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Bias correction for rainrate retrievals from satellite passive microwave sensors

Rainrates retrieved from past and present satellite-borne microwave sensors are affected by a fundamental remote sensing problem. Sensor fields-of-view are typically large enough to encompass substantial rainrate variability, whereas the retrieval algorithms, based on radiative transfer calculations, show a non-linear relationship between rainrate and microwave brightness temperature. Retrieved rainrates are systematically too low. A statistical model of the bias problem shows that bias correction factors depend on the probability distribution of instantaneous rainrate and on the average thickness of the rain layer.

Short, David A.↗

Microwave Observations of Precipitation and the Atmosphere

This research effort had three elements devoted to improving satellite-derived passive microwave retrievals of precipitation rate: morphological rain-rate retrievals, warm rain retrievals, and extension of a study of geostationary satellite options. The morphological precipitation-rate retrieval method uses for the first time the morphological character of the observed storm microwave spectra. The basic concept involves: 1) retrieval of point rainfall rates using current algorithms, 2) using spatial feature vectors of the observations over segmented multi-pixel storms to estimate the integrated rainfall rate for that storm (cu m/s), and 3) normalization of the point rain-rate retrievals to ensure consistency with the storm-wide retrieval. This work is ongoing, but two key steps have been completed: development of a segmentation algorithm for defining spatial regions corresponding to single storms for purposes of estimation, and reduction of some of the data from NAST-M that will be used to support this research going forward. The warm rain retrieval method involved extension of Aquai/AIRS/AMSU/HSB algorithmic work on cloud water retrievals. The central concept involves the fact that passive microwave cloud water retrievals over approx. 0.4 mm are very likely associated with precipitation. Since glaciated precipitation is generally detected quite successfully using scattering signatures evident in the surface-blind 54- and 183-GHz bands, this new method complements the first by permitting precipitation retrievals of non-glaciated events. The method is most successful over ocean, but has detected non-glaciated convective cells over land, perhaps in their early formative stages. This work will require additional exploration and validation prior to publication. Passive microwave instrument configurations for use in geostationary orbit were studied. They employ parabolic reflectors between 2 and 4 meters in diameter, and frequencies up to approx.430 GHz; this corresponds to nadir spot diameters as small as 10 km.

Staelin, David H.↗

User Guide for TROPICS Data Products

This document provides information for using the data products available from the “Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats” (TROPICS) mission. The TROPICS mission will produce a range of data products that will be available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The data products will be produced at the TROPICS Data Processing Center (UW-M SSEC), and consist of Level-1 radiances (antenna and brightness temperatures), Level-2a unified resolution radiance, Level-2b Atmospheric Vertical Temperature Profiles (AVTP), Level-2b Atmospheric Vertical Moisture Profiles (AVMP), Level-2b Instantaneous Surface Rain Rate (ISRR), and Level-2b Tropical Cyclone (TC) intensity algorithms to estimate two primary variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). Two independent intensity estimation methods are included: 1) the Tropical Cyclone Intensity Estimate algorithm (TCIE) developed at the University of Wisconsin/CIMSS using native microwave brightness temperatures and 2) the Hurricane Intensity and Structure Algorithm (HISA) developed at Colorado State University/CIRA using microwave retrievals of temperature, moisture, and integrated quantities. In addition to MSW and MSLP, HISA also provides estimates of surface wind radii and 2D winds at standard pressure levels. TROPICS is adapting the NOAA STAR Microwave Integrated Retrieval System (MIRS) to retrieve the AVTP and AVMP data products. The ISRR algorithm uses the NASA Goddard Precipitation Retrieval and Profiling Scheme (PRPS).

TROPICS↗

Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data

Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values.

Kurtz, Nathan T.↗

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗

A physically-based retrieval of cloud liquid water from SSM/I measurements

A simple physical scheme is proposed for retrieving cloud liquid water over the ice-free global oceans from Special Sensor Microwave/Imager (SSM/I) observations. Details of the microwave retrieval scheme are discussed, and the microwave-derived liquid water amounts are compared with the ground radiometer and AVHRR-derived liquid water for stratocumulus clouds off the coast of California. Global distributions of the liquid water path derived by the method proposed here are presented.

Greenwald, Thomas J.↗

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = −0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Soil MOisture↗

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Owe, Manfred↗

Evaluation and use of TOVS retrievals at NMC

In a current analysis procedure at the National Meteorological Center (NMC), a first guess analysis (from the latest 6 or 12 hour forecast) is updated by new data. In the newest analysis procedures, which are based on optimum interpolation, the observational correction depends on the size of preassigned, expected observational errors versus the size of expected errors in the first guess forecast. In the case of Northern Hemisphere ocean temperatures, the latter are around 2 degrees. The infrared satellite retrievals have a similar size "error". If (as assumed) their errors are uncorrelated with the first guess error, they will improve the analysis. The larger errors of the microwave retrievals, however, mean that they will be given little weight in the analysis. An evaluation of the TIROS-N retrievals is currently underway at NMC to determine the impact of satellite derived data within operational analysis schemes, to isolate possible problems within current retrieval methods, and to offer possible solutions for these problems.

Phillips, N. A.↗

IMERG V06: Changes to the Morphing Algorithm

As the US Science Team’s globally gridded precipitation product from the NASA/JAXA Global Precipitation Measurement (GPM) mission, the Integrated Multi-satellitE Retrievals for GPM (IMERG) estimates the surface precipitation rates at 0.1° every half-hour using spaceborne sensors for various scientific and societal applications. One key component of IMERG is the morphing algorithm, which uses motion vectors to perform quasi-Lagrangian interpolation to fill in gaps in the passive microwave precipitation field using motion vectors. Up to IMERG V05, the motion vectors were derived from the large-scale motions of infrared observations of cloud tops. This study details the changes introduced in IMERG V06 to derive motion vectors from large-scale motions of selected atmospheric variables in numerical models, which allow IMERG estimates to be extended from the 60°N/S latitude band to the entire globe. Evaluation against both instantaneous passive microwave retrievals and ground measurements demonstrates the general improvement in the precipitation field of the new approach. Most of the model variables tested exhibited similar performance, but total precipitable water vapor was chosen as the source of the motion vectors for IMERG V06 due to its competitive performance and global completeness. Continuing assessments will provide further insights into possible refinements of this revised morphing scheme in future versions of IMERG.

Jackson Tan↗

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with the frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.

Wilheit, Thomas T.↗

An Updated TRMM Composite Climatology of Tropical Rainfall and Its Validation

An updated 15-yr Tropical Rainfall Measuring Mission (TRMM) composite climatology (TCC) is presented and evaluated. This climatology is based on a combination of individual rainfall estimates made with data from the primaryTRMMinstruments: theTRMM Microwave Imager (TMI) and the precipitation radar (PR). This combination climatology of passive microwave retrievals, radar-based retrievals, and an algorithm using both instruments simultaneously provides a consensus TRMM-based estimate of mean precipitation. The dispersion of the three estimates, as indicated by the standard deviation sigma among the estimates, is presented as a measure of confidence in the final estimate and as an estimate of the uncertainty thereof. The procedures utilized by the compositing technique, including adjustments and quality-control measures, are described. The results give a mean value of the TCC of 4.3mm day(exp -1) for the deep tropical ocean beltbetween 10 deg N and 10 deg S, with lower values outside that band. In general, the TCC values confirm ocean estimates from the Global Precipitation Climatology Project (GPCP) analysis, which is based on passive microwave results adjusted for sampling by infrared-based estimates. The pattern of uncertainty estimates shown by sigma is seen to be useful to indicate variations in confidence. Examples include differences between the eastern and western portions of the Pacific Ocean and high values in coastal and mountainous areas. Comparison of the TCC values (and the input products) to gauge analyses over land indicates the value of the radar-based estimates (small biases) and the limitations of the passive microwave algorithm (relatively large biases). Comparison with surface gauge information from western Pacific Ocean atolls shows a negative bias (~16%) for all the TRMM products, although the representativeness of the atoll gauges of open-ocean rainfall is still in question.

(GPCP) Global Precipitation Project analysis↗

Determination of Spring Onset and Growing Season Duration using Satellite Measurements

An integrated approach to retrieve microwave emissivity difference vegetation index (EDVI) over land regions has been developed from combined multi-platform/multi-sensor satellite measurements, including SSM/I measurements. A possible relationship of the remotely sensed EDVI and the leaf physiology of canopy is exploited at the Harvard Forest site for two growing seasons. This study finds that the EDVI is sensitive to leaf development through vegetation water content of the crown layer of the forest canopy, and has demonstrated that the spring onset and growing season duration can be determined accurately from the time series of satellite estimated EDVI within uncertainties about 3 and 7 days for spring onsets and growing season duration, respectively, compared to in-situ observations. The leaf growing stage may also be quantitatively monitored by a normalized EDVI. Since EDVI retrievals from satellite are generally possible during both daytime and nighttime under non-rain conditions, the EDVI technique studied here may provide higher temporal resolution observations for monitoring the onset of spring and the duration of growing season compared to currently operational satellite methods.

Min, Q.↗

Radiative transfer to space through a precipitating cloud at multiple microwave frequencies. I - Model description. II - Results and analysis

The impact of time-dependent cloud microphysical structure on the transfer to space of passive microwave radiation is studied at several frequencies across the EHF and lower SHF portions of the microwave spectrum. The feasibility of using multichannel passive-microwave retrieval techniques to estimate precipitation from space-based platforms is examined. The model is described, and the results are assessed in conjunction with a Nimbus-7 SMMR case study of precipitation in an intense tropical Pacific storm. It is concluded that the effects of cloud liquid water content must be considered to obtain a realistic estimation and distribution of rainrates.

Mugnai, Alberto↗

Design, performance evaluation, and investigation of the theoretical capabilities of the NASA Millimeter-wave Imaging Radiometer (MIR)

The development of techniques for passive microwave retrieval of water vapor and precipitation parameters using millimeter- and sub-millimeter wavelength channels is reviewed. Channels of particular interest are in the tropospheric transmission windows at 90, 150, 220, and 340 GHz and centered around the water vapor lines at 183 and 325 GHz. Collectively, these channels have potential application in high-resolution mapping (e.g., from geosynchronous orbit), remote sensing of cloud and precipitation parameters, and retrieval of water vapor profiles. Both theoretical and experimental results to date are discussed.

Gasiewski, Albin J.↗

The Millimeter-Wave Imaging Radiometer (MIR)

The Millimeter-Wave Imaging Radiometer (MIR) is a new instrument being designed for studies of airborne passive microwave retrieval of tropospheric water vapor, clouds, and precipitation parameters. The MIR is a total-power cross-track scanning radiometer for use on either the NASA ER-2 (high-altitude) or DC-8 (medium altitude) aircraft. The current design includes millimeter-wave (MMW) channels at 90, 166, 183 +/- 1,3,7, and 220 GHz. An upgrade for the addition of submillimeter-wave (SMMW) channels at 325 +/- 1,3,7 and 340 GHz is planned. The nadiral spatial resolution is approximately 700 meters at mid-altitude when operated aboard the NASA ER-2. The MIR consists of a scanhead and data acquisition system, designed for installation in the ER-2 superpod nose cone. The scanhead will house the receivers (feedhorns, mixers, local oscillators, and preamplifiers), a scanning mirror, hot and cold calibration loads, and temperature sensors. Particular attention is being given to the characterization of the hot and cold calibration loads through both laboratory bistatic scattering measurements and analytical modeling. Other aspects of the MIR and the data acquisition system are briefly discussed, and diagrams of the location of the MIR in the ER-2 superpod nosecone and of the data acquisition system are presented.

Gasiewski, A. J.↗

Passive microwave remote sensing of precipitation from space - Impact of cloud microphysics

Numerical experiments to investigate the impact of time-dependent cloud microphysical structure on the transfer to space of passive microwave radiation are carried out, using a vertically and angularly detailed, plane-parallel radiative transfer model for unpolarized microwave radiation. The object is to explore the feasibility of multichannel passive-microwave retrieval techniques to estimate precipitation from space. Results on the time-dependent influence of large graupel-size ice particles on top-of-atmosphere brightness temperature - rainfall rate relationships at 6.6, 10.7, 18, 19.35, 22.235, 37, 89.5, 130, and 231 GHz are given. Frequency-dependent vertical profiles of a generalized brightness-temperature weighting function, introduced to vertically resolve the contributions by individual cloud and precipitation layers to the brightness temperatures, are also shown.

Mugnai, Alberto↗