiometer, in which the results are found to be in close agreement.

Microwave land emissivity calculations using AMSU measurements

Atmospheric parameter retrievals over land from Advanced Microwave Sounding Unit (AMSU) measurements, such as atmospheric temperature and moisture profiles, could be possible using a reliable estimate of the land emissivity. The land surface emissivities have been calculated using six months of data, for 30 beam positions (observation zenith angles from -58/spl deg/ to +58/spl deg/) and the 23.8-, 31.4-, 50.3-, 89-, and 150-GHz channels. The emissivity calculation covers a large area including Africa, Eurasia, and Eastern South America. The day-to-day variability of the emissivity is less than 2% in these channels. The angular and spectral dependence of the emissivity is studied. The obtained AMSU emissivities are in good agreement with the previously derived SSMI ones. The scan asymmetry problem has been evidenced for AMSU-A channels. And possible extrapolation of the emissivity from window channels to sounding ones has been successfully tested.

Interpretation of AMSU microwave measurements for the retrievals of snow water equivalent and snow depth

The objective of this paper is to interpret microwave scattering signatures over snow cover as observed by the Advanced Microwave Sounding Unit (AMSU) for the retrievals of snow water equivalent and snow depth. A case study involving seasonal snow cover over the U.S. Great Plains was analyzed in detail. Area‐wide analysis of the relationship between snow depth and the AMSU scattering signatures in the 23–150 GHz window region showed weak correlation, deteriorated by the dependence of these signatures on snow metamorphism. The lower frequency scattering index, computed as the difference in the brightness temperature between 23 and 31 GHz channels, was low and insensitive to fresh snow predominant in December, but increased later in the season, and thus was more sensitive to snow depth for older snow cover. However, this seasonal increase in microwave scattering was observed for every snow depth range, suggesting a strong dependence on snow metamorphism. In contrast, the 89 GHz scattering index responded to relatively shallow snow cover in December, but was less sensitive to snow depth variability later in the season. A snow hydrology model was applied at specific locations to estimate snow water equivalent (other than snow depth) for comparisons with the AMSU measurements. Overall, the lower frequency index was the best predictor of snow water equivalent and snow depth. However, correlation was higher for snow density and snow water equivalent. This was attributed to the response of this scattering index to the grain size evolution with time, which correlated better with the snow density and water equivalent changes in the snow cover than snow depth. Correlation between the snow water equivalent and the lower frequency index for fresh snow cover was significantly improved by switching to the higher frequency index at 89 GHz as predictor when the lower frequency index at 31 GHz was less than the 5 K threshold. Correlation further improved for fresh snow cover associated with a positive 150 GHz scattering index. These results suggest that the utility of AMSU measurements for the retrievals of snow depth and snow water equivalent could be better optimized by proper selection of the scattering thresholds that minimize the variability of important snow parameters such as grain size.

Satellite analysis of tropical cyclones using NOAA-16 AMSU measurements over Indian region

The first Advanced Microwave Sounding Unit (AMSU) was launched aboard NOAA-15 satellite on 13 May 1998. AMSU measurements are now also available from NOAA-16 and NOAA-17 satellites. The AMSU is well suited for the observation of tropical cyclones because the ice clouds that cover tropical cyclones do not significantly affect its measurements. In this paper the intensity of three tropical cyclones formed over Bay of Bengal and Arabian Sea in the month of October 1999, May and September 2001 were studied using AMSU measurements. The upper tropospheric warm core thermal anomalies over the tropical cyclone areas were computed from temperature profiles using the NOAA-15 and NOAA-16 AMSU-A measurements. It has been observed that the magnitude of the warm core temperature anomaly at about 250 hPa was an indicator of the intensity of tropical cyclones in all three cases. The order of the temperature anomaly was about 6oC in case of super tropical cyclone, 1999 while in other two cases the order of the temperature anomaly were of about 3oC for moderate tropical cyclones, 2001. Therefore, it may be stated that the AMSU data appeared to offer substantial opportunities for improvements in tropical cyclone analysis and forecasting.

A new snowfall detection algorithm over land using measurements from the Advanced Microwave Sounding Unit (AMSU)

This study introduces a new snowfall detection algorithm over land using AMSU measurements. The algorithm utilizes a combination of channels in the microwave window, water vapor and oxygen absorption regions. The new algorithm is combined with the current NOAA operational AMSU rain rate product for falling snow and rain areal extent retrievals over the U.S. These retrievals are compared with NEXRAD radar precipitation and local meteorological observations. Preliminary results demonstrate that the algorithm is robust in capturing winter precipitation with minimum classification errors.

Impact of the Advanced Microwave Sounding Unit Measurements on Hurricane Prediction

Abstract Due to the lack of meteorological observations over the tropical oceans, almost all the current hurricane models require bogusing of a vortex into the large-scale analysis of the model initial state. In this study, an algorithm to construct hurricane vortices is developed using the Advanced Microwave Sounding Unit (AMSU-A) data. Under rain-free atmospheric conditions, the temperature profile could be retrieved with a root-mean-square error of 1.5°C. Under heavy rainfall conditions, measurements from channels 3–5 are removed in retrieving temperatures. An application of this algorithm to Hurricane Bonnie (1998) shows well the warm-core eye and strong thermal gradients across the eyewall. The rotational and divergent winds are obtained by solving the nonlinear balance and omega equations using the large-scale analysis as the lateral boundary conditions. In doing so, the sea level pressure distribution is empirically specified, and the geopotential heights are calculated from the retrieved temperatu...

Determination of precipitable water and cloud liquid water over oceans from the NOAA 15 advanced microwave sounding unit

The advanced microwave sounding unit (AMSU) was finally launched in May 1998 aboard the NOAA 15 satellite. Algorithms are provided for retrieving the total precipitable water (TPW) and cloud liquid water (CLW) over oceans using the AMSU measurements at 23.8 and 31.4 GHz. Extensive comparisons are made between the AMSU retrievals of CLW and TPW and those obtained using other satellite instruments (Special Sensor Microwave Imager (SSM/I) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI)) and ground‐based radiometers. The AMSU TPW is also compared against radiosonde data, where all of the results are in good agreement with rms differences less than 3 mm and biases less than 1 mm over the range between 5 and 60 mm. The CLW comparisons show greater variability, although the time series of the AMSU and ground‐based sensors follow each other and cover the same dynamic range of 0–0.5 mm. The AMSU CLW also compares well with the other satellite measurements, although a bias exists between AMSU and TMI when the CLW exceeds 0.5 mm.