Passive millimeter-wave retrieval of global precipitation utilizing satellites and a numerical weather prediction model

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 229-234).This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for icy hydrometeors (F([lambda])), to be used as a global precipitation ground-truth for evaluating alternative millimeter-wave satellite designs and for developing methods for millimeter-wave precipitation retrieval and assimilation. The model's predicted millimeter-wave atmospheric radiances were found to statistically agree with those observed by satellite instruments [Advanced Microwave Sounding Unit-A/B (AMSU-A/B)] on the United States National Ocean and Atmospheric Administration NOAA-15, -16, and -17 satellites over 122 global representative storms. Whereas such radiance agreement was found to be sensitive to assumptions in MM5 and the radiative transfer model, precipitation retrieval accuracies predicted using the MM5/TBSCAT/F([lambda]) model were found to be robust to the assumptions.(cont.) Appropriate specifications for geostationary microwave sounders and their precipitation retrieval accuracies were studied. It was found that a 1.2-m micro-scanned filled-aperture antenna operating at 118/166/183/380/425 GHz, which is relatively inexpensive, simple to build, technologically mature, and readily installed on a geostationary satellite, could provide useful observation of important global precipitation with ~20-km resolution every 15 minutes. AMSU global precipitation retrieval algorithms for retrieving surface precipitation rate, peak vertical wind, and water-paths for rainwater, snow, graupel, cloud water, cloud ice, and the sum of rainwater, snow, and graupel, over non-icy surfaces were developed separately using a statistical ensemble of global precipitation predicted by the MM5/TBSCAT/F([lambda]) model. Different algorithms were used for land and sea, where principal component analysis was used to attenuate unwanted noises, such as surface effects and angle dependence. The algorithms were found to perform reasonably well for all types of precipitation as evaluated against MM5 ground-truth. The algorithms also work over land with snow and sea ice, but with a strong risk of false detections. AMSU surface precipitation rates retrieved using the algorithm developed in this thesis reasonably agree with those retrieved for the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) aboard the Aqua satellite over both land and sea.(cont.) Surface precipitation rates retrieved using the Advanced Microwave Sounding Unit (AMSU) aboard NOAA-15 and -16 satellites were further compared with four similar products derived from other systems that also observed the United States Great Plains (USGP) during the summer of 2004. These systems include AMSR-E aboard the Aqua satellite, the Special Sensor Microwave/Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F-13, -14, and -15 satellites, the passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) aboard the TRMM satellite, and a surface precipitation rate product (NOWRAD), produced and marketed by Weather Services International Corporation (WSI) using observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) systems of the Next-Generation Weather Radar (NEXRAD) program. The results show the reasonable agreement among these surface precipitation rate products where the difference is mostly in the retrieval resolution, which depends on instruments' characteristics. A technique for assimilating precipitation information from observed millimeter-wave radiances to MM5 model was proposed. Preliminary study shows that wind and other correction techniques could help align observations at different times so that information from observed radiances is used at appropriate locations.by Chinnawat Surussavadee.Ph.D

First observations of polarized scattering over ice clouds at close-to-millimeter wavelengths (157 GHz) with MADRAS on board the Megha-Tropiques mission

Polarized scattering by frozen hydrometeors is investigated for the first time up to 157 GHz, based on the passive microwave observations of the Microwave Analysis and Detection of Rain and Atmospheric Structures (MADRAS) instrument on board the Indo-French Megha-Tropiques satellite mission. A comparison with time-coincident Tropical Rainfall Measurement Mission Microwave Imager records confirms the consistency of the coincident observations collected independently by the two instruments up to 89 GHz. The MADRAS noise levels of 1.2 K at 89 GHz and of 2.5 K at 157 GHz are in agreement with the required specifications of the mission. Compared to the 89 GHz polarized channels that mainly sense large ice particles (snow and graupel), the 157 GHz polarized channel is sensitive to smaller particles and provides additional information on the cloud systems. The analysis of the radiometric signal at 157 GHz reveals that the ice scattering can induce a polarization difference of the order of 10 K at that frequency. Based on radiative transfer modeling the specific signature is interpreted as the effect of mainly horizontally oriented ice cloud particles. This suggests that the effects of the cloud particle orientation should be considered in rain and cloud retrievals using passive radiometry at microwave and millimeter wavelengths.Fil: Defer, Eric. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Galligani, Victoria Sol. Centre National de la Recherche Scientifique. Observatoire de Paris; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Prigent, Catherine. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Jimenez, Carlos. Centre National de la Recherche Scientifique. Observatoire de Paris; Franci

ULF Wave‐Associated Density Irregularities and Scintillation at the Equator

This paper presents independent multi‐instrument observations that address the physical mechanisms of how ultralow‐frequency (ULF) wave‐associated electric fields initiate ionospheric density fluctuation and scintillation at the equator. Since the magnetic field at the equator is entirely embedded in a relatively high‐collision and high‐conductivity medium, the condition may not be possible for the geomagnetic field to fluctuate due to ULF wave activity. This implies that the fluctuating electric field at the equator may not be produced through equatorial dynamo action due to fluctuating magnetic fields. Instead, the electric field penetrates from high latitudes and produces fluctuating magnetic field as well as modulates the vertical drift and hence causes the density to fluctuate at the equatorial region. We demonstrate this by estimating the ULF associated fluctuating electric field at high latitudes and at the equatorial region by applying the appropriate attenuation factor as it penetrates to lower latitudes. The periodicity of both electric field and density fluctuations appears to be between 6 and 9 min, which is a typical period of ULF waves in the Pc5 range. Because of its large amplitude and long periods compared to other ULF wave frequency bands, the Pc5 wave‐associated electric field, which can even be estimated using magnetograms with low sensitivity and low sampling rate (e.g., 1 min), can easily penetrate to the lower latitude region and produce significant ionospheric density fluctuations that can be strong enough to create scintillation at the equatorial region.Plain Language SummaryThe ultralow‐frequency (ULF) wave, which is believed to be generated by strong solar wind dynamic pressure at the magnetopause, can penetrate to the ionosphere and modulate high‐latitude electric field that can penetrate to equatorial latitudes and cause density irregularities in the ionosphere. Especially in the dusk to midnight local time sector, when the background density is weaker and can easily be driven up and down by small magnitude of fluctuating electric field (vertical drift), the density fluctuation becomes stronger. Such density fluctuations create favorable conditions for the creation of rapid amplitude and phase fluctuations of radio signals, which affects several technological systems such as over the horizon high‐frequency radio communication outage and increased Global Navigation Satellite System navigation errors. Thus, ionospheric density fluctuations are as much an engineering concern as they are a scientific quest, and hence understanding the physics behind the contribution of ULF wave power for the formation of small‐scale ionospheric density fluctuations is very important to develop a model that can accurately capture the structure and dynamics of the global low‐latitude ionospheric irregularities.Key PointsULF modulates high-latitude electric fieldElectric field penetrates from high to low latitudesFluctuating electric field causes scintillation at the equatorPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144582/1/grl57466.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144582/2/grl57466_am.pd

SPARE-ICE: synergistic Ice Water Path from passive operational sensors

This article presents SPARE-ICE, the Synergistic Passive Atmospheric Retrieval Experiment-ICE. SPARE-ICE is the first Ice Water Path (IWP) product combining infrared and microwave radiances. By using only passive operational sensors, the SPARE-ICE retrieval can be used to process data from at least the NOAA 15 to 19 and MetOp satellites, obtaining time series from 1998 onward. The retrieval is developed using collocations between passive operational sensors (solar, terrestrial infrared, microwave), the CloudSat radar, and the CALIPSO lidar. The collocations form a retrieval database matching measurements from passive sensors against the existing active combined radar-lidar product 2C-ICE. With this retrieval database, we train a pair of artificial neural networks to detect clouds and retrieve IWP. When considering solar, terrestrial infrared, and microwave-based measurements, we show that any combination of two techniques performs better than either single-technique retrieval. We choose not to include solar reflectances in SPARE-ICE, because the improvement is small, and so that SPARE-ICE can be retrieved both daytime and nighttime. The median fractional error between SPARE-ICE and 2C-ICE is around a factor 2, a figure similar to the random error between 2C-ICE ice water content (IWC) and in situ measurements. A comparison of SPARE-ICE with Moderate Resolution Imaging Spectroradiometer (MODIS), Pathfinder Atmospheric Extended (PATMOS-X), and Microwave Surface and Precipitation Products System (MSPPS) indicates that SPARE-ICE appears to perform well even in difficult conditions. SPARE-ICE is available for public use

High-Resolution Climate Simulations in the Tropics with Complex Terrain Employing the CESM/WRF Model

This study evaluates the high-resolution climate simulation system CESM/WRF composed of the global climate model, Community Earth System Model (CESM) version 1, and the mesoscale model, Weather Research and Forecasting Model (WRF), for simulating high-resolution climatological temperature and precipitation in the tropics with complex terrain where temperature and precipitation are strongly inhomogeneous. The CESM/WRF climatological annual and seasonal precipitation and temperature simulations for years 1980–1999 at 10 km resolution for Sumatra and nearby regions are evaluated using observations and the global climate reanalysis ERA-Interim (ERA). CESM/WRF simulations at 10 km resolution are also compared with the downscaled reanalysis ERA/WRF at 10 km resolution. Results show that while temperature and precipitation patterns of the original CESM are very different from observations, those for CESM/WRF agree well with observations. Resolution and accuracies of simulations are significantly improved by dynamically downscaling CESM using WRF. CESM/WRF can simulate locations of very cold temperature at mountain peaks well. The high-resolution climate simulation system CESM/WRF can provide useful climate simulations at high resolution for Sumatra and nearby regions. CESM/WRF-simulated climatological temperature and precipitation at 10 km resolution agree well with ERA/WRF. This suggests the use of CESM/WRF for climate projections at high resolution for Sumatra and nearby regions.Thailand. Prince of Songkla Universit

Satellite Retrievals of Arctic and Equatorial Rain and Snowfall Rates Using Millimeter Wavelengths

A new global precipitation retrieval algorithm for the millimeter-wave Advanced Microwave Sounding Unit is presented that also retrieves Arctic precipitation rates over surface snow and ice. This algorithm improves upon its predecessor by excluding some surface-sensitive channels and by reducing the number of principal components (PCs) used to represent those that remain. The training sets were also modified to better represent cold regions. The algorithm still incorporates conversion of brightness temperatures to nadir, spatial filtering to better detect pixels scattering near 54 GHz, PC filtering of surface effects, and use of separate neural networks trained with the fifth-generation National Center for Atmospheric Research/Penn State Mesoscale Model (MM5) for land and sea, where warm and cold ocean are now treated differently. The validity of the snowfall detections is supported by nearly coincident CloudSat radar observations, and the physics of the model is largely validated by the reasonable agreement in annual precipitation obtained for 231 globally distributed rain gauges, including many at latitudes where snowfall dominates. Observed annual global precipitation statistics are also presented to permit comparisons with other algorithms and sensors.National Aeronautics and Space Administration (Grant NNX07AE35G)Thailand. Prince of Songkla University (Grant PSU 977/301

Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia

This study evaluates the performances of all forty different global climate models (GCMs) that participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for simulating climatological temperature and precipitation for Southeast Asia. Historical simulations of climatological temperature and precipitation of the 40 GCMs for the 40-year period of 1960–1999 for both land and sea and those for the century of 1901–1999 for land are evaluated using observation and reanalysis datasets. Nineteen different performance metrics are employed. The results show that the performances of different GCMs vary greatly. CNRM-CM5-2 performs best among the 40 GCMs, where its total error is 3.25 times less than that of GCM performing worst. The performance of CNRM-CM5-2 is compared with those of the ensemble average of all 40 GCMs (40-GCM-Ensemble) and the ensemble average of the 6 best GCMs (6-GCM-Ensemble) for four categories, i.e., temperature only, precipitation only, land only, and sea only. While 40-GCM-Ensemble performs best for temperature, 6-GCM-Ensemble performs best for precipitation. 6-GCM-Ensemble performs best for temperature and precipitation simulations over sea, whereas CNRM-CM5-2 performs best over land. Overall results show that 6-GCM-Ensemble performs best and is followed by CNRM-CM5-2 and 40-GCM-Ensemble, respectively. The total errors of 6-GCM-Ensemble, CNRM-CM5-2, and 40-GCM-Ensemble are 11.84, 13.69, and 14.09, respectively. 6-GCM-Ensemble and CNRM-CM5-2 agree well with observations and can provide useful climate simulations for Southeast Asia. This suggests the use of 6-GCM-Ensemble and CNRM-CM5-2 for climate studies and projections for Southeast Asia

Correcting Microwave Precipitation Retrievals for near-Surface Evaporation

This paper compares two methods for correcting passive or active microwave surface precipitation estimates based on hydrometeors sensed aloft that may evaporate before landing. These corrections were derived using two years of data from 516 globally distributed rain gauges and passive millimeter-wave Advanced Microwave Sounding Units (AMSU) aboard three NOAA satellites (N15, N16, and N18). The first correction reduces rms differences between rain gauges and AMSU annual precipitation accumulations (mm) by a separate factor for each infrared-based surface classification, while the second correction factor uses a 3-2-1 neural network (NN) trained using both surface classification and annual average relative humidity profiles. Different data were used for training and accuracy evaluation. The NN results agreed with rain gauges better than did surface classification corrections alone. The rms annual accumulation errors relative to the 516 uncorrected rain gauges using AMSU with surface classification and NN corrections were 223 and 209 mm/yr, respectively, compared to 152 mm/yr for GPCP, which incorporates rain gauge data and data from more satellite sensors

Global precipitation retrieval algorithm trained for SSMIS using a numerical weather prediction model: Design and evaluation

This paper presents and evaluates a global precipitation retrieval algorithm for the Special Sensor Microwave Imager/Sounder (SSMIS). It is based on those developed earlier for the Advanced Microwave Sounding Unit (AMSU) and employs neural networks trained with 122 global storms that spanned a year and were simulated using the fifth-generation National Center for Atmospheric Research/Penn State Mesoscale Model (MM5) and a radiative transfer program validated using AMSU observations. Only non-icy surfaces at latitudes less than 50° have been analyzed because their surface effects are more predictable. Sensitivity to surface emissivity variations was reduced by using only more surface-insensitive principal components of brightness temperature. Based on MM5 simulations, retrievals for land are slightly less accurate than those for sea and all are useful for rates above 1 mm/h. F-16 SSMIS, NOAA-15 AMSU, and Global Precipitation Climatology Project (GPCP) annual estimates generally agree. SSMIS retrieves less precipitation for some areas partly due to its higher resolution that resolves precipitation better. SSMIS overestimates precipitation over under-vegetated land requiring the near-surface evaporation correction illustrated earlier for AMSU

Global Precipitation Retrievals Using the NOAA AMSU Millimeter-Wave Channels: Comparisons with Rain Gauges

A surface-precipitation-rate retrieval algorithm for 13-channel Advanced Microwave Sounding Unit (AMSU) millimeter-wave spectral observations from 23 to 191 GHz is described. It was trained using cloud-resolving fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) simulations over 106 global storms. The resulting retrievals from the U.S. NOAA-15 and NOAA-16 operational weather satellites are compared with average annual accumulations (mm yr−1) for 2006–07 observed by 787 rain gauges globally distributed across 11 surface classifications defined using Advanced Very High Resolution Radiometer infrared spectral images and two classifications defined geographically. Most surface classifications had bias ratios for AMSU/gauges that ranged from 0.88 to 1.59, although higher systematic AMSU overestimates by factors of 2.4, 3.1, and 9 were found for grassland, shrubs over bare ground, and pure bare ground, respectively. The retrievals were then empirically corrected using these observed biases for each surface type. Global images of corrected average annual accumulations of rain, snow, and convective and stratiform precipitation are presented for the period 2002–07. Most results are consistent with Global Precipitation Climatology Project estimates. Evidence based on MM5 simulations suggests that near-surface evaporation of precipitation may have necessitated most of the corrections for undervegetated surfaces. A new correction for radio-frequency interference affecting AMSU is also presented for the same two NOAA satellites and improves retrieval accuracies.United States. National Aeronautics and Space Administration (NASA) (Grant NNX07AE35G)Thailand. Prince of Songkla University (Grant PSU 977/301