Elizabeth Smith

Design of an inversion-based precipitation proflie retrieval algorithm using an explicit cloud model for initial guess microphysics

SummaryThis paper describes the design and validation of the FSU precipitation profile retrieval algorithm for applications with SSM/I passive microwave measurements. The algorithm employs the principles of multifrequency inversion based on forward radiative transfer modeling. A Sobolev 2-stream solution to the radiative transfer equation (RTE) is used as the forward RTE model and is described herein. The method is shown to be very accurate, retaining the same degree of computational efficiency inherent to simpler 2-stream flux models. Tests of the model against more detailed multistream, adding-doubling models demonstrate that the Sobolev solution produces radiance accuracies of approximately 1%. An advantage of the Sobolev approach is that the intensity field can be expanded in a mathematically consistent fashion, an essential feature in applications with the off-nadir SSM/I microwave measurements. A 4-dimensional non-hydrostatic cloud model provides the microphysical underpinnings of the algorithm, and is used to generate the initial guess profiles for the inversion procedure. The various stages of the algorithm are described, as well as two different methods of computational implementation for storm-scale and global-scale applications. The paper also summarizes a number of different rainrate validation analyses that have been carried out at the two scales, as well as examining the capabilities of the algorithm in diagnosing the vertical latent heating structure. The validation results represent a mixture of quantitative comparisons to radar and raingage datasets, and more qualitative comparisons to the numerical modeling results of other investigators. Because of known uncertainties in the validation data in terms of their accuracy and representativeness, and the underlying problems with time-space matching of the comparisons, it is not yet possible to place absolute confidence limits on the retrievals. However, taken as a whole, the rainrate validation analyses and the estimated latent heating profiles present solid evidence that the profile approach is returning credible rainfall estimates whose uncertainnes are commensurate with those of current validation data.

Reducing discrepancies in atmospheric heat budget of Tibetan Plateau by satellite-based estimates of radiative cooling and cloud-radiation feedback

SummaryPast investigations of the summertime heat budget over the Tibetan Plateau have not included detailed estimates of radiative cooling (QR) nor have they carefully considered the effects of cloudiness on this term. The various attempts to eyaluate different combinations of heat and moisture budget torms and to understand the sources of energy to the summer armospheric heat source over the plateau are not in agreement, partly because of remaining discrepancies in the radiative and turbulent flux components, and partly because until recently, the conventional data sets needed for independently estimating the total heating and moistening terms have been incomplete. The uncertainties in the radiative term have also led to difficulties in assessing the uncertainties in the other budget terms, since no study to date has assembled a complete enough data set to allow a unified calculation of all budget quantities or to obtain budget closure. Recently published results of Yanai and his colleagues involving apparent heat source calculations for the plateau region based on a much improved FGGE data set, have motivated the examination of whether more detailed radiative calculations can help resolve past discrepancies in the budget terms on a monthly time scale. This study uses a continuous time series of 22-km resolution INSAT geosynchronous satellite measurements and ECMWF profile analyses in conjunction with medium spectral resolution radiative transfer models to estimate the slicrtwave and longwave components of the radiative cooling term and the role of cloudiness on these components for the 1988 summer period. The calculations reveal both meridional and zonal structure in radiative divergence across the plateau associated with the substantial gradients of cloudiness and aridity that dominate the summertime plateau climatology. The calculations also indicate that the magnitudes of both cloud-induced shortwave heating and longwave cooling over the plateau are much greater than over low-elevation regions. Moreover, since cloud-induced longwave cooling exceeds cloud-induced shortwave heating, the bulk effect of clouds is to radiatively cool the plateau atmosphere. The high resolution calculations are reduced to monthly averaged budget quantities for analyzing whether existing discrepancies in the plateau heat budget can be resolved. Although there is no means to rigorously verify the accuracies and representativeness of the individual budget terms, the new radiative estimates combined with the most reliable current estimates of total heating and turbulent fluxes, produce near closure (within 4%) of the plateau heat budget for the June to August period.

Using coincident SSM/I and infrared geostationary satellite data for rapid updates of rainfall

There exists a need for rapid updates of land and ocean-based precipitation within the atmospheric, oceanographic, and hydrologic communities. While presenting their own difficulties, satellite observations overcome many of the difficulties encountered in obtaining observations near coasts and over oceans. The current microwave-based Special Sensor Microwave Imagers (SSM/I) provide global coverage of rainfall from a polar-orbiting perspective. Conversely, operational geostationary imagers such as the Geostationary Operational Earth Satellites (GOES) provide rapid hourly (or less) updates in the infrared (IR) spectrum near 11 microns, which for optically thick clouds senses the emitted radiation from the upper cloud regions. This technique attempts to statistically fuse these two types of disjoint satellite data together in a real-time fashion for retrieval of instantaneous rain rate as well as accumulations at the geostationary update cycle. The technique works with any of the four current operational geostationary imagers (GOES-8, GOES-9, GMS 5 and Meteosat-6), and is easily adaptable to assimilate rain rates derived from the Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI).

Microwave multisensor rainfall retrieval applied to TOGA-COARE observations

Rainfall retrieval estimation algorithms, based on passive and active microwave sensor data, are applied to along-track nadir-looking observations of a cyclone over ocean that occurred on February 8, 1993 during TOGA-COARE. The estimated rainfall rates derived from the radiometer data are compared with those obtained from ARMAR radar. Results in terms of reflectivity profiles and upwelling brightness temperatures, reconstructed from the estimated cloud structures, are discussed.

Pilot study using SPOT satellite imagery over Apalachicola national forest to determine appropriate spatial scale for area-wide aggregation of surface fluxes

SummaryHigh resolution radiances from SPOT satellite imagery converted to Normalized Difference Vegetation Indices (NDVI) over a 16×16 km2 mixed ground cover study-area in the Apalachicola National Forest in northwest Florida, along with in situ measurements from a Bowen ratio surface flux monitoring system and physical modeling techniques, are used to determine the length manifold beyond which degraded resolution satellite imagery fails to capture flux variability over the scene. The investigation is relevant to an understanding of how bias error is generated in methods designed to produce scale-invariant surface flux estimates from satellite measurements. Error estimates are based on assigning characteristic NDVI values to the four predominant types of ground cover found within the study-area. An open site near the center of the study-area, which satisfies the conditions for surface flux monitoring, is used for obtaining input data for a biosphere-atmosphere exchange model designed to calculate representative fluxes for the different ground covers. Continuous 6-minute meteorological and surface flux measurements were made at the monitoring site for a period of 22 days. These measurements are used in conjunction with surface layer theory to provide surface layer profile estimates of wind speed, temperature, and relative humidity at the tops of the forested sites. The measured and derived meteorological parameters, together with representative biophysical parameters, are used as input to the biosphere-atmosphere exchange model. By representing sensible and latent heat flux distributions due to the variable ground cover with characteristic NDVI values at 20-m resolution, baseline area-wide sensible and latent heat flux quantities are calculated. Error-growth curves as a function of spatial resolution for the fluxes are found by degrading the resolution of the SPOT radiances used to calculate NDVI, and rationing the associated area-wide fluxes to the baseline values. The point at which an error-growth curve becomes invariant represents the edge of a length manifold beyond which the satellite input no longer contains information on surface flux variability, even though NDVI variability continues at all scales up to that of the complete SPOT scene. The error-growth curves are non-linear, with all the error build-up taking place between 20 m and 1.6 km. Decreasing the spatial resolution of the NDVI information down to or below 1.6 km, introduces bias errors in the area-wide surface flux estimates of 10% for sensible heat and 8% for latent heat. The underlying assumptions and modeling produce uncertainty in estimating the manifold limits, however, the principal objective is to show that in using satellite data for scale-invariant surface flux retrieval, there is an optimal spatial resolution factor that can be objectively quantified.

Measurements and applications of combined radar-passive microwave rainfall profiling during TOGA-COARE

The NASA Tropical Rainfall Measuring Mission (TRMM) represents the first opportunity to incorporate both multifrequency passive microwave and active radar measurements in a satellite precipitation retrieval algorithm. The TRMM microwave imager (TMI) includes many of the same passive channels as the Special Sensor Microwave Imager (SSMI), with the addition of a 10.7 GHz channel and a 14 GHz incoherent precipitation radar (PR). During the 1992-1993 TOGA-COARE experiment in the western Pacific Ocean, coordinated radar and microwave radiometer data were gathered data over a multitude of precipitating storm regions including the forming and mature stages of a tropical cyclone. Although the TRMM radiometer and radar fields of view will differ, the radar data provide clues to the underlying cloud vertical structure that can be used to mitigate ambiguities in profile-based retrieval algorithms that rely upon the passive T/sub B/ alone.

Measurements and implications for combined radar-passive microwave rainfall profiling techniques

An upcoming NASA satellite platform, the Tropical Rainfall Measuring Mission (TRMM), represents the first opportunity to incorporate both multifrequency passive microwave and active radar measurements in its retrieval algorithms. The TRMM microwave imager (TMI) includes many of the same passive channels as the current Special Sensor Microwave Imager (SSMI), with the addition of a 10.7 GHz channel. The 14 GHz incoherent precipitation radar (PR) scans an across-track swath width about one-third the width of the forward-view conical TMI scan. Therefore, the radar data arrives about a minute after the TMI scan, and the PR and TMI beams view significantly different profiles in the atmosphere for a given on-Earth pixel location. During the 1992-1993 TOGA-COARE experiment in the western Pacific Ocean, a DC-8-based precipitation radar and an ER-a-based 4-channel microwave radiometer gathered data over a multitude of precipitating storm regions including the forming and mature stages of a tropical cyclone. Example imagery and vertical radar profiles are presented. These data are currently being used by the authors for vertical profiling algorithms which exploit the information contained in both the radar and radiometer. The radar data provide clues to the underlying cloud vertical structure that can be used to mitigate ambiguities in profile-based retrieval algorithms that rely upon the passive T/sub B/ alone.<<ETX>>