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At least 217 records · Page 12

Comparison of SSM/I measurements to numerically-simulated cloud and precipitation during ERICA

These investigations focused essentially on the macroscale organization of cloud and precipitation which occurred during the 4th Intensive Observing Period (IOP-4) of the Experiment for Rapidly Intensifying Cyclones over the Atlantic (ERICA). This experiment, held off the East Coast of the United States and Canada during the winter of 1989, documented several episodes of rapid cyclonic storm development. Also playing a major role as validation and ground truth in these studies are Special Sensor Microwave Imager (SSM/I) retrievals of precipitable water, total liquid water and ice, generated by other Marshall Space Flight Center (MSFC) supported investigations. Model simulations produced to date suggest that, while the large-scale atmospheric dynamics was an essential driving mechanism, the role of condensation was crucial in facilitating the exceptionally rapid spinup of the cyclone and the low surface pressure. A model simulation of the precipitation rate at the time of most rapid storm intensification is shown in the accompanying figure. Heavier precipitation rates in the crescent shaped region are associated with deep convection along the leading edge of a dry intrusion behind the surface low. The majority of precipitation in the stratiform region to the northeast involved the production of ice with deposition from vapor to ice being the dominant process of growth. Some small amount of mixed phase cloudiness was present. Model condensate distributions matched well with SSM/I observations. The accompanying SSM/I imagery which delineates areas of large (greater than several hundred micron effective radius) precipitating ice over the ocean suggests that the model has done well in capturing the essential mechanisms responsible for the horizontal distribution of precipitation.

Robertson, Franklin R.↗

TRMM-Based Merged Precipitation Analyses

This paper describes results of using Tropical Rainfall Measuring Mission (TRMM) information as the key calibration tool in a merged analysis on a 1X1 latitude/longitude monthly scale based on multiple satellite sources and raingauge analyses. The TRMM-based product is compared with surface-based validation data sets and the community-based 20-year Global Precipitation Climatology Project (GPCP)monthly analyses. The TRMM-based merged analysis uses the TRMM information to calibrate the estimates from SSM/I and geosynchronous IR observations and merges those estimates together with the TRMM and gauge information to produce accurate rainfall estimates with the increased sampling provided by the combined satellite information. This TRMM merged analysis uses the combined instrument (Precipitation Radar [PR] and TRMM Microwave Imager [TMI]) retrieval of Haddad as the TRMM estimate with which to calibrate the other satellite estimates. This TRMM Combined instrument (TCI) estimate is shown to produce very similar absolute values to the other main TRMM products. The TRMM and other satellites merged analysis compares favorably to the atoll data set of Morrissey for the months of 1998 with a very small positive bias of 2%. However, comparison with the preliminary results from the TRMM ground validation radar information at Kwajalein atoll in the western Pacific Ocean shows a 26% positive bias. Therefore, absolute magnitudes from TRMM and/or the ground validation need to be treated with care at this point. A month by month comparison of the TRMM merged analysis and the GPCP analysis indicates very similar patterns, but with subtle differences in magnitude. Focusing on the Pacific Ocean ITCZ one can see the TRMM-based estimates having higher peak values and lower values in the ITCZ periphery. These attributes also show up in the statistics, where GPCP>TRMM at low values (below 10 mm/d) and TRMM>GPCP at high values (greater than 15 mm/d). Integrated over the 37N-37S belt for all of 1998 the TRMM value is 3.1 mm/day compared to 2.9 mm/day for GPCP, with the results when confined to ocean being 3.3 and 3.0, respectively. Therefore, TRMM has approximately 10% higher tropical oceanic precipitation than GPCP. Examples of TRMM monthly fields in analysis of geographic and temporal variations will also be discussed. Results for 1998 indicate that TRMM has a different ratio of western Pacific to eastern Pacific rainfall than GPCP, perhaps indicating that TRMM's ability to discern the vertical structure of the rain may lead to better estimates in the eastern Pacific. In addition the rainfall anomalies associated with the '98-'99 ENSO event are shown to be larger with the TRMM results as compared to the GPCP analyses.

Adler, Robert↗

Space-Time Characteristics of Rainfall Diurnal Variations

The space-time features of rainfall diurnal variation of precipitation are systematically investigated by using the Tropical Rainfall Measuring Mission (TRMM) precipitation products retrieved from TRMM microwave imager (TMI), precipitation radar (PR) and TMI/PR combined algorithms. Results demonstrate that diurnal variability of precipitation is obvious over tropical regions. The dominant feature of rainfall diurnal cycle over, ocean is that there is consistent rainfall peak in early morning, while there is a consistent rainfall peak in mid-late afternoon over land. The seasonal variation on intensity of rainfall diurnal cycle is clearly evidenced. Horizontal distributions of rainfall diurnal variations indicate that there is a clearly early-morning peak with a secondary peak in the middle-late afternoon in ocean rainfall at latitudes dominated by large-scale convergence and deep convection. There is also an analogous early-morning peak in land rainfall along with a stronger afternoon peak forced by surface heating. Amplitude analysis shows that the patterns and its evolution of rainfall diurnal cycle are very close to rainfall distribution pattern and its evolution. These results indicate that rainfall diurnal variations are strongly associated with large-scale convective systems and climate weather systems. Phase studies clearly present the regional and seasonal features of rainfall diurnal activities. Further studies on convective and stratiform rainfall show different characteristics of diurnal cycles. Their spatial and temporal variations of convective and stratiform rainfall indicate that mechanisms for rainfall diurnal variations vary with time and space.

Yang, Song↗

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Bell, Thomas L.↗

Convective Formation of Pileus Cloud Near the Tropopause

Pileus clouds form where humid, stably stratified air is mechanically displaced vertically ahead of rising convection. This paper describes convective formation of pileus cloud in the tropopause transition layer (TTL), and explores a possible link to the formation of long-lasting cirrus at cold temperatures. In-situ measurements from off the coast of Honduras during the July 2002 CRYSTALFACE experiment show an example of TTL cirrus associated with, and penetrated by, deep convection. The cirrus was enriched with total water compared to its surroundings, but composed of extremely small ice crystals with effective radii between 2 and 4 m. Through gravity wave analysis, and intercomparison of measured and simulated cloud microphysics, it is argued that the TTL cirrus in this case originated neither from convectively-forced gravity wave motions nor environmental mixing alone. Rather, it is hypothesized that some combination was involved in which, first, convection forced pileus cloud to form from TTL air; second, it punctured the pileus layer, contributing larger ice crystals through interfacial mixing; third, the addition of condensate inhibited evaporation of the original pileus ice crystals in the warm phase of the ensuing gravity wave; fourth, through successive pulses, deep convection formed the observed layer of TTL cirrus. While the general incidence and longevity of pileus cloud remains unknown, in-situ measurements, and satellite-based Microwave Limb Sounder retrievals, suggest that much of the tropical TTL is sufficiently humid to be susceptible to its formation. Where these clouds form and persist, there is potential for an irreversible repartition from water vapor to ice at cold temperatures.

Garrett, Timothy J.↗

Retrieval of atmospheric temperature profiles by a scanning microwave spectrometer

The Nimbus-6 satellite carries a scanning microwave spectrometer (SCAMS) experiment. The five frequency bands observed are near 22.2, 31.6, 52.8, 53.8, and 55.4 GHz. The calibration system permitted preflight calibration to an accuracy of about 1 K. In orbit, small empirical corrections were made to the calibration constants to obtain agreement in the mean of SCAMS measurements with computations based on conventional data analyzed by the National Meteorological Center (NMC). Global maps of temperature profiles were retrieved from the SCAMS measurements by a statistical method. Using the NMC analysis as the verification, RMS errors in level temperatures range of about 2-4 K, depending on altitude. Errors for layers of octave extent in pressure are uniformly about 2 K. Theoretical computations show that additional spectrometer channels would improve temperature sensing performance

Rosenkranz, P. W.↗

2-D Lunar Microwave Radiance Observations From the NOAA-20 ATMS

Reported here are disk-integrated Moon surface microwave brightness temperature (Tb) retrievals covering the frequency range of 23–183 GHz. FullMoon observations obtained from the advanced technology microwave sounder (ATMS) onboard the NOAA-20 satellite during a special spacecraft pitch–maneuver operation forms the basis of the retrievals. Instrument nonlinearity, Earth sidelobe contamination, cosmic background radiation, and reflector thermal emission corrections are applied to the observations to obtain accurate values of the Moon’s Tb at all frequencies. The measured full Moon Tb ranges from ~240 to 293 K with frequency increases from 23 to 183 GHz. A clear frequency trend is detected when the brightness temperature increases.

Hu Yang↗

Validation of UARS Microwave Limb Sounder Ozone Measurements

This paper describes the validation of ozone data from the Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS). The MLS ozone retrievals are obtained from the calibrated microwave radiances (emission spectra) in two separate bands, at frequencies near 205 and 183 GHz. Analyses described here focus on the MLS Version 3 data (the first set of files made publicly available). We describe results of simulations performed to assess the quality of the retrieval algorithms, in terms of both mixing ratio and radiance closure. From actual MLS observations, the 205-GHz ozone retrievals give better closure (smaller radiance residuals) than that from the 183-GHz measurements and should be considered more accurate from the calibration aspects. However, the 183-GHz data are less noise limited in the mesosphere and can provide the most useful scientific results in that region. We compare the retrieved 205-GHz ozone profiles in the middle-to lower stratosphere to ozonesonde measurements at a wide range of latitudes and seasons. Ground-based lidar data from Table Mountain, California, provide a good reference for comparisons at higher altitudes. Based on these analyses, comparisons with balloon-borne measurements and others, as well as a detailed budget of estimated uncertainties, MLS results appear to be generally of high quality, with some biases worth mentioning. Results for the lowermost stratosphere (approx. 50 to 100 bPa) are still in need of improvement. A set of estimated precision and accuracy values is derived for the MLS ozone data sets. We also comment on recent updates in the retrieval algorithms and their impact on ozone values.

Froidevaux, L.↗

NASA team algorithm for sea ice concentration retrieval from Defense Meteorological Satellite Program special sensor microwave imager - Comparison with Landsat satellite imagery

The present study describes the validation of the the NASA team algorithm for the determination of sea ice concentrations from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave ice concentration algorithm for a range of ice concentrations and ice types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat ice concentrations are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young ice, the NASA team algorithm was found to underestimate ice concentrations by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat ice concentrations decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.

Steffen, Konrad↗

Microwave Signatures of Snow on Sea Ice: Modeling

Accurate knowledge of snow-depth distribution over sea ice is critical for polar climate studies. Current snow-depth-over-sea-ice retrieval algorithms do not sufficiently account for variations in snow and ice physical properties that can affect the accuracy of retrievals. For this reason, airborne microwave observations were coordinated with ground-based measurements of snow depth and snow properties in the vicinity of Barrow, AK, in March 2003. In this paper, the effects of snowpack properties and ice conditions on microwave signatures are examined using detailed surface-based measurements and airborne observations in conjunction with a thermal microwave-emission model. A comparison of the Microwave Emission Model of Layered Snowpacks (MEMLS) simulations with detailed snowpack and ice data from stakes along the Elson Lagoon and the Beaufort Sea and ra- 'diometer data taken from low-level flights using a Polarimetric Scanning Radiometer (PSR-A) shows that MEMLS can be used to simulate snow on sea ice and is a useful tool for understanding the limitations of the snow-depth algorithm. Analysis of radiance data taken over the Elson Lagoon and the Beaufort Sea using MEMLS suggests that the radiometric differences between the two locations are due to the differences in sea-ice emissivity. Furthermore, measured brightness temperatures suggest that the current snow-depth retrieval algorithm is sufficient for areas of smooth first-year sea ice, whereas new algorithm coefficients are needed for rough first-year sea ice. Snowpack grain size and density remain an unresolved issue for snow-depth retrievals using passive-microwave radiances.

Powell, D. C.↗

Assessment of the Impact of Spatial Heterogeneity on Microwave Satellite Soil Moisture Periodic Error

An accurate temporal and spatial characterization of errors is required for the efficient processing, evaluation, and assimilation of remotely-sensed surface soil moisture retrievals. However, empirical evidence exists that passive microwave soil moisture retrievals are prone to periodic artifacts which may complicate their application in data assimilation systems (which commonly treat observational errors as being temporally white). In this paper, the link between such temporally-periodic errors and spatial land surface heterogeneity is examined. Both the synthetic experiment and site-specified cases reveal that, when combined with strong spatial heterogeneity, temporal periodicity in satellite sampling patterns (associated with exact repeat intervals of the polar-orbiting satellites) can lead to spurious high frequency spectral peaks in soil moisture retrievals. In addition, the global distribution of the most prominent and consistent 8-day spectral peak in the Advanced Microwave Scanning Radiometer - Earth Observing System soil moisture retrievals is revealed via a peak detection method. Three spatial heterogeneity indicators - based on microwave brightness temperature, land cover types, and long-term averaged vegetation index - are proposed to characterize the degree to which the variability of land surface is capable of inducing periodic error into satellite-based soil moisture retrievals. Regions demonstrating 8-day periodic errors are generally consistent with those exhibiting relatively higher heterogeneity indicators. This implies a causal relationship between spatial land surface heterogeneity and temporal periodic error in remotely-sensed surface soil moisture retrievals.

Fangni Lei↗

Estimating Alpine Snow Depth by Combining Multi-Frequency Passive Radiance Observations with Ensemble Snowpack Modeling

This paper presents a physically-based snow depth retrieval algorithm adapted for deep mountainous snowpack and airborne multifrequency (10.7, 18.7, 37.0 and 89.0 GHz) passive microwave (PM) radiance observations from a single flight. The algorithm employs a single forecast-analysis cycle of a traditional sequential assimilation scheme. It uses an ensemble of multi-layer snowpack model runs to resolve snow microstructure and melt-refreeze crusts, andmicrowave radiative transfer models to relate snow properties to microwave measurements.Snow depth was retrieved at a 120 m spatial resolution over three 1 km2 Intensive Study Area (ISA) within the Rabbit Ears Meso-Cell Study Area (MSA) from the NASA Cold Land Processes Experiment (CLPX) in Colorado (United States) for one date in February 2003. When evaluated against in situ observations, root mean square error (RMSE) of the snow depth from the assimilation was 13.3 cm for areas with low (<5 %) forest cover, which was a reduction of 48 % in the RMSE compared with the modeled snow depth when the PM observations were not assimilated; indicating a ~5% relative error of the posterior snow depth with respect to the average snow depth (200 cm) measured at these pixels. For pixels with forest cover ranging from 5-15% and 15-30%, results were improved (R2 increased from 0.65 to 0.71 and from 0 to 0.38, respectively) by introducing a forest radiative transfer model during the assimilation.

Airborne Multifrequency↗

Validation of UARS MLS Ozone Measurements

This paper describes the validation of ozone data from the Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS). The MLS ozone retrievals are obtained from the calibrated microwave radiances (emission spectra) in two separate bands, at frequencies near 205 and 183 GHz.

Microwave Limb Sounder (MLS)↗

Evaluation of the potential of one to three SEASAT-SMMR channels in retrieving sea surface temperature

The scanning multichannel microwave radiometer (SMMR) aboard the SEASAT satellite measured emitted radiation in both horizontal and vertical polarizations at microwave frequencies of 6.6, 10.69, 18.0, 21.0 and 37.0 GHz. Retrieval algorithms, for sea surface temperature (SST) determination, from subsets of one to three SMMR channels are obtained by a two step statistical technique. The technique first selects the best subsets of a given size defined by an R2 criterion (coefficient of determination), of a given size by the application of an efficient 'leaps and bounds' technique on a statistical data base. It then performs a regression analysis on the selected subsets. The statistical data base employed a large (600) set of seasonally and geographically diverse atmospheric and surface parameters for radiative transfer calculations. The results of the study of one to three channel subset retrieval algorithms indicate the possibility of using 6.6V, 6.6H and 18V channels for SST determination from SEASAT-SMMR data.

Pandey, P. C.↗

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Sun-Mack, Sunny↗

Changes in the TRMM Version 7 Space/Time Averaged Level 3 Data Products Based on GPROF TMI Swath-Based Precipitation Retrievals

TRMM has three level 3 (space/time averaged) data products that aggregate level 2 TRMM Microwave Imager (TMI) GPROF precipitation retrievals. These three products are TRMM 3A12, which is a monthly accumulation of 2A12 the GPROF swath retrieval product; TRMM 3B31, which is a monthly accumulation of 2A12 and 2B31 the combined retrieval product that uses both Precipitation Radar (PR) and TMI data; and 3G68 and its variants, which provide hourly retrievals for TMI, PR and combined. The 3G68 products are packaged as daily files but provide hourly information at 0.5 deg x 0.5 deg resolution globally, 0.25 deg x 0.25 deg globally, or 0.1 deg x 0.1 deg over Africa, Australia and South America. This paper will present early information of the changes in the v7 TMI GPROF level 2 retrievals that have an impact on the level 3 accumulations. This paper provides an analysis of the effect the 2A12 GPROF changes have on 3G68 products. In addition, it provides a comparison between the TRMM level 3 products that use the TMI GPROF swath retrievals.

Stocker, Erich↗