Advanced Microwave Sounding Unit-B Research Articles

Observation of a Lunar Eclipse at 89, 150, and 183 GHz

We describe the measurement of the brightness temperature of the Moon from space during a total lunar eclipse by using a microwave sounder aboard a weather satellite. Previous observations of lunar eclipses were inconsistent and did not cover the frequency range between 100 and 200 GHz. In this work, we seek to establish a reliable relationship between frequency and drop in brightness temperature during a total eclipse for millimeter wavelengths. For this purpose, we chose the eclipse on 2004 October 28, because it coincided with appearances of the Moon in the deep space view of the Advanced Microwave Sounding Unit-B on NOAA-15. It was therefore possible to measure its disk-integrated radiance at 89, 150, and 183 GHz at 100 minutes intervals. Our observations are, to the best of our knowledge, the only ones between 100 and 200 GHz, and demonstrate the nearly linear dependency on frequency of the maximum relative drop in effective temperature during an eclipse. The slope of this function is m = 0.00114 ± 0.00017 GHz−1 in the range 88–300 GHz. The good agreement between the variations of the effective lunar temperature and a new radiative-transfer model suggests that the Moon is suitable as a flux standard for microwave observations with beam sizes larger than 0.5°.

Assessing the consistency of satellite-derived upper tropospheric humidity measurements

Abstract. Four upper tropospheric humidity (UTH) datasets derived from satellite sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The datasets include UTH computed from brightness temperature measurements of the 183.31±1 GHz channel of the Special Sensor Microwave – Humidity (SSM/T-2), Advanced Microwave Sounding Unit-B (AMSU-B), and Microwave Humidity Sounder (MHS) and from channel 12 of the High-resolution Infrared Radiation Sounder (HIRS). The four datasets are generally consistent in the interannual temporal and spatial variability of the tropics. Large positive anomalies peaked over the central equatorial Pacific region during El Niño events in the same phase with the increase of sea surface temperature (SST). Conversely, large negative anomalies were obtained during El Niño events when the tropical-domain average is taken. The weakened ascending branch of the Pacific Walker circulation in the western Pacific and the enhanced descending branches of the local Hadley circulation along the Pacific subtropics largely contributed to widespread drying areas and thus negative anomalies in the upper troposphere during El Niño events as shown in all four datasets. During a major El Niño event, UTH had higher correlations with the coincident precipitation (0.60 to 0.75) and with 200 hPa velocity potential (−0.42 to −0.64) than with SST (0.37 to 0.49). Due to differences in retrieval definitions and gridding procedures, there can be a difference of 3 %–5 % UTH between datasets on average, and larger magnitudes of anomaly values are usually observed in spatial maps of microwave UTH data. Nevertheless, the tropical-domain averaged anomalies of the datasets are close to each other with their differences being mostly less than 0.5 %, and more importantly the phases of the time series are generally consistent for variability studies.

A New Method for Hail Detection from the GPM Constellation: A Prospect for a Global Hailstorm Climatology

A new method for detecting hailstorms by using all the MHS-like (MHS, Microwave Humidity Sounder) satellite radiometers currently in orbit is presented. A probability-based model originally designed for AMSU-B/MHS-based (AMSU-B, Advanced Microwave Sounding Unit-B) radiometers has been fitted to the observations of all microwave radiometers onboard the satellites of the Global Precipitation Measurements (GPM) constellation. All MHS-like frequency channels in the 150–170 GHz frequency range were adjusted on the MHS channel 2 (157 GHz) in order to account for the instrumental differences and tune the original model on the MHS-like technical characteristics. The novelty of this approach offers the potential of retrieving a uniform and homogeneous hail dataset on the global scale. The application of the hail detection model to the entire GPM constellation demonstrates the high potential of this generalized model to map the evolution of hail-bearing systems at very high temporal rate. The results on the global scale also demonstrate the high performances of the hail model in detecting the differences of hailstorm structure across the two hemispheres by means of a thorough reconstruction of the seasonality of the events particularly in South America where the largest hailstones are typically observed.

Improved water vapour retrieval from AMSU-B and MHS in the Arctic

Abstract. Monitoring of water vapour in the Arctic on long timescales is essential for predicting Arctic weather and understanding climate trends, as well as addressing its influence on the positive feedback loop contributing to Arctic amplification. However, this is challenged by the sparseness of in situ measurements and the problems that standard remote sensing retrieval methods for water vapour have in Arctic conditions. Here, we present advances in a retrieval algorithm for vertically integrated water vapour (total water vapour, TWV) in polar regions from data of satellite-based microwave humidity sounders: (1) in addition to AMSU-B (Advanced Microwave Sounding Unit-B), we can now also use data from the successor instrument MHS (Microwave Humidity Sounder), and (2) artefacts caused by high cloud ice content in convective clouds are filtered out. Comparison to in situ measurements using GPS and radiosondes during 2008 and 2009, as well as to radiosondes during the N-ICE2015 campaign and to ERA5 reanalysis, show the overall good performance of the updated algorithm.

A new climate data record of upper-tropospheric humidity from microwave observations

We generated a new Climate Data Record (CDR) of Upper Tropospheric Humidity (UTH) based on observations from the microwave sounders Special Sensor Microwave Temperature - 2 (SSMT-2), Advanced Microwave Sounding Unit - B (AMSU-B) and Microwave Humidity Sounder (MHS). The data record covers the time period between 1994 and 2017 and provides monthly mean 183.31 ± 1 GHz brightness temperatures and derived UTH along with estimates of measurement uncertainty on a 1° × 1° latitude-longitude grid covering the tropical region (30° S to 30° N). For the UTH retrieval we introduce a new definition of UTH. Forgoing the use of the humidity Jacobian as a weighting function, it is easier to apply than the traditional definition without compromising the retrieval accuracy. The same definition can be used to derive UTH from infrared observations, allowing for a more synergistic use of infrared and microwave UTH in the future. The new UTH CDR is validated against an existing UTH data record.

An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic

An advanced algorithm for atmospheric water vapor column (WVC) retrieval from the Advanced Microwave Scanning Radiometer (AMSR) measurements over the Arctic sea ice (SI) and open ocean waters is presented. The algorithm is built on the physical modeling of the brightness temperature (BT) of the microwave radiation of the SI–open ocean–atmosphere system at the AMSR frequencies and polarizations. The BTs are calculated using a data set of the SI, atmospheric, and oceanic parameters changing in the range of their natural variability in the Arctic, and using the SI microwave emission coefficients varied according to the published experimental data. The inverse operator explores neural networks (NNs), trained on an ensemble of modeled BTs. The algorithm is applied both to the AMSR-E and to the AMSR2 measurement data. Validation of the algorithm is performed with radiosonde (r/s) WVC measurements from the four Arctic coastal stations at different SI conditions during 2014–2017. The results of the application of the new algorithm to satellite radiometer measurements are also compared with the Era-Interim reanalysis WVC, as well as with other satellite WVC products, based on the data of the Moderate Resolution Imaging Spectrometer (MODIS) and on the data of the Advanced Microwave Sounding Unit-B (AMSU-B) for 2008 and 2015. To justify the usage of the Era-Interim WVC as a reference data set for the algorithm accuracy estimation in the Arctic area, Era-Interim WVC is also compared with the r/s WVC measurements.

Radiometric correction of observations from microwave humidity sounders

Abstract. The Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) are total power microwave radiometers operating at frequencies near the water vapor absorption line at 183 GHz. The measurements of these instruments are crucial for deriving a variety of climate and hydrological products such as water vapor, precipitation, and ice cloud parameters. However, these measurements are subject to several errors that can be classified into radiometric and geometric errors. The aim of this study is to quantify and correct the radiometric errors in these observations through intercalibration. Since the bias in the calibration of microwave instruments changes with scene temperature, a two-point intercalibration correction scheme was developed based on averages of measurements over the tropical oceans and nighttime polar regions. The intercalibration coefficients were calculated on a monthly basis using measurements averaged over each specified region and each orbit, then interpolated to estimate the daily coefficients. Since AMSU-B and MHS channels operate at different frequencies and polarizations, the measurements from the two instruments were not intercalibrated. Because of the negligible diurnal cycle of both temperature and humidity fields over the tropical oceans, the satellites with the most stable time series of brightness temperatures over the tropical oceans (NOAA-17 for AMSU-B and NOAA-18 for MHS) were selected as the reference satellites and other similar instruments were intercalibrated with respect to the reference instrument. The results show that channels 1, 3, 4, and 5 of AMSU-B on board NOAA-16 and channels 1 and 4 of AMSU-B on board NOAA-15 show a large drift over the period of operation. The MHS measurements from instruments on board NOAA-18, NOAA-19, and MetOp-A are generally consistent with each other. Because of the lack of reference measurements, radiometric correction of microwave instruments remain a challenge, as the intercalibration of these instruments largely depends on the stability of the reference instrument.

Inter-channel uniformity of a microwave sounder in space

Abstract. We analyzed intrusions of the Moon in the deep space view of the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite and found no significant discrepancies in the signals from the different sounding channels between 2001 and 2008. However, earlier investigations had detected biases of up to 10 K, by using simultaneous nadir overpasses of NOAA-16 with other satellites. These discrepancies in the observations of Earth scenes cannot be due to non-linearity of the receiver or contamination of the deep space view without affecting the signal from the Moon as well. As neither major anomalies of the on-board calibration target nor the local oscillator were present, we consider radio frequency interference in combination with a strongly decreasing gain the most obvious reason for the degrading photometric stability. By means of the chosen example we demonstrate the usefulness of the Moon for investigations of the performance of microwave sounders in flight.

Noise performance of microwave humidity sounders over their lifetime

Abstract. The microwave humidity sounders Special Sensor Microwave Water Vapor Profiler (SSMT-2), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) to date have been providing data records for 25 years. So far, the data records lack uncertainty information essential for constructing consistent long time data series. In this study, we assess the quality of the recorded data with respect to the uncertainty caused by noise. We calculate the noise on the raw calibration counts from the deep space views (DSVs) of the instrument and the noise equivalent differential temperature (NEΔT) as a measure for the radiometer sensitivity. For this purpose, we use the Allan deviation that is not biased from an underlying varying mean of the data and that has been suggested only recently for application in atmospheric remote sensing. Moreover, we use the bias function related to the Allan deviation to infer the underlying spectrum of the noise. As examples, we investigate the noise spectrum in flight for some instruments. For the assessment of the noise evolution in time, we provide a descriptive and graphical overview of the calculated NEΔT over the life span of each instrument and channel. This overview can serve as an easily accessible information for users interested in the noise performance of a specific instrument, channel and time. Within the time evolution of the noise, we identify periods of instrumental degradation, which manifest themselves in an increasing NEΔT, and periods of erratic behaviour, which show sudden increases of NEΔT interrupting the overall smooth evolution of the noise. From this assessment and subsequent exclusion of the aforementioned periods, we present a chart showing available data records with NEΔT < 1 K. Due to overlapping life spans of the instruments, these reduced data records still cover without gaps the time since 1994 and may therefore serve as a first step for constructing long time series. Our method for count noise estimation, that has been used in this study, will be used in the data processing to provide input values for the uncertainty propagation in the generation of a new set of Fundamental Climate Data Records (FCDRs) that are currently produced in the project Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO).

Impact of radiance data assimilation on the prediction performance of cyclonic storm SIDR using WRF-3DVAR modelling system

This study attempts to investigate the impact of assimilation of satellite radiances and its role to improve the model initial condition and forecast of Bay of Bengal cyclone ‘Sidr’ by using the weather research and forecasting model and its three-dimensional variational data assimilation system. Results signify that the assimilation of high-resolution satellite radiances of advanced microwave sounding unit B (AMSU-B) data at peak channels has led to significant improvement in the initial fields of the storm structure. It improved the initial condition of moisture profile more significantly than the temperature profile, when radiances are assimilated into the model. In addition, the assimilation of AMSU-B showed a more positive impact on the prediction of the track and intensity of the storm than the assimilation of radiances of advanced microwave sounding unit A (AMSU-A) and high-resolution infra-red sounder (HIRS). The assimilation exercise with all observations (NCEP PREBUFR, AMSU-A, AMSU-B, HIRS, microwave humidity sounder, and atmospheric infra-red sounder) indicate that the track errors are reduced by about 46, 62, 90, and 86%, respectively, at 24, 48, 72, and 96 h forecasts compared to the experiment considering without data assimilation. The landfall, intensity, and structure of storm are well captured when all observations are assimilated into the model. Overall, it is concluded that assimilation of radiances is beneficial for the analysis and forecast of the storm. The results suggest that assimilating of both NCEP PREBUFR and radiance observations into the mesoscale model improves the initial condition and forecast of the storm.

Calibration of Millimeter Wave Sounder Radiometers on Polar Orbiting Satellites

This paper discusses the radiometric calibration of millimeter sounder radiometers, on polar orbiter satellites in the NASA Global Precipitation Mission (GPM) constellation; and presents radiometric bias results. Because the Tropical Rainfall Measurement Mission (TRMM) operated for over 17 years, it is important to combine the TRMM and the GPM precipitation datasets to produce a climate data record for global climate change studies. In the last decade of TRMM's operation, sounder radiometers were introduced into the TRMM constellation, which included: Advanced Microwave Sounding Unit-B sensors flown on NOAA weather satellites and the microwave humidity sounders sensors flown on NOAA and meteorological operational satellite program satellites. These sensors have provided an invaluable dataset of radiance measurements with full earth coverage, which has been used in precipitation measurements, weather prediction, and climate studies.

Surface Emissivity at Microwaves to Millimeter Waves over Polar Regions: Parameterization and Evaluation with Aircraft Experiments

AbstractThe Tool to Estimate Land Surface Emissivity from Microwave to Submillimeter Waves (TELSEM2) is linked to a climatology of monthly emissivity estimates and provides a parameterization of the surface emissivity up to 700 GHz, in the framework of the preparation for the Ice Cloud Imager (ICI) on board the Meteorological Operational Satellite Second Generation (MetOp-SG). It is an updated version of the Tool to Estimate Land Surface Emissivities at Microwave Frequencies (TELSEM; Aires et al. 2011). This study presents the parameterization of continental snow and ice and sea ice emissivities in TELSEM2. It relies upon satellite-derived emissivities up to 200 GHz, and it is anchored to the Special Sensor Microwave Imager (SSM/I) TELSEM monthly climatology dataset (19–85 GHz). Emissivities from Météo-France and the National Oceanic and Atmospheric Administration (NOAA) at frequencies up to 190 GHz were used, calculated from the Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Microwave Sounding Unit-B (AMSU-B) observations. TELSEM2 has been evaluated up to 325 GHz with the observations of the International Submillimeter Airborne Radiometer (ISMAR) and the Microwave Airborne Radiometer Scanning System (MARSS), which were operated on board the Facility for Airborne Atmospheric Measurements (FAAM) aircraft during the Cold-Air Outbreak and Submillimeter Ice Cloud Study (COSMICS) campaign over Greenland. Above continental snow and ice, TELSEM2 is very consistent with the aircraft estimates in spatially homogeneous regions, especially at 89 and 157 GHz. Over sea ice, the aircraft estimates are very variable spatially and temporally, and the comparisons with the TELSEM2 were not conclusive. TELSEM2 will be distributed in the new version of the RTTOV radiative transfer community code, to be available in 2017.

Impacts from assimilation of one data stream of AMSU‐A and MHS radiances on quantitative precipitation forecasts

Since the launch of the NOAA‐15 satellite in 1998, the observations from microwave temperature and humidity sounders have been routinely disseminated to user communities through two separate data streams. In the Advanced Microwave Sounding Unit‐A (AMSU‐A) data stream, brightness temperatures in 15 channels are available primarily for profiling atmospheric temperature from the Earth's surface to the low stratosphere. In the Advanced Microwave Sounding Unit‐B (AMSU‐B) or Microwave Humidity Sounder (MHS) data stream, the brightness temperatures in five channels are included for sounding water vapour in the low troposphere. Assimilation of microwave radiance data in numerical weather prediction systems has also been carried out with AMSU‐A and AMSU‐B (MHS) data in two separate data streams. A new approach is to combine AMSU‐A and MHS radiances into one data stream for their assimilation. The National Centers for Environmental Prediction Gridpoint Statistical Interpolation analysis system and the Advanced Research Weather Research and Forecast model are employed for testing the impacts of the combined datasets. It is shown that the spatial collocation between MHS and AMSU‐A fields of view in the one data stream experiment allows for an improved quality control of MHS data, especially over the conditions where the liquid‐phase clouds are dominant. As a result, a closer fit of analyses to AMSU‐A and MHS observations is obtained, especially for AMSU‐A surface‐sensitive channels. The quantitative precipitation forecast skill is improved over a 10‐day period when Hurricane Isaac made landfall.

A microwave satellite water vapour column retrieval for polar winter conditions

Abstract. A new microwave satellite water vapour retrieval for the polar winter atmosphere is presented. The retrieval builds on the work of Miao et al. (2001) and Melsheimer and Heygster (2008), employing auxiliary information for atmospheric conditions and numerical optimization. It was tested using simulated and actual measurements from the Microwave Humidity Sounder (MHS) satellite instruments. Ground truth was provided by the G-band vapour radiometer (GVR) at Barrow, Alaska. For water vapour columns less than 6 kg m−2, comparisons between the retrieval and GVR result in a root mean square (RMS) deviation of 0.39 kg m−2 and a systematic bias of 0.08 kg m−2. These results are compared with RMS deviations and biases at Barrow for the retrieval of Melsheimer and Heygster (2008), the AIRS and MIRS satellite data products, and the ERA-Interim, NCEP, JRA-55, and ASR reanalyses. When applied to MHS measurements, the new retrieval produces a smaller RMS deviation and bias than for the earlier retrieval and satellite data products. The RMS deviations for the new retrieval were comparable to those for the ERA-Interim, JRA-55, and ASR reanalyses; however, the MHS retrievals have much finer horizontal resolution (15 km at nadir) and reveal more structure. The new retrieval can be used to obtain pan-Arctic maps of water vapour columns of unprecedented quality. It may also be applied to measurements from the Special Sensor Microwave/Temperature 2 (SSM/T2), Advanced Microwave Sounding Unit B (AMSU-B), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Technology Microwave Sounder (ATMS), and Chinese MicroWave Humidity Sounder (MWHS) instruments.

An assessment of the consistency between satellite measurements of upper tropospheric water vapor

AbstractWe assess the consistency of the satellite‐based observations of upper tropospheric water vapor (UTWV) by comparing brightness temperature measurements from the channel 12 of High‐Resolution Infrared Radiation Sounder (HIRS), the 183.31 ± 1 GHz channel of Advanced Microwave Sounding Unit‐B (AMSU‐B)/Microwave Humidity Sounder (MHS), and spectral radiances from the Atmospheric Infrared Sounder (AIRS). All three products exhibit consistent spatial and temporal patterns of interannual variability. On decadal time scales, the spatial patterns of trends are similar between all three products; however, the amplitude of the regional trends is noticeably weaker in the HIRS measurements than in either the AMSU‐B/MHS or AIRS data. This presumably reflects the greater clear‐sky sampling limitations of HIRS relative to the other products. However, when averaged over tropical or near‐global spatial scales, the trends between all three products are statistically indistinguishable from each other. The overall consistency between all three products provides important verification of their credibility for documenting long‐term changes in UTWV. A similar analysis is performed for reanalysis‐produced and model‐simulated UTWV using the HIRS record as a benchmark. On decadal time scales, both reanalysis data sets and the multimodel ensemble mean have difficulty in capturing the observed moistening of climatologically dry regions of the subtropics, although the model‐simulated trends are more consistent with the HIRS measurements than the reanalysis data.

Detectability of Polar Mesocyclones and Polar Lows in Data From Space-Borne Microwave Humidity Sounders

Polar lows are small intense low-pressure systems over polar seas associated with strong winds and heavy snowfall. Because of small scale and short lifetime, they are often missed by weather observation networks. As they can significantly affect ships and coastal communities and can have a large impact on lateral heat and moisture transport, better observation of polar lows with satellites is worthwhile. Here, we assess the detectability of polar lows using data from the microwave humidity sounders advanced microwave sounding unit-B (AMSU-B) and microwave humidity sounder (MHS) on the polar-orbiting satellites of NOAA. It turns out that cloud ice and frozen precipitation in polar lows cause strong scattering of upwelling atmospheric emission in the three water vapor channels around 183.31 GHz. As a result, most polar lows can be detected in brightness temperature differences of the water vapor channels as small areas of reversed sign. Out of 110 confirmed polar lows in the Nordic Seas, 85% could be clearly detected with AMSU-B. Looking for all polar-low-like signatures in AMSU-B/MHS data, we found about twice as many cases as the most thorough remote sensing inventory of polar lows published so far. The main reason is that in contrast to that inventory, we did not impose a minimum wind criterion which would need wind data from other sources. However, using the AMSU-B/MHS brightness temperature differences can be a quick tool to detect possible polar lows in near real time and this can equally well be applied to similar microwaves sounders operational on current and future satellites.

Impacts of radiance data assimilation on the Beijing 7.21 heavy rainfall

Precipitation simulation during the Beijing heavy rainfall event on 21 July 2012 has been investigated in this study. A control run of the Weather Research and Forecasting (WRF) model can roughly simulate the mesoscale features and spatial heterogeneity of precipitation over North China, but it cannot capture the locations, intensity and timing of maximum rainfall over the Beijing area compared with ground observations. To gain better initial conditions in the performance of the mesoscale model, Advanced Microwave Sounding Unit (AMSU) radiance data assimilation was carried out. The spatial distribution and intensity of precipitation have been significantly improved. In particular, data assimilation of Advanced Microwave Sounding Unit-A only has similar impacts on heavy rainfall simulation as the AMSU data assimilation run. Data assimilation of Advanced Microwave Sounding Unit-B only has improved the spatial distribution of heavy rainfall, but it has little impact on the intensity of rainfall. However, the timing of heavy rainfall in all simulations is about 5 to 6h later than observations. Further analysis shows that the center and strength of the low-pressure system was not well simulated during the early development of heavy rainfall in the model. Results from radiance data assimilation suggest that improvement of the initial conditions plays a positive impact on heavy rainfall in 24h simulation. Operational forecast system including satellite radiance data assimilation may improve heavy rainfall forecasting.

Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

The impact of one or two missing passive microwave (PMW) input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA) products were reproduced and re-released by National Aeronautics and Space Administration (NASA) Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B) and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16) input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the “early” and “late” Version-7 TMPA real-time (TMPA-RT) precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors) with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km2). The retrieval counts and retrieval frequency of various PMW and Infrared (IR) sensors incorporated into the TMPA system were also analyzed to identify and diagnose the impacts of sensor availability on the TMPA-RT retrieval accuracy. Results show that the incorporation of AMSU-B and SSMIS-F16 has substantially reduced systematic errors. The improvement exhibits rather strong seasonal and topographic dependencies. Our analyses suggest that one or two single PMW sensors might play a key role in affecting the end product of current combined microwave-infrared precipitation estimates. This finding supports algorithm developers’ current endeavor in spatiotemporally incorporating as many PMW sensors as possible in the multi-satellite precipitation retrieval system called Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG). This study also recommends users of satellite precipitation products to switch to the newest Version-7 TMPA datasets and the forthcoming IMERG products whenever they become available.

Investigating the Ice Water Path in Convective Cloud Life Cycles to Improve Passive Microwave Rainfall Retrievals

Abstract This study focuses on the possible relationship between ice water path (IWP) retrievals using high-frequency channels (89 and 150 GHz) from the Advanced Microwave Sounding Unit-B and Moisture Humidity Sounder sensors (NOAA-16–NOAA-19) and the life cycle stage of convective clouds. In the first part of this study, the relationship between IWP and the cloud area expansion rate is analyzed using the 235-K isotherm from Geostationary Operational Environmental Satellite-12 (GOES-12) thermal infrared images (10.7 μm). Next, the relationships between cloud convective fraction, rain rates (from ground radar), and cloud life cycle are analyzed. The selected area and time period coincide with the research activities of the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the Global Precipitation Measurement (CHUVA)–Geostationary Lightning Mapper (GLM) project at São José dos Campos, Brazil. The results show that 84% of precipitating clouds contain ice, according to the Microwave Surface and Precipitation Products System (MSPPS) algorithm. Convective systems in the intensifying stage (when the area is expanding and the minimum temperature is decreasing) tend to have larger IWPs than systems in the dissipating stage. Larger rain rates and convective fractions are also observed from radar retrievals in the early stage of convection compared with mature systems. Hydrometeor retrieval data from polarimetric X-band radar suggest that particle effective diameter De and IWP patterns inferred with the MSPPS algorithm could be used to determine the life cycle stage of a given convective system. Using this information, a new set of equations is evaluated for rainfall retrievals using De and IWP from the current retrieval algorithm. This new approach outperforms the current algorithm in the studied region.

Patterns of Precipitation and Convection Occurrence over the Mediterranean Basin Derived from a Decade of Microwave Satellite Observations

The Mediterranean region is characterized by its vulnerability to changes in the water cycle, with the impact of global warming on the water resources being one of the major concerns in social, economical and scientific ambits. Even if precipitation is the best-known term of the Mediterranean water budget, large uncertainties remain due to the lack of suitable offshore observational data. In this study, we use the data provided by the Advanced Microwave Sounding Unit-B (AMSU-B) on board NOAA satellites to detect and analyze precipitating and convective events over the last decade at spatial resolution of 0.2° latitude × 0.2° longitude. AMSU-B observation shows that rain occurrence is widespread over the Mediterranean in wintertime while reduced in the eastern part of the basin in summer. Both precipitation and convection occurrences display a weak diurnal cycle over sea. In addition, convection occurrences, which are essentially located over land during summertime, shift to mostly over the sea during autumn with maxima in the Ionian sub-basin and the Adriatic Sea. Precipitation occurrence is also inferred over the sea from two other widely used climatological datasets, HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis interim (ERA-Interim). There is generally a rather fair agreement between these climatologies for describing the large-scale patterns such as the strong latitudinal gradient of rain and eastward rain signal propagation. Furthermore, the higher spatial resolution of AMSU-B measurements (16 km at nadir) gives access to mesoscale details in the region (e.g., coastal areas). AMSU-B measurements show less rain occurrences than HOAPS during wintertime, thereby suggesting that some of the thresholds used in our method might be too stringent during this season. We also observed that convection occurrences in ERA-Interim are systematically lower than those derived from AMSU-B. These results are potentially valuable to evaluate the rainfall parameterization in weather and climate models and to constrain ocean models.