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NASA NTRS1999

Impact of a Merged Precipitation Data on Global Soil Moisture Variability

Accurate soil moisture information has proved to be important to climate simulations and climate and weather forecasts. However, many difficulties exist that limit our understanding of soil moisture distribution and variability. One of them is the lack of accurate precipitation with appropriate spatial and temporal resolution. Precipitation as an input forcing to the land surface greatly influences soil moisture characteristics and variability. To improve precipitation data quality, an algorithm has been developed to generate a spatially and temporally continuous 3-hourly global precipitation data for the period of 1987 to present. This precipitation product is a combination of the precipitation from Special Sensor Microwave Imager (SSMI) with the Goddard Earth Observing System-1 Data Assimilation System (GEOS-1 DAS) employing a Physical-space Statistical Analysis System (PSAS). In this study we investigate the impact of this merged/analyzed precipitation data on the global soil moisture variability using an Off-line Land-surface GEOS Assimilation (OLGA) system. Two OLGA integrations starting from 1987 to 1993 are performed forced with the analyzed and GEOS-1 DAS precipitation respectively. We examine the spatial and temporal characteristics of soil moisture variability in response to the analyzed precipitation. The influence of this merged precipitation on the soil moisture variability and regional hydrological budget is estimated throughout the comparison with the results forced with the GEOS-1 DAS precipitation only. In the OLGA the sut@-grid scale horizontal heterogeneity is explicitly represented on the tile space. This provides a means to assess the role of the surface moisture heterogeneity in the interaction with the surface atmosphere and surface hydrological budget, and to validate OLGA results at tile space with in situ observation. ABRACOS (Anglo-Brazilian Amazonian Climate Observation Study), FIFE (First ISLSCP Field Experiment) I and HAPEX data will be used in the validation.

Yang, Runhua↗
NASA NTRS1996

Responses of the Tropical Pacific to Wind Forcing as Observed by Spaceborne Sensors and Simulated by an Ocean General Circulation Model

In this study, satellite observations, in situ measurements, and model simulations are combined to assess the oceanic response to surface wind forcing in the equatorial Pacific. The surface wind fields derived from observations by the spaceborne special sensor microwave imager (SSM/I) and from the operational products of the European Centre for Medium-Range Weather Forecasts (ECMWF) are compared. When SSM/I winds are used to force a primitive-equation ocean general circulation model (OGCM), they produce 3 C more surface cooling than ECMWF winds for the eastern equatorial Pacific during the cool phase of an El Nino-Southern Oscillation event. The stronger cooling by SSM/I winds is in good agreement with measurements at the moored buoys and observations by the advanced very high resolution radiometer, indicating that SSM/I winds are superior to ECMWF winds in forcing the tropical ocean. In comparison with measurements from buoys, tide gauges, and the Geosat altimeter, the OGCM simulates the temporal variations of temperature, steric, and sea level changes with reasonable realism when forced with the satellite winds. There are discrepancies between model simulations and observations that are common to both wind forcing fields, one of which is the simulation of zonal currents; they could be attributed to model deficiencies. By examining model simulations under two winds, vertical heat advection and uplifting of the thermocline are found to be the dominant factors in the anomalous cooling of the ocean mixed layer.

Liu, W. Timothy↗
NASA NTRS1999

Consistency Between Tropical Divergent Circulations from Reanalysis Data Sets and Satellite-Derived Precipitation, Radiation, and Surface Fluxes

Large-scale divergent circulations are part of the atmospheric dynamic response to diabatic heating from condensation, radiative processes, and surface heat fluxes. Vertical motion and the associated divergent wind is thus intimately tied to the hydrologic cycle and the global heat balance. Vertical motions are recovered diagnostically from reanalyses and, as such, are subject to shortcommings in model physics, numerics, and data availability. We use several Global Energy and Water Cycle Experiment (GEWEX) Earth Observation System (EOS) data sets derived from satellite data to assess interannual divergent flow anomalies in the National Centers for Environmental Prediction (NCEP), Goddard Space Flight Center (GSFC), and GSFC Data Assimilation Office (DAO) analyses. Among the data sets are monthly, 2.5 degree gridded precipitation (Microwave Sounding Unit (MSU) and Special Sensor Microwave Imager (SSM/I-based)), Top or the atmosphere (TOA) radiative fluxes from ERBS, surface radiative fluxes from the SRB project, and surface latent and sensible flux estimates from SSM/I. These data sets can be considered as independent of the reanalysis fields. We focus largely on the period 1987-1989 encompassing a strong El Nino / la Nina couplet. Consequently we emphasize interannual changes as well as climatological aspects of the reanalyses. In the processes of this study we use simple integral constraints enforced through the satellite-derived data sets to derive corrections to the divergent circulation produced from the reanalyses. We examine the implications of these corrections in describing how perturbations to the tropical heat balance evolve during a warm / cool couplet. In particular the perturbations to the planetary scale water vapor transport, and the resulting changes in TOA and surface radiative fluxes are considered.

Robertson, Franklin R.↗
NASA NTRS1999

The Impact of TRMM on Mesoscale Model Simulation of Super Typhoon Paka

Tropical cyclone Paka formed during the first week of December 1997 and underwent three periods of rapid intensification over the following two weeks. During one of these periods, which initiated early on December 10, Paka's Dvorak-measured windspeed increased from 23 to 60 m/s over a 48-hr period. On December 18, during the last rapid deepening episode, Paka became a supertyphoon with a maximum wind speed of about 80 m/s. In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (135, 45 and 15 km horizontal resolution) will be used to simulate supertyphoon Paka. We performed two runs initialized with Goddard Earth Observing System (GEOS) data sets. The first GEOS data set does not incorporate either TRMM (tropical rainfall measuring mission satellite) or SSM/I (sensor microwave imager) observed rainfall fields into the GEOS's assimilation system while the second one does. Preliminary results show that the MM5 simulated surface pressure deepened by more than 25 mb (45 km resolution domain) in the run initialized with the GEOS data set incorporating TRMM and SSM/I derived rainfall, compared to the one initialized without. However, the track and precipitation patterns are quite similar between the runs. In our presentation, we will show the impact of TRMM rainfall upon the MM5 simulation of Paka at various horizontal resolutions. We will also examine the physical processes associated with initial explosive development by comparing MM5 simulated rainfall and latent heat release. In addition, budget (vorticity, PV, momentum and heat) calculations and sensitivity tests will be performed to examine the upper-tropospheric and SST mechanisms responsible for the explosive development of Paka.

Tao, W.-K.↗
NASA NTRS1999

A TRMM Rainfall Estimation Method Applicable to Land Areas

Methods developed to estimate rain rate on a footprint scale over land with the satellite-borne multispectral dual-polarization Special Sensor Microwave Imager (SSM/1) radiometer have met with limited success. Variability of surface emissivity on land and beam filling are commonly cited as the weaknesses of these methods. On the contrary, we contend a more significant reason for this lack of success is that the information content of spectral and polarization measurements of the SSM/I is limited. because of significant redundancy. As a result, the complex nature and vertical distribution C, of frozen and melting ice particles of different densities, sizes, and shapes cannot resolved satisfactorily. Extinction in the microwave region due to these complex particles can mask the extinction due to rain drops. Because of these reasons, theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. To illustrate the weakness of these models, as an example we can consider the brightness temperature measurement made by the radiometer in the 85 GHz channel (T85). Models indicate that T85 should be inversely related to the rain rate, because of scattering. However, rain rate derived from 15-minute rain gauges on land indicate that this is not true in a majority of footprints. This is also supported by the ship-borne radar observations of rain in the Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) region over the ocean. Based on these observations. we infer that theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. We do not follow the above path of rain retrieval on a footprint scale. Instead, we depend on the limited ability of the microwave radiometer to detect the presence of rain. This capability is useful to determine the rain area in a mesoscale region. We find in a given rain event that this rain area is closely related to the mesoscale-average rain rate. Based on this observation, in this study we have developed a method to estimate the mesoscale-average rain rate over land utilizing microwave radiometer data. Because of the high degree of geographic and seasonal variability in the nature and intensity of rain, this method requires some tuning with 15-minute rain gauge data on land. After tuning the method, it can be applied to an independent set of rain events that are close in time and space. We find that the mesoscale rain rates retrieved over the period of a month on land with this method shows a correlation of about 0.85 with respect to the surface rain-gauge observations. This mesoscale-average rain rate estimation method can be useful to extend the spatial and temporal coverage of the rainfall data provided by the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM) satellite.

Prabhakara, C.↗
NASA NTRS1999

The Estimation Surface Latent Heat Flux Over the Ocean and its Relationship to Marine Atmospheric Boundary Layer (MABL) Structure

A new technique combining active and passive remote sensing instruments for the estimation of surface latent heat flux over the ocean is presented. This synergistic method utilizes aerosol lidar backscatter data, multi-channel infrared radiometer data and microwave scatterometer data acquired onboard the NASA P-3B research aircraft during an extended field campaign over the Atlantic ocean in support of the Lidar In-space Technology Experiment (LITE) in September of 1994. The 10 meter wind speed derived from the scatterometers and the lidar-radiometer inferred near-surface moisture are used to obtain an estimate of the surface flux of moisture via bulk aerodynamic formulae. The results are compared with the Special Sensor Microwave Imager (SSM/I) daily average latent heat flux and show reasonable agreement. However, the SSM/I values are biased high by about 30 W/sq m. In addition, the MABL height, entrainment zone thickness and integrated lidar backscatter intensity are computed from the lidar data and compared with the magnitude of the surface fluxes. The results show that the surface latent heat flux is most strongly correlated with entrainment zone top, bottom and the integrated MABL lidar backscatter, with corresponding correlation coefficients of 0.62, 0.67 and 0.61, respectively.

Palm, Stephen P.↗
NASA NTRS1999

TRMM Data Assimilation at NASA

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. Work has been underway at NASA's Data Assimilation Office to explore the use of Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave Imager (SSM/I)-derived rainfall and total precipitable water (TPW) data in global data assimilation to directly constrain these hydrological parameters. We found that assimilating these data types improves not only the precipitation and moisture estimates but also key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation in the tropics. We will present results showing that assimilating TRMM and SSM/I 6-hour averaged rain rates and TPW estimates significantly reduces the state-dependent systematic errors in assimilated products. Specifically, rainfall assimilation improves cloud and latent heating distributions, which, in turn, improves the cloudy-sky radiation and the large-scale circulation, while TPW assimilation reduces moisture biases to improve radiation in clear-sky regions. Rainfall and TPW assimilation also improves tropical forecasts beyond I day.

Hou, Arthur Y.↗
NASA NTRS1999

A Combined Infrared and Microwave Technique for Studying the Diurnal Variation of Rainfall over Amazonia

Over 10 years of continuous data from the Special Sensor microwave Imager (SSM/I) aboard a series of Defense Department satellites has made it possible to construct regional rainfall climatologies at high spatial resolution. Using the Goddard Profiling Algorithm (GPROF), monthly estimates of precipitation were made over the region of northern Brazil, including the Amazon Basin, for 1987 to 1998. GPROF is a physical approach to passive microwave precipitation retrieval, which uses the Goddard Cumulus Ensemble (cloud) model to establish prior probability densities of precipitation structures. Precipitation fields from GPROF were stratified into morning and evening satellite overpasses, and accumulated at monthly intervals at 0.5 degree spatial resolution. Important diurnal effects were noted in the analysis, the most pronounced being a land/sea breeze circulation along the northern coast of Brazil and a mountain/valley circulation along the Andes. There were also indications of morning rainfall maxima along the major rivers, and evening maxima between the rivers. The addition of simultaneous geosynchronous infrared (IR) data leads to the current technique, which takes advantage of the 30 minute sampling and 4 km spatial resolution of the infrared channel and the better physics of the microwave retrieval. The resultant IR method is subsequently used to derive the diurnal variability of rainfall over the Amazon basin, and further, to investigate the relative contribution from its convective and stratiform components.

Negri, Andrew J.↗
NASA NTRS1999

Current and Future Plans of the NASA Data Assimilation Office (DAO)

The mission of the Data Assimilation Office (DAO) is to advance the state of the art of data assimilation and produce research-quality assimilated data sets which make optimal use of space-based observations. Development efforts over the last few years have focused on delivering a production data assimilation system in support of NASA's Terra platform. That system, called the Goddard Earth Observing System - version 2 or GEOS-2, represents a major upgrade to the baseline GEOS-1 system employed in NASA's first reanalysis effort. GEOS-2 includes a physical-space three dimensional variational analysis algorithm (the Physical-space Statistical Analysis System or PSAS) and numerous improvements to the general circulation model. The latter include a Soil-Vegetation-Atmosphere Transfer (SVAT) land surface scheme, a level 2.5 moist turbulence scheme and new Short Wave (SW) and Long Wave (LW) radiation code. The system also includes an off-line ozone assimilation system, and the capability to assimilate scatterometer surface winds, and TIROS Operational Vertical Sounder (TOVS) and Special Sensor Microwave Imager (SSM/I) moisture data. GEOS-2 is currently run at 1 degree horizontal resolution and 48 levels extending to O.Olmb. Experimental versions of GEOS-2 are run with a global stretched grid allowing enhanced (e.g. 1/4 deg) regional resolution. Other capabilities being developed include, the assimilation of Tropical Rainfall Measuring Mission (TRMM) precipitation and Global Positioning System (GPS) data, an off-line land surface assimilation system, and a retrospective analysis scheme. The DAO is also engaged in a number of collaborative efforts to help accelerate the development of the next generation data assimilation system. These include, a joint modeling effort between the DAO and NCAR/CGDD to develop a new Global Circulation Model (GCM), and a Department of Energy Lawrence Livermore National Laboratory (DOE/LLNL) collaboration on model parallelization. Plans for the next reanalysis will be discussed in the context of current and near term system quality and computing capabilities, and the need for multiple reanalysis products.

Atlas, Robert↗
NASA NTRS1999

New NOAA-15 Advanced Microwave Sounding Unit (AMSU) Datasets for Stratospheric Research

The NOAA-15 spacecraft launched in May 1998 carried the first Advanced Microwave Sounding Unit (AMSU). The AMSU has eleven oxygen absorption channels with weighting functions peaking from near the surface to 2 mb. Twice-daily, limb-corrected I degree gridded datasets of layer temperatures have been constructed since the AMSU went operational in early August 1998. Examples of AMSU imagery will be shown, as will preliminary analyses of daily fluctuations in tropical stratospheric temperatures and their relationship to daily variations in tropical-average rainfall measured by the Special Sensor Microwave Imager (SSM/I). The AMSU datasets are now available for other researchers to utilize.

Spencer, Roy W.↗
NASA NTRS1998

Surface-Wind Anomalies in North-Atlantic and North Pacific from SSM/I Observations: Influence on Temperature of Adjoining Land Regions

Surface winds over the oceans are derived from Special Sensor Microwave Imager (SSM/I) measurements, assigning direction by Variational Analysis Method (VAM). Validations by comparison with other measurements indicate highly-satisfactory data quality. Providing global coverage from 1988, the dataset is a convenient source for surface-wind climatology. In this study, the interannual variability of zonal winds is analyzed concentrating on the westerlies in North Atlantic and North Pacific, above 30 N. Interannual differences in the westerlies exceeding 10 m sec (exp -1) are observed over large regions, often accompanied by changes of the same magnitude in the easterlies below 30 N. We concentrate on February/March, since elevated temperatures, by advancing snow-melt, can produce early spring. The extremely strong westerlies in 1997 observed in these months over North Atlantic (and also North Pacific) apparently contributed to large surface-temperature anomalies in western Europe, on the order of +3 C above the climatic monthly average for England and France. At these latitudes strong positive anomalies extended in a ring around the globe. We formulated an Index of South westerlies for the North Atlantic, which can serve as an indicator for day-by-day advection effects into Europe. In comparing 1997 and 1998 with the previous years, we establish significant correlations with the temperature anomalies (one to five days later, depending on the region, and on the season). This variability of the ocean-surface winds and of the temperature anomalies on land may be related to the El Nino/La Nina oscillations. Such large temperature fluctuations over large areas, whatever the cause, can be regarded as noise in attempts to assess long-term trends in global temperature.

Otterman, Joseph↗
NASA NTRS1999

Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems Using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

Latent heating profiles associated with three (TOGA COARE) Tropical Ocean and Global Atmosphere Coupled Ocean Atmosphere Response Experiment active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the Goddard Cumulus Ensemble (GCE) Model and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm . The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/1), Radar and the GCE model. Diagnostically determined latent heating profiles calculated using 6 hourly soundings are used for validation. The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that both estimated by the GCE model and SSM/I in all three different COARE IFA periods. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50% for December 19-27, 42% for December 11-17 and 56% for the February 9-13 case. These results are consistent with large-scale analyses. The accurate estimates of stratiform amount is needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20%) than the radar for all three convective episodes. SSM/I derived stratiform amount is about 37% for December 19-27, 48% for December 11-17 and 41% for the February 9-13 case. Temporal variability of CSH algorithm retrieved latent heating profiles using either GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good 4r, rainfall retrieval from SSM/I for a convective event always leads to a good latent heating retrieval. Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, are not in bad agreement with those derived by soundings for the December 10-17 convective period. The heating retrievals may be more accurate for longer time scales provided there is no bias in the sampling.

Tao, Wei-Kuo↗
NASA NTRS2000

The Impact of Sea-Surface Winds on Meteorological Conditions in Israel: An Initial Study

The SSM/I (Spectral Sensor Microwave Imager) dataset is used to monitor surface wind speed and direction at four locations over the Eastern Mediterranean during December 1998 - January 1999. Time series of these data are compared to concurrent series of precipitation, surface temperature, humidity and winds at selected Israeli stations: Sde Dov (coastal), Bet Dagan (5 km. inland), Jerusalem (Judean Hills), Hafetz Haim (3 km. inland) and Sde Boker (central Negev). December 1998 and the beginning of January 1999 were dry in Israel, but significant precipitation was recorded at many stations during the second half of January (1999). SSM/I data show a surge in westerly surface winds west of Israel (32 N, 32.5 E) on 15 January, coinciding with the renewal of precipitation. We discuss the relevant circulation and pressure patterns during this transition in the context of the evolving meteorological conditions at the selected Israeli locations. The SSM/I dataset of near ocean surface winds, available for the last 12 years, is described. We analyze lagged correlation between these data and the Israeli station data and investigate possibility of predictive skill. Application of such relationships to short-term weather prediction would require real-time access to the SSM/I observations.

Otterman, J.↗
NASA NTRS2000

Active and Passive Microwave Determination of the Circulation and Characteristics of Weddell and Ross Sea Ice

A combination of satellite microwave data sets are used in conjunction with ECMWF (Medium Range Weather Forecasts) and NCEP (National Center for Environment Prediction) meteorological analysis fields to investigate seasonal variability in the circulation and sea-ice dynamics of the Weddell and Ross Seas. Results of sea-ice tracking using SSM/I (Special Sensor Microwave Imager), Scatterometer and SAR images are combined with in-situ data derived from Argos buoys and GPS drifters to validate observed drift patterns. Seasonal 3-month climatologies of ice motion and drift speed variance illustrate the response of the sea-ice system to seasonal forcing. A melt-detection algorithm is used to track the onset of seasonal melt, and to determine the extent and duration of atmospherically-led surface melting during austral summer. Results show that wind-driven drift regulates the seasonal distribution and characteristics of sea-ice and the intensity of the cyclonic Gyre circulation in these two regions.

Drinkwater, Mark R.↗
NASA NTRS2000

SSMI Wind Speed Climatology of the Time of Monsoon Wind Offset in the Western Arabian Sea

Forecasting the time of onset of monsoon wind in the western Arabian Sea, which is believed to precede the onset of rainfall along the west coast of India, is an important unsolved problem. Prior to measurements of the surface wind field by satellite, there was an absence of suitable surface wind observations. NASA scatterometer (NSCAT) surface wind vectors revealed that the time of the 1997 onset of 12 m/s southwest monsoon wind speeds in the western Arabian Sea preceded the onset of monsoon rainfall in Goa, India, by 3 - 4 days. Wind speed and direction data were necessary to establish a dynamical mechanism between times of onset of 12 m/s wind speed off Somalia and rainfall in Goa. Except for NSCAT, no satellite scatterometer wind product recorded adequately sampled 2-day 1deg x 1deg averaged wind vectors, which are the required space and time scales, to examine the wind-rain relationship in other years. However, the greater-than-95% steadiness of summer monsoon winds allows an opportunity to use satellite measurements of surface wind speed. The Special Sensor Microwave Imager (SSMI) recorded surface wind speed with adequate sampling to produce a 1-day, 1deg x 1deg data product during 1988 - 1998. SSMI data had been uniformly processed throughout the period. Times of onset of 12 m/s wind speed off Somalia determined with the SSMI data set were 21 May 1988, 24 May 1989, 17 May 1990, 28 May 1991, 8 June 1992, 28 May 1993, 30 May 1994, 7 June 1995, 29 May 1996, 12 June 1997, and 15 May 1998. Uncertainty of the 1992 and 1996 times of onset were increased because of the absence of SSMI data on 6 and 7 June 1992 and on 30 May 1996. Correlations of timing of monsoon wind onset with El Nino will be described. Variability of the time difference between times of onset of 12 m/s wind speed and Goa rainfall will be discussed. At the time of submission of the abstract, the Goa rainfall data have not arrived from the India Meteorological Department.

Halpern, David↗
NASA NTRS1999

Detecting 1mm/Year Signals in Altimetric Global Sea Level: Effect of Atmospheric Water Vapor and Precipitation

Several research efforts exist to use Topography Experiment (TOPEX)/ Projet d'Observatorie de Surveillance et d'Etudes Integrees de la Dynamique des Oceans (Poseidon) (T/P) to detect changes in global sea level possibly associated with climate change. This requires much better than 1 mm/yr accuracy, something that none of the instruments in T/P [or the European Remote Sensing (ERS-2) satellite, or the U.S. Navy's Geosat Follow-On (GFO) satellite] were designed for. This work focuses on the ability of the T/P microwave radiometer (TMR) to retrieve the path delay due to atmospheric water vapor along the altimeter's path with accuracy in the time changes below 1 mm/yr on global average. In collaboration with Stephen Keihm of JPL and Christopher Ruf of Pennsylvania State University, we compared TMR path delay (PD) estimates with atmospheric precipitable water (PW) from the Special Sensor Microwave Imager (SSMI) aboard the Defense Meteorological Satellite Program (DMSP) series of satellites for 1992-1998 to selected radiosondes, and we also looked at the brightness temperatures measured by TMR in the lowest 1% of the histogram. The conclusion is that TMR had a slow instrumental drift, associated with the 18-GHz channel, which causes an approximate underestimation of water vapor at a rate equivalent to 1.2 mm/yr in path delay between 1992 and 1996; this effect stopped and no drift is detected in 1997. The same study concluded that there is no detectable scale error (one which is proportional to measured vapor) in TMR. In related work, carried out with graduate student Damien Cailliau, we investigated the relative abilities of TMR, SSMI and the UP dual-frequency radar altimeter to detect rain, relative to a climatology of shipborne observations. Rain is a crucial but poorly measured variable in studies of the climate system, and a dedicated mission, Tropical Rainfall Measuring Mission (TRMM), was recently launched to measure it. However, the climatologies built over the past 10 years used passive radiometers, such as SSMI, or infrared observation from National Oceanic and Atmospheric Administration (NOAA) geostationary satellites. We concluded that the dual-frequency altimeter does an excellent job at retrieving rain on scales much smaller than the passive radiometer, and a better job at retrieving total precipitation (rain as well as snow) at high latitudes. This work improves the sea level observations by allowing better flagging of observations contaminated by rain, and more importantly, provides an alternative way to measure rainfall over the oceans.

Zlotnicki, Victor↗
NASA NTRS2000

Monthly Oceanic Rainfall Derived from Space-Borne Microwave Data

A technique for estimating monthly oceanic rainfall rate using multi-channel microwave measurements has been developed. This technique is applied to the Special Sensor Microwave Imager (SSM/I) data since 1987 to infer monthly rainfall for the Global Precipitation Climatology Project (GPCP). A modified version of this algorithm is now being applied to the TRMM Microwave Imager (TMI) data. There are three prominent features of this algorithm. First, the knowledge of the form of the rainfall intensity probability density function used to augment the measurements. Second, utilizing a linear combination of the 19.35 and 22.235 GHz channels to deemphasize the effect of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35 and 22.23 5 GHz brightness temperature histograms, TMI data with better spatial resolution and 24 hour sampling (vs. sun-synchronized sampling, which is limited to two narrow intervals of local solar time for DMSP satellites) prompt us to study the similarity and difference between these two rainfall estimates. One year of rainfall data (January to December 1998) are used in this study. The mean differences of these two rain estimates are typically less than 15%. Statistical tests are administrated to evaluate the differences between rainfall estimates from SSM/I and TMI data. Differences between TMI and SSM/I rain estimates are discussed in the context of radiative transfer calculations and rainfall estimate algorithm.

Chang, Alfred T. C.↗
NASA NTRS2000

The Estimation of Surface Latent Heat Flux Over the Ocean and its Relationship to Marine Atmospheric Boundary Layer (MABL) Structure

A new technique combining active and passive remote sensing instruments for the estimation of surface latent heat flux over the ocean is presented. This synergistic method uses aerosol lidar backscatter data, multi-channel infrared radiometer data and microwave scatterometer data acquired onboard the NASA P-3B research aircraft during an extended field campaign over the Atlantic ocean in support of the Lidar In-space Technology Experiment (LITE) in September of 1994. The 10 meter wind speed derived from the scatterometers and the lidar-radiometer inferred near-surface moisture are used to obtain an estimate of the surface flux of moisture via bulk aerodynamic formulae. The results are compared with the Special Sensor Microwave Imager (SSM/I) daily average latent heat flux and show reasonable agreement with an rms error and bias of about 50 and 25 W per square meters, respectively. In addition, the MABL height, entrainment zone thickness and integrated lidar backscatter intensity are computed from the lidar data and compared with the magnitude of the surface fluxes. The results show that the surface latent heat flux is most strongly correlated with entrainment zone top, bottom and the integrated MABL lidar backscatter, with corresponding correlation coefficients of 0.62, 0.67 and 0.61, respectively.

Palm, Stephen P.↗