Advanced Microwave Sounding Unit-B Research Articles

Upper tropospheric water vapour variability over tropical latitudes observed using radiosonde and satellite measurements

The present study deals with using long-term database for upper tropospheric water vapour (UTWV) variability studies over three tropical stations (Gadanki, Singapore and Truk), where different climatic conditions prevail. Over Gadanki (13.5°N, 79.2°E) strong seasonal variation in UTWV is revealed but not over Singapore (1.37°N, 103.98°E) and Truk (7.46°N, 151.85°E) except at 100 hPa. It is examined whether high resolution radiosonde measurements represent well the UTWV by comparing with different satellite based (Atmospheric Infrared Sounder (AIRS), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Limb Sounder (MLS)) water vapour measurements. Very good comparison in the nature of variations of UTWV is observed between radiosonde data and satellite data, except over Singapore particularly with AIRS and MLS data, on long-term basis. An attempt is also made to examine the source for UTWV. A close relationship is found between UTWV and deep convection over Gadanki indicating that the source for UTWV is convection particularly during the summer monsoon season.

Intercalibrating Microwave Satellite Observations for Monitoring Long-Term Variations in Upper- and Midtropospheric Water Vapor*

Abstract This paper analyzes the growing archive of 183-GHz water vapor absorption band measurements from the Advanced Microwave Sounding Unit B (AMSU-B) and Microwave Humidity Sounder (MHS) on board polar-orbiting satellites and document adjustments necessary to use the data for long-term climate monitoring. The water vapor channels located at 183.31 ± 1 GHz and 183.31 ± 3 GHz are sensitive to upper- and midtropospheric relative humidity and less prone to the clear-sky sampling bias than infrared measurements, making them a valuable but underutilized source of information on free-tropospheric water vapor. A method for the limb correction of the satellite viewing angle based upon a simplified model of radiative transfer is introduced to remove the scan angle dependence of the radiances. Biases due to the difference in local observation time between satellites and spurious trends associated with satellite orbital drift are then diagnosed and adjusted for using synthetic radiative simulations based on the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim). The adjusted, cloud-filtered, and limb-corrected brightness temperatures are then intercalibrated using zonal-mean brightness temperature differences. It is found that these correction procedures significantly improve consistency and quantitative agreement between microwave radiometric satellite observations that can be used to monitor upper- and midtropospheric water vapor. The resulting radiances are converted to estimates of the deep-layer-mean upper- and midtropospheric relative humidity, and can be used to evaluate trends in upper-tropospheric relative humidity from reanalysis datasets and coupled ocean–atmosphere models.

The effects of assimilating satellite brightness temperature and bogus data on the simulation of Typhoon Kalmaegi (2008)

Observational and bogus satellite data are directly assimilated into the Weather Research and Forecasting (WRF) model in simulations of Typhoon Kalmaegi (2008). The data assimilation is performed using the Radiative Transfer for TIROS-N Operational Vertical Sounder (RTTOV) model and the three-dimensional variational data assimilation (3DVAR) technique, with satellite observations taken from the National Oceanic and Atmospheric Administration-16 (NOAA-16) Advanced TIROS Vertical Sounder (ATOVS) system composed of the High-resolution Infrared Radiation Sounder (HIRS), the Advanced Microwave Sounding Unit-A (AMSU-A), and the Advanced Microwave Sounding Unit-B (AMSU-B). Data assimilation experiments are initialized at three different times. Improvements in the numerical simulation of the typhoon are discussed in the context of wind, temperature, pressure, and geopotential fields.

Fengyun-3B MicroWave Humidity Sounder (MWHS) Data Noise Characterization and Filtering Using Principle Component Analysis

MicroWave Humidity Sounder (MWHS) onboard both Fengyun-3A (FY-3A) and FY-3B satellites have three channels (channels 3-5) near the 183-GHz water-vapor absorption line. These channel frequencies are also used in other instruments such as Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) onboard MetOp and NOAA satellites. Both MWHS and MHS are cross-track scanners. In this paper, a comparison between the simulated brightness temperatures with MWHS measurements clearly shows that MWHS observations from the three sounding channels contain a scan-angle-dependent cohesive noise along the instrument scanline. This noise does not cancel out when a large amount of data over a sufficiently long period of time is averaged, which eliminates the possibility of such a noise to arise from the natural variability of the atmosphere and the surface. The noises are around 0.3, 0.2, and 0.2 K for channels 3-5, respectively. A principle component analysis is used for the characterization of this cohesive noise using one-month FY-3B MWHS data. It is shown that the MWHS cohesive noise is primarily contained in the first principal component (PC) mode, which mainly describes a scan-angle-dependent brightness temperature variation, i.e., a unique feature of the cross-tracking instrument. The first PC accounts for more than 99.91 % total variance in the three MWHS sounding channels. A five-point smoother is then applied to the first PC, which effectively removes such a data noise in the MWHS data. The reconstruction of the MWHS radiance spectra using the noise-filtered first PC component is of good quality. The scan-angle-dependent bias from the reconstructed MWHS data becomes more uniform and is consistent with the NOAA-18 MHS data.

Satellite and Numerical Model Investigation of Two Heavy Rain Events over the Central Mediterranean

Abstract Two heavy rain events over the Central Mediterranean basin, which are markedly different by genesis, dimensions, duration, and intensity, are analyzed. Given the relative low frequency of this type of severe storms in the area, a synoptic analysis describing their development is included. A multispectral analysis based on geostationary multifrequency satellite images is applied to identify cloud type, hydrometeor phase, and cloud vertical extension. Precipitation intensity is retrieved from (i) surface rain gauges, (ii) satellite data, and (iii) numerical model simulations. The satellite precipitation retrieval algorithm 183-Water vapor Strong Lines (183-WSL) is used to retrieve rain rates and cloud hydrometeor type, classify stratiform and convective rainfall, and identify liquid water clouds and snow cover from the Advanced Microwave Sounding Unit-B (AMSU-B) sensor data. Rainfall intensity is also simulated with the Weather Research and Forecasting (WRF) numerical model over two nested domains with horizontal resolutions of 16 km (comparable to that of the satellite sensor AMSU-B) and 4 km. The statistical analysis of the comparison between satellite retrievals and model simulations demonstrates the skills of both methods for the identification of the main characteristics of the cloud systems with a suggested overall bias of the model toward very low rain intensities. WRF (in the version used for the experiment) seems to classify as low rain intensity regions those areas where the 183-WSL retrieves no precipitation while sensing a mixture of freshly nucleated cloud droplets and a large amount of water vapor; in these areas, especially adjacent to the rain clouds, large amounts of cloud liquid water are detected. The satellite method performs reasonably well in reproducing the wide range of gauge-detected precipitation intensities. A comparison of the 183-WSL retrievals with gauge measurements demonstrates the skills of the algorithm in discriminating between convective and stratiform precipitation using the scattering and absorption of radiation by the hydrometeors.

Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction

Abstract The potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis real-time product 3B42RT (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product and through evaluation of streamflow simulations over four tributaries of La Plata basin (LPB) in South America using the two precipitation products, is investigated. Assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February 2005, which include use of additional microwave sensors [Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and Advanced Microwave Sounding Unit-B (AMSU-B)] and implementation of different calibration schemes. This study suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

A comparison of the performance of Kalpana and HIRS water vapor radiances in the WRF 3D-Var assimilation system for mesoscale weather predictions

[1] An impact study is presented to compare the performance of the Weather Research and Forecasting (WRF) model in response to assimilation of water vapor (WV) channel radiances from Indian geostationary satellite Kalpana and from High-Resolution Infrared Sounder (HIRS) HIRS-3/4 instruments on board NOAA satellites. A three-dimensional variational data assimilation (3D-Var) system is used for assimilation of radiances from above mentioned instruments, and the impacts of these radiances were assessed on 24 h forecasts starting on each day at 0000 UTC for the period 10–20 July 2008. It was found that the Kalpana radiances provide significant improvement over the HIRS radiances. Compared to HIRS, the assimilation of the Kalpana WV radiances improved the mid–upper tropospheric moisture (∼6%) and temperature (∼1.5%) analysis when verified against National Centers for Environmental Prediction (NCEP) analysis. Simulated microwave radiances using model fields assimilated with Kalpana radiances match significantly closer to Advanced Microwave Sounding Unit-B (AMSU-B) radiances, compared to those assimilated with HIRS radiances. Impact on mid–upper tropospheric moisture, temperature and lower and upper tropospheric wind forecast was positive. The reduction in the root mean square errors by the Kalpana radiance assimilation reached up to 1.5% for the temperature forecast against NCEP analysis, and about 2% for the moisture forecast. The improved mid to upper tropospheric humidity and temperature with the use of Kalpana radiances led to better rain forecasts.

WRF Simulations of the 20–22 January 2007 Snow Events over Eastern Canada: Comparison with In Situ and Satellite Observations

Abstract One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold-season precipitation measurements in mid- and high latitudes through the use of high-frequency passive microwave radiometry. For this purpose, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF–SDSU) to facilitate snowfall retrieval algorithms over land by providing a virtual cloud library and corresponding microwave brightness temperature measurements consistent with the GPM Microwave Imager (GMI). When this study was initiated, there were no prior published results using WRF at cloud-resolving resolution (1 km or finer) for high-latitude snow events. This study tested the Goddard cloud microphysics scheme in WRF for two different snowstorm events (a lake-effect event and a synoptic event between 20 and 22 January 2007) that took place over the Canadian CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) site in Ontario, Canada. The 24-h-accumulated snowfall predicted by WRF with the Goddard microphysics was comparable to that observed by the ground-based radar for both events. The model correctly predicted the onset and termination of both snow events at the Centre for Atmospheric Research Experiments site. The WRF simulations captured the basic cloud patterns as seen by the ground-based radar and satellite [i.e., CloudSat and Advanced Microwave Sounding Unit B (AMSU-B)] observations, including the snowband featured in the lake event. The results reveal that WRF was able to capture the cloud macrostructure reasonably well. Sensitivity tests utilizing both the “2ICE” (ice and snow) and “3ICE” (ice, snow, and graupel) options in the Goddard microphysical scheme were also conducted. The domain- and time-averaged cloud species profiles from the WRF simulations with both microphysical options show identical results (due to weak vertical velocities and therefore the absence of large precipitating liquid or high-density ice particles like graupel). Both microphysics options produced an appreciable amount of liquid water, and the model cloud liquid water profiles compared well to the in situ C3VP aircraft measurements when only grid points in the vicinity of the flight paths were considered. However, statistical comparisons between observed and simulated radar echoes show that the model tended to have a high bias of several reflectivity decibels (dBZ), which shows that additional research is needed to improve the current cloud microphysics scheme for the extremely cold environment in high latitudes, despite the fact that the simulated ice/liquid water contents may have been reasonable for both events. Future aircraft observations are also needed to verify the existence of graupel in high-latitude continental snow events.

Mediterranean hurricanes: large-scale environment and convective and precipitating areas from satellite microwave observations

Abstract. Subsynoptic scale vortices that have been likened to tropical cyclones or polar lows (medicanes) are occasionally observed over the Mediterranean Sea. Generated over the sea, they are usually associated with strong winds and heavy precipitation and thus can be highly destructive in islands and costal areas. Only an accurate forecasting of such systems could mitigate these effects. However, at the moment, the predictability of these systems remains limited. Due to the scarcity of conventional observations, use is made of NOAA/MetOp satellite observations, for which advantage can be taken of the time coverage differences between the platforms that carry it, to give a very complete temporal description of the disturbances. A combination of AMSU-B (Advanced Microwave Sounding Unit-B)/MHS (Microwave Humidity Sounder) observations permit to investigate precipitation associated with these systems while coincident AMSU-A (Advanced Microwave Sounding Unit-A) observations give insights into the larger synoptic-scale environment in which they occur. Three different cases (in terms of intensity, location, trajectory, duration, and periods of the year – May, September and December, respectively) were investigated. Throughout these time periods, AMSU-A observations show that the persisting deep outflow of cold air over the sea together with an upper-level trough upstream constituted a favourable environment for the development of medicanes. AMSU-B/MHS based diagnostics show that convection and precipitation areas are large in the early stage of the low, but significantly reduced afterwards. Convection is maximum just after the upper-level trough, located upstream of cold mid-tropospheric air, reached its maximum intensity and acquired a cyclonic orientation.

Observing precipitation by means of water vapor absor tion lines: a first check of the retrieval capabilities of the 183-WSL rain retrieval method

A new approach is described to infer rain rates by using the opaque channels of the Advanced Microwave Sounding Unit-B (AMSU-B) sensor on board of the NOAA satellites. The retrieval scheme of the 183-WSL (Water Strong Lines at 183.31 GHz) algorithm consists of two main modules. First, some thresholds act to discriminate between rainy and non-rainy pixels (183-WSLW). This is necessary to prevent false alarms mainly caused by the strong absorption of the condensed cloud droplets developing during light precipitation formation. Cloud droplets, especially when they feed precipitation formation mechanisms, can sensibly grow as a consequence of intense condensation in the surrounding regions of rainy clouds. Secondly, on the basis of different extinction of radiation, rain types are classified as convective (183-WSLC module) or stratiform (183-WSLS module) typologies.

Rainfall estimation from satellite passive microwave observations in the range 89 GHz to 190 GHz

The aim of the present work is to improve the current state of rainfall estimation by proposing a procedure based entirely on the observations made by the US Advanced Microwave Sounding Unit/B (AMSU/B) on board the National Oceanic and Atmospheric Administration (NOAA) satellites. The procedure does not require the integration of additional sensors which could deteriorate the overall spatial and temporal resolution. It exploits both the radiometric observations made at 89 and 150 GHz (window channels) and the ones made in the 183 GHz water vapor band (opaque channels). In particular, the differences between the measurements of some of the AMSU/B channels are analyzed through radiative transfer simulations for the estimation of precipitation over both land and water surfaces and are related to rain rate values in different atmospheric scenarios. The algorithm estimates exhibit a very good agreement with ground‐based (both radar and rain gauge) observations in the detection of rainfall and a reasonably good estimation of rain rate values. The probability of detection of precipitation is 75% and 90% for rain rates greater than 1 mm/h and 5 mm/h, respectively. Furthermore, due to the use of both window and opaque channels, the proposed procedure is able to retrieve light rain and not to misidentify snow‐covered surfaces as rain.

Comparison of AIRS and AMSU‐B monthly mean estimates of upper tropospheric humidity

Satellite‐borne measurements provide valuable information on the global distribution of upper tropospheric humidity (UTH), which represents the mean relative humidity in a layer approximately enclosed by the atmospheric pressure levels 500 and 200 hPa. Monthly mean distributions of microwave observations of UTH obtained from the Advanced Microwave Sounding Unit‐B (AMSU‐B) and the Humidity Sounder for Brazil (HSB) are compared to infrared observations of UTH from the Atmospheric Infrared Sounder (AIRS). All data sets for January 2003 show distributions as expected from climatologies. Data of AIRS and AMSU‐B averaged on 1.5° × 1.5° lat‐lon bins for January 2003 show good overall agreement. However, with 2.7%RH AIRS shows an unexpected wet mean bias, especially for regions where the influence of clouds is small or cloud affected measurements are excluded for both sensors. In regions where AIRS is sensitive to cloud affected measurements but not AMSU‐B, the bias is reduced and partly negative.

Comparisons of global cloud ice from MLS, CloudSat, and correlative data sets

Aura Microwave Limb Sounder (MLS) version 2.2 (V2.2) and CloudSat R04 (release 4) ice water content (IWC) and partial‐column ice water path (pIWP) measurements are analyzed and compared to other correlative data sets. The MLS IWC, representing an average over ∼300 × 7 × 4 km3 volume, is retrieved at 215–268 hPa with precision varying between 0.06 and 1 mg/m3. The MLS pIWP products, representing the partial columns over ∼100 × 7 km2 area with the bottom at ∼8, ∼6, and ∼11 km for 115, 240, and 640 GHz, have estimated precisions of 5, 1.5, and 0.8 g/m2, respectively. CloudSat, on the other hand, shows a minimum detectable sensitivity of −31 dBZ in the reflectivity measurement at 94 GHz. CloudSat IWC is an average over ∼1.8 × 1.4 × 0.5 km3 volume, and its precision varies from 0.4 mg/m3 at 8 km to 1.6 mg/m3 at 12 km. The estimated single‐profile precision for CloudSat IWP is ∼9 g/m2. However, these measurements are associated with relatively large systematic error, mostly due to uncertainties in the retrieval assumptions about microphysics, which lead to relatively poor accuracy compared to measurement precision. To characterize systematic differences among various observations and those derived from models, we employ the normalized probability density function (pdf) in the comparisons. CloudSat IWC shows generally consistent slopes of pdf distribution with in situ observations, particularly at ∼12 km where the in situ data come mostly from long‐leg flights. Despite similar IWC morphology found between MLS and CloudSat observations, CloudSat R04 IWC retrieval is higher compared to MLS, especially at 14–17 km where the MLS technique is not limited by sensitivity saturation. The MLS and CloudSat IWC pdf's agree well in the overlapped sensitivity range with relative difference <50%, but the difference appears to increase with IWC. MLS and CloudSat cloud ice measurements are compared with other data sets in terms of monthly map and pdf. Comparisons with European Center for Medium range Weather Forecasting (ECMWF) analyses show that grid box averages of monthly ECMWF IWC are much smaller (by ∼5× and ∼20×) than the same MLS and CloudSat averages. Comparisons of pIWP data from CloudSat and passive sensors reveal large uncertainties associated with passive techniques, such as penetration depth and sensitivity limitation. In particular, retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Sounding Unit‐B (AMSU‐B) differ largely in IWP pdf from the CloudSat R04 retrieval, showing CloudSat values generally lower (by ∼5× and ∼8×, respectively) at IWP = 10–500 g/m2 but higher at IWP > 500 g/m2.

Microwave radiative transfer in scattering atmosphere: Effects of complex permittivity of ice spherical crystals

This paper presents the effects of ice particle's complex permittivity uncertainties on the scattering properties and upwelling brightness temperatures of cloudy atmospheres at the Advanced Microwave Sounding Unit-B (AMSU-B) channel frequencies of 89, 150 and 183 GHz. We investigated the mean deviations of ice particle's optical efficiencies and asymmetry parameters due to the uncertainties in the real and imaginary parts of its complex permittivities. We assumed that the true values of ice particle's permittivity are, respectively, within ±20% for the imaginary part and ±5% for the real part of the permittivity values given by the model of Hufford. Microwave radiative transfer calculations were performed to estimate the absolute errors of brightness temperatures due to uncertainties in ice particle's permittivities. Ice particles were taken to be spherical and their diameters were chosen in the range of 40–4000 μm. Gamma-size distribution was employed in computing volume scattering properties and the effective diameters were 70, 100 and 150 μm with an effective variance being 0.25. We found that ±20% uncertainty in the imaginary part of ice particle's permittivity resulted in only about 10% mean deviations in the absorption efficiencies at the three AMSU-B channel frequencies. However, an uncertainty of ±5% in the real part resulted in more than 15% mean deviations in both scattering and extinction efficiencies, especially significant at the frequency of 183 GHz. The absolute variations of the emerging brightness temperature from the cloudy atmosphere due to uncertainties in the permittivity were found to be more than 1 K, which is already significant compared with the sensitivities achieved with today's technology for millimeter wave radiometers.

Western disturbances seen with AMSU-B and infrared sensors

Western disturbances (WD) of winter and pre-monsoon seasons are the important sources of rainfall in the Indo-Gangetic plains. WDs are troughs or circulations in the westerly winds modified by the Himalayas. Operationally, WDs are monitored using infrared (IR) and water vapour (WV) images. Advanced Microwave Sounding Unit-B (AMSU-B), flying onboard the NOAA satellites, also allows WDs to be monitored in five microwave frequencies. Two are in water vapour window (89, 150 GHz) and three are absorption channels (centred at 183.31 GHz). Unlike the top of cloud view in IR or WV, AMSU-B radiances show the effect of moisture and hydrometeors in different layers.Two cases of WD (17 April 2001 and 18–19 February 2003) are discussed using the microwave data from AMSU-B and the IR and WV data from Meteosat-5. The aim here is to demonstrate the skill of AMSU-B in delineating structure of WDs. In particular, the cold intrusion and the moist conveyor belts are examined. It was found that the multi-channel view of the AMSU-B permits a better understanding of the moist structures seen in the conveyor belts.The à trous wavelet transform is used to clearly bring out mesoscale features in WDs. AMSU-B brings out intense convection as a large depression of BTs (>50K) at 150/176 GHz, cirrus and moist bands at 180/182 GHz. Mesoscale convection lines within WDs that last short time are shown here for the first time only in the AMSU-B images. Large-scale cirrus features are separated using the à trous wavelet transform.Lastly, it is shown that there is a good likeness in the rain contours in the 3-h rain 3B42 (computed from TRMM and other data) to AMSU-B depressions in BT. Overall, AMSU-B shows better skill in delineating the structure of clouds and rain in WDs.

Arctic Total Water Vapor: Comparison of Regional Climate Simulations with Observations, and Simulated Decadal Trends

Abstract Satellite-retrieved data of total water vapor (TWV) over the Arctic are patchy, with large areas of missing data because of various limitations of the retrieval algorithms. To overcome these observational difficulties, a new retrieval algorithm has been developed that allows for monitoring the TWV over the Arctic during most of the year. This method retrieves TWV from satellite microwave radiometer data [the Advanced Microwave Sounding Unit B (AMSU-B)]. These new data have been made available for 4 yr (2000–03) and have been used to evaluate high-resolution simulations with the Arctic regional atmospheric climate model HIRHAM at daily, monthly, and seasonal time scales. The strong dynamic TWV variability on the daily time scale, linked with moisture transport by weather systems, is discussed for selected case studies. Both the simulated climatological seasonal mean patterns and the variability on interannual and decadal time scales are in agreement with those of the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data. Trends in Arctic TWV for 1958–2001, broken down by season, are presented. Although an increase in the TWV is obvious in all seasons, there are also regions where a decreasing trend appears. Significant maximum positive trends are calculated over the western Arctic in summer (up to 0.06 kg m−2 yr−1), and a significant small negative trend is calculated over the East Siberian Sea in winter.

An algorithm to detect tropical deep convective clouds through AMSU-B water vapor channels

An algorithm to detect tropical deep convective clouds and deep convective overshootings based on the measurements from the three water vapor channels (183.3 GHz±1 GHz, 183.3 GHz±3 GHz and 183.3 GHz±7 GHz) of the Advanced Microwave Sounding Unit-B (AMSU-B) is presented. This algorithm is an improved version of the method of Hong et al. (2005). The proposed procedure is based on the statistical analysis of seven years’ (2001–2007) measurements from AMSU-B on NOAA-16. From the 1-d histograms of the brightness temperature of the three water vapor channels and the 2-d histograms of the brightness temperature difference between these channels, new thresholds for brightness temperature differences and the brightness temperature of channel 18 (183.3 GHz±1 GHz) are suggested. The new algorithm is employed to investigate the mean distribution of tropical deep convective clouds and convective overshootings from 30°S to 30°N for the years 2001 to 2007. The major concentration of deep convective clouds and convective overshootings is found over the Intertropical Convergence Zone (ITCZ), the South Pacific Convergence Zone (SPCZ), tropical Africa, South America, the Indian Ocean and Indonesia with an average fraction of 0.4%. In terms of these clouds we identify the secondary Intertropical Convergence Zone located in the eastern South Pacific and parallel to the main ITCZ in the North Pacific. The convective overshooting is more frequently observed over land than over the ocean.

Evaluation of Coincident Passive Microwave Rainfall Estimates Using TRMM PR and Ground Measurements as References

Abstract This study compares instantaneous rainfall estimates provided by the current generation of retrieval algorithms for passive microwave sensors using retrievals from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and merged surface radar and gauge measurements over the continental United States as references. The goal is to quantitatively assess surface rain retrievals from cross-track scanning microwave humidity sounders relative to those from conically scanning microwave imagers. The passive microwave sensors included in the study are three operational sounders—the Advanced Microwave Sounding Unit-B (AMSU-B) instruments on the NOAA-15, -16, and -17 satellites—and five imagers: the TRMM Microwave Imager (TMI), the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) instrument on the Aqua satellite, and the Special Sensor Microwave Imager (SSM/I) instruments on the Defense Meteorological Satellite Program (DMSP) F-13, -14, and -15 satellites. The comparisons with PR data are based on “coincident” observations, defined as instantaneous retrievals (spatially averaged to 0.25° latitude and 0.25° longitude) within a 10-min interval collected over a 20-month period from January 2005 to August 2006. Statistics of departures of these coincident retrievals from reference measurements as given by the TRMM PR or ground radar and gauges are computed as a function of rain intensity over land and oceans. Results show that over land AMSU-B sounder rain retrievals are comparable in quality to those from conically scanning radiometers for instantaneous rain rates between 1.0 and 10.0 mm h−1. This result holds true for comparisons using either TRMM PR estimates over tropical land areas or merged ground radar/gauge measurements over the continental United States as the reference. Over tropical oceans, the standard deviation errors are comparable between imager and sounder retrievals for rain intensities above 5 mm h−1, below which the imagers are noticeably better than the sounders; systematic biases are small for both imagers and sounders. The results of this study suggest that in planning future satellite missions for global precipitation measurement, cross-track scanning microwave humidity sounders on operational satellites may be used to augment conically scanning microwave radiometers to provide improved temporal sampling over land without degradation in the quality of precipitation estimates.

Interannual to Diurnal Variations in Tropical and Subtropical Deep Convective Clouds and Convective Overshooting from Seven Years of AMSU-B Measurements

Abstract This study surveys interannual to diurnal variations of tropical deep convective clouds and convective overshooting using the Advanced Microwave Sounding Unit B (AMSU-B) aboard the NOAA polar orbiting satellites from 1999 to 2005. The methodology used to detect tropical deep convective clouds is based on the advantage of microwave radiances to penetrate clouds. The major concentrations of tropical deep convective clouds are found over the intertropical convergence zone (ITCZ), the South Pacific convergence zone (SPCZ), tropical Africa, the Indian Ocean, the Indonesia maritime region, and tropical and South America. The geographical distributions are consistent with previous results from infrared-based measurements, but the cloud fractions present in this study are lower. Land–ocean and Northern–Southern Hemisphere (NH–SH) contrasts are found for tropical deep convective clouds. The mean tropical deep convective clouds have a slightly decreasing trend with −0.016% decade−1 in 1999−2005 while the mean convective overshooting has a distinct decreasing trend with −0.142% decade−1. The trends vary with the underlying surface (ocean or land) and with latitude. A secondary ITCZ occurring over the eastern Pacific between 2° and 8°S and only in boreal spring is predominantly found to be associated with cold sea surface temperatures in La Niña years. The seasonal cycles of deep convective cloud and convective overshooting are stronger over land than over ocean. The seasonal migration is pronounced and moves south with the sun from summer to winter and is particularly dramatic over land. The diurnal cycles of deep convective clouds and convective overshooting peak in the early evening and have their minima in the late morning over the tropical land. Over the tropical ocean the diurnal cycles peak in the morning and have their minima in the afternoon to early evening. The diurnal cycles over the NH and SH subtropical regions vary with the seasons. The local times of the maximum and minimum fractions also vary with the seasons. As the detected deep convective cloud fractions are sensitive to the algorithms and satellite sensors used and are influenced by the life cycles of deep convective clouds, the results presented in this study provide information complementary to present tropical deep convective cloud climatologies.

Improved Retrieval of Total Water Vapor Over Polar Regions From AMSU-B Microwave Radiometer Data

The polar regions are among those where the least information is available about the current and predicted states of surface and atmosphere. We present advances in a method to retrieve the total water vapor (TWV) of the polar atmosphere from data from spaceborne microwave radiometers such as the Advanced Microwave Sounding Unit B (AMSU-B) on the polar-orbiting satellites of the National Oceanic and Atmospheric Administration (NOAA), NOAA-15, -16, and -17. The starting point of the retrieval is a recently proposed algorithm that uses the three AMSU-B channels centered around the 183-GHz water vapor line and the window channel at 150 GHz, and that can retrieve the TWV with little dependence on the surface emissivity. This works up to TWV values of about 7 kg/m2. We extend the retrievable range toward higher TWV values by including the window channel at 89 GHz. However, now, the algorithm needs information on the surface emissivity, which we have extracted from emissivity measurements over sea ice and open water during the Surface Emissivities in Polar Regions-Polar Experiment campaign. The resulting algorithm can retrieve TWV up to about 15 kg/m2, with reduced accuracy as compared to the original algorithm. It now allows the monitoring of the TWV over the central Arctic sea ice and over Antarctica, and the surrounding sea ice during most of the year with a spatial resolution of about 50 km. Such TWV fields can show details which might be missed out by standard weather model analysis data.