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NASA NTRS1993

Interannual Sea Level Variations in the Tropical Indian Ocean from Geosat and Shallow Water Simulations

Sea level variations of the Indian Ocean north of 20 deg S are analyzed from Geosat satellite altimeter data over April 1985-September 1989. These variations are compared and interpreted with numerical simulations derived from a reduced gravity model forced by FSU observed winds over the same period. After decomposition into complex empirical orthogonal functions, the low-frequency anomalies are described by the first two modes for observations as well as for simulations. The sums of the two modes contain 34% and 40% of the observed and simulated variances, respectively. Averaged over the basin, the observed and simulated sea level changes are correlated by 0.92 over 1985-1988. The strongest change happens during the El Ninio 1986-1987: between winter 1986 and summer 1987 the basin-averaged sea level rises by approx. 1 cm. These low-frequency variations can partly be explained by changes in the Sverdrup circulation. The southern tropical Indian Ocean between 1O deg and 20 deg S is the domain where those changes are strongest: the averaged sea level rises by approx. 4.5 cm between winter 1986 and winter 1987. There, the signal propagates southwestward across the basin at a speed similar to free Rossby waves. Sensitivity of observed anomalies is examined over 1987-1988, with different orbit ephemeris, tropospheric corrections, and error reduction processes. The uncertainty of the basin-averaged sea level estimates is mostly due to the way the orbit error is reduced and reaches approx. 1 cm. Nonetheless, spatial correlation is good between the various observations and better than between observations and simulations. Sensitivity of simulated anomalies to the wind uncertainty, examined with Former Soviet Union (FSU) and European Center for Medium-Range Weather Forecasting (ECMWF) forcings over 1985-1988, shows that the variance of the simulations driven by ECMWF is 52% smaller, as FSU winds are stronger than ECMWF. Results show that the wind strength also affects the dynamic response of the ocean: anomalies propagate westward across the basin more than twice as fast with FSU than with ECMWF. It is found that the discrepancy is larger between ECMWF and FSU simulations than between observations and FSU simulations.

Perigaud, Claire↗

NASA NTRS2001

Monitoring of MLS Measurements for Ozone Data Assimilation

The ozone data assimilation system at the NASA Goddard Space Flight Center Data Assimilation Office (DAO) has operationally provided near real time global three dimensional analyzed ozone fields since December 1999. Presently, 4 system assimilates both total column ozone and profile measurements from the NOAA - 16 SBUV/2 instrument into an off-line transport model using a physical space statistical analysis scheme (PS AS). Recently, this system was modified to investigate a possible impact from including MLS profile observations. Over a period from December 13, 1991 to March 1, 1992 the system assimilated both NOAA 11 SBUV/2 profile measurements and TOMS total column measurements. Short term ozone forecasts were produced and compared to MLS observations. The resulting observed -minus -forecast (O-F) residuals were studied regionally (by both latitude bands and pressure levels) in order to explore the potential impact of MLS observations on the assimilation and sensitivity to the UARS yaw maneuver and other instrument and algorithm characteristics. In addition, MLS profiles were compared to nearest neighbor SBUV and analysis profiles. In the tropics, analyzed ozone values tend to be too high from 1-3 hPa and too low from 10-20 hPa. MLS measurements in these regions tend be lower and higher (respectively) than forecast ozone values. This indicates that assimilating MLS measurements may improve, analysis results in these areas. Further, nearest neighbor profile comparisons in the southern high latitudes indicate that laminar features present in the analysis but not present in SBUV measurements, are also present in MLS measurements. This, together with the availability of MLS measurements in polar night regions indicates that assimilating MLS measurements in polar night regions indicates that assimilating MLS measurements may improve analyzed ozone values in high latitudes.

Winslow, Nathan↗

NASA NTRS2022

Influence of Vegetation on Simulation of the Water Balance and Hydrological Response to El Niño–Southern Oscillation in Western Tropical South America

Land surface models (LSMs) rely on vegetation parameters for use in hydrological and energy balance analysis, monitoring, and forecasting. This study examines the influence that vegetation representation in the Noah-Multiparameterization (Noah-MP) LSM has on hydrological simulations across the diverse climate zones of western tropical South America (WTSA), with specific consideration of hydrological variability associated with El Niño–Southern Oscillation (ENSO). The influence of model representation of vegetation on simulated hydrology is evaluated through three simulation experiments that use 1) satellite-derived constant MODIS; 2) satellite-derived time-varying MODIS; and 3) the Noah-MP dynamic leaf model. We find substantial differences in vegetation fields between these simulations, with the Noah-MP dynamic leaf model diverging significantly from satellite-derived vegetation fields in many ecoregions. Impacts on simulated hydrology were, however, found to be modest across climate zones, except for select extreme events. Also, although impacts on hydrology under ENSO-induced variability were small, we find that the Noah-MP dynamic leaf model simulates a positive relationship between rainfall and vegetation in humid ecoregions of WTSA, where satellite observations may indicate the opposite. The relatively small sensitivity of simulated hydrology to vegetation scheme suggests that the performance of hydrological monitoring and forecasting in WTSA that uses Noah-MP is largely unaffected by the choice of vegetation scheme, such that using a simple climatological default is generally no worse than adopting more complicated options. The presence of some differences between the time-varying and constant MODIS simulations for hydrologic extremes, however, indicates that time-varying MODIS configuration might be more suitable for hydrological hazards applications.

South America↗

NASA NTRS2014

Evaluation of Mixed-Phase Microphysics Within Winter Storms Using Field Data and In Situ Observations

Snow prediction within models is sensitive to the snow densities, habits, and degree of riming within the BMPs. Improving these BMPs is a crucial step toward improving both weather forecasting and climate predictions. Several microphysical schemes in the Weather Research and Forecasting (WRF) model down to 1.33-km grid spacing are evaluated using aircraft, radar, and ground in situ data from the Global Precipitation Mission Cold-season Precipitation Experiment (GCPEx) experiment over southern Ontario, as well as a few years (12 winter storms) of surface measurements of riming, crystal habit, snow density, and radar measurements at Stony Brook, NY (SBNY on north shore of Long Island) during the 2009-2012 winter seasons. Surface microphysical measurements at SBNY were taken every 15 to 30 minutes using a stereo microscope and camera, and snow depth and snow density were also recorded. During these storms, a vertically-pointing Ku band radar was used to observe the vertical evolution of reflectivity and Doppler vertical velocities. The GCPex presentation will focus on verification using aircraft spirals through warm frontal snow band event on 18 February 2012. All the BMPs realistically simulated the structure of the band and the vertical distribution of snow/ice aloft, except the SBU-YLIN overpredicted slightly and Thompson (THOM) underpredicted somewhat. The Morrison (MORR) scheme produced the best slope size distribution for snow, while the Stony Brook (SBU) underpredicted and the THOM slightly overpredicted. Those schemes that have the slope intercept a function of temperature (SBU and WSM6) tended to perform better for that parameter than others, especially the fixed intercept in Goddard. Overall, the spread among BMPs was smaller than in other studies, likely because there was limited riming with the band. For the 15 cases at SBNY, which include moderate and heavy riming events, the non-spherical snow assumption (THOM and SBU-YLIN) simulated a more realistic distribution of reflectivity than spherical snow assumptions in the WSM6 and MORR schemes. The MORR, WSM6, and SBU schemes are comparable to the observed velocity distribution in light and moderate riming periods. The THOM is approx. 0.25 m/s too slow with its velocity distribution in these periods. In heavier riming, the vertical Doppler velocities in the WSM6, THOM, and MORR schemes were approx. 0.25 m/s too slow, while the SBU was 0.25 to 0.5 m/s too fast because of some excessive cloud water issues.

Colle, Brian A.↗

NASA NTRS2019

Impact of Assimilating AIRS Cloud-Cleared Radiances on Atmospheric Dynamics and Boundary Layer Height at High Latitudes

High latitude weather forecasts, on scales ranging from mesoscale to synoptic, present difficulties due, in part, to the sparsity of conventional observations. In addition, the prevalence of extended low-level stratus cloud cover limits the use of infrared data, which are operationally assimilated only in areas unaffected by clouds. Use of cloud-cleared AIRS (Atmospheric Infrared Sounder) radiances (AIRS CCR), allows the assimilation of infrared information in cloudy regions, permitting data ingestion in regions usually undersampled. This study explores the sensitivity of planetary boundary layer height and related atmospheric dynamics to the assimilation of these data in the Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast system during the boreal fall 2014 season using observing system experiments (OSEs). Examined here are comparisons between the current, operational approach of assimilating AIRS clear-sky radiances against the assimilation of CCR. Assimilation of hyperspectral infrared information from AIRS over the Arctic region slightly modifies the lower midtropospheric temperature structure, which in turn contributes to adjustments in geopotential height, affecting the baroclinic instability properties over the entire hemisphere and explaining the overall improvement in global forecast skill.

McGrath-Spangler, E. L.↗

NASA NTRS2004

Polar Processes in a 50-year Simulation of Stratospheric Chemistry and Transport

The unique chemical, dynamical, and microphysical processes that occur in the winter polar lower stratosphere are expected to interact strongly with changing climate and trace gas abundances. Significant changes in ozone have been observed and prediction of future ozone and climate interactions depends on modeling these processes successfully. We have conducted an off-line model simulation of the stratosphere for trace gas conditions representative of 1975-2025 using meteorology from the NASA finite-volume general circulation model. The objective of this simulation is to examine the sensitivity of stratospheric ozone and chemical change to varying meteorology and trace gas inputs. This presentation will examine the dependence of ozone and related processes in polar regions on the climatological and trace gas changes in the model. The model past performance is base-lined against available observations, and a future ozone recovery scenario is forecast. Overall the model ozone simulation is quite realistic, but initial analysis of the detailed evolution of some observable processes suggests systematic shortcomings in our description of the polar chemical rates and/or mechanisms. Model sensitivities, strengths, and weaknesses will be discussed with implications for uncertainty and confidence in coupled climate chemistry predictions.

Kawa, S.R.↗

NASA NTRS1974

Atmospheric response to variations in sea surface temperature

An extended range prediction experiment was performed with the GISS atmospheric model on a global data to test the sensitivity of the model to sea surface temperature (SST) variation over a two-week forecast period. The use of an initial observed SST field in place of the climatological monthly mean sea temperatures for surface flux calculations in the model was found to have a significant effect on the predicted precipitation over the ocean, with enhanced convection computed over areas where moderately large warm SST anomalies are found. However, there was no detectable positive effect of the SST anomaly field on forecast quality. The influence of the SST anomalies on the daily predicted fields of pressure and geopotential is relatively insignificant up to about one week compared with the growth of prediction error, and is no greater over a two-week period than that resulting from random errors in the initial meteorological state. The 14-day average fields of sea level pressure and 500-mb height predicted by the model, appear to be similarly insensitive to anomalies of sea surface temperature.

Spar, J.↗

NASA NTRS2012

Transforming Community Access to Space Science Models

Researching and forecasting the ever changing space environment (often referred to as space weather) and its influence on humans and their activities are model-intensive disciplines. This is true because the physical processes involved are complex, but, in contrast to terrestrial weather, the supporting observations are typically sparse. Models play a vital role in establishing a physically meaningful context for interpreting limited observations, testing theory, and producing both nowcasts and forecasts. For example, with accurate forecasting of hazardous space weather conditions, spacecraft operators can place sensitive systems in safe modes, and power utilities can protect critical network components from damage caused by large currents induced in transmission lines by geomagnetic storms.

MacNeice, Peter↗

NASA NTRS2008

Impact of Local Sensors

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and the CCAFS (XMR) daily rawinsonde observations (RAOB) to issue and verify wind advisories and warnings for operations. These observations are also used by the National Weather Service (NWS) Spaceflight Meteorology Group (SMG) in Houston, Texas and the NWS Melbourne, Florida (NWS MLB) to initialize their locally-run mesoscale models. In addition, SMG uses these observations to support shuttle landings at the Shuttle Landing Facility (SLF). Due to impending budget cuts, some or all of the KSC/CCAFS wind towers on the east-central Florida mainland and the XMR RAOBs may be eliminated. The locations of the mainland towers and XMR RAOB site are shown in Figure I. The loss of these data may impact the forecast capability of the 45 WS, SMG and NWS MLB. The AMU was tasked to conduct an objective independent modeling study to help determine how important these observations are to the accuracy of the model output used by the forecasters. To accomplish this, the Applied Meteorology Unit (AMU) performed a sensitivity study using the Weather Research and Forecasting (WRF) model initialized with and without KSC/CCAFS wind tower and XMR RAOB data.

Watson, Leela R.↗

NASA NTRSDate not supplied

Assimilation of Soil Moisture Observations Over Land Improves Analysis and Prediction of Tropical Cyclone Idai

Soil moisture conditions can impact the circulation and structure of a tropical cyclone (TC) when part or all of the circulation is over land. Dry land surface conditions may lead to faster dissipation of a TC over land, whereas very wet conditions may lead to a prolonged maintenance of its intensity. While this relationship is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tbs significantly improves modeled land surface states. Here we evaluate: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP Tb observations. We find that in the analysis with SMAP assimilation, the TC has a better-defined, more aligned vertical structure over land relative to the control run; moreover, the analyzed TC size, as measured by the wind speed radius, better matches the observed TC size. We further find significant reductions in the forecast intensity error and the forecast along-track error, measured against observations. The largest error reductions occur at lead times of 36 to 72 hours, suggesting that the land with its longer memory gains in importance as a source of predictability at this timescale. An investigation of the underlying mechanisms leading to the skill improvements from SMAP data assimilation revealed that the assimilation of SMAP leads to wetter soil moisture conditions and an increased latent heat flux in the SMAP analysis, which results in a TC with higher column-integrated total moisture content and total energy compared to the control analysis.

Jana Kolassa↗

NASA NTRS1994

Experiments with the Mesoscale Atmospheric Simulation System (MASS) using the synthetic relative humidity

This study is intended to examine the impact of the synthetic relative humidity on the model simulation of mesoscale convective storm environment. The synthetic relative humidity is derived from the National Weather Services surface observations, and non-conventional sources including aircraft, radar, and satellite observations. The latter sources provide the mesoscale data of very high spatial and temporal resolution. The synthetic humidity data is used to complement the National Weather Services rawinsonde observations. It is believed that a realistic representation of initial moisture field in a mesoscale model is critical for the model simulation of thunderstorm development, and the formation of non-convective clouds as well as their effects on the surface energy budget. The impact will be investigated based on a real-data case study using the mesoscale atmospheric simulation system developed by Mesoscale Environmental Simulations Operations, Inc. The mesoscale atmospheric simulation system consists of objective analysis and initialization codes, and the coarse-mesh and fine-mesh dynamic prediction models. Both models are a three dimensional, primitive equation model containing the essential moist physics for simulating and forecasting mesoscale convective processes in the atmosphere. The modeling system is currently implemented at the Applied Meteorology Unit, Kennedy Space Center. Two procedures involving the synthetic relative humidity to define the model initial moisture fields are considered. It is proposed to perform several short-range (approximately 6 hours) comparative coarse-mesh simulation experiments with and without the synthetic data. They are aimed at revealing the model sensitivities should allow us both to refine the specification of the observational requirements, and to develop more accurate and efficient objective analysis schemes. The goal is to advance the MASS (Mesoscal Atmospheric Simulation System) modeling expertise so that the model output can provide reliable guidance for thunderstorm forecasting.

Chang, Chia-Bo↗

NASA NTRS2013

Inclusion of Linearized Moist Physics in Nasa's Goddard Earth Observing System Data Assimilation Tools

Inclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa-Schubert (RAS) convection scheme has been developed and tested in NASA's Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encountered. Efficient filtering of these profiles is achieved by diagnosis of steep gradients in a reduced version of the operator of the tangent linear model. With filtering turned on, the inclusion of linearized moist physics increases the correlation between the nonlinear perturbation trajectory and the linear approximation of the perturbation trajectory. A month-long observation impact experiment is performed and the effect of including moist physics on the impacts is discussed. Impacts from moist-sensitive instruments and channels are increased. The effect of including moist physics is examined for adjoint sensitivity studies. A case study examining an intensifying Northern Hemisphere Atlantic storm is presented. The results show a significant sensitivity with respect to moisture.

Convection↗

NASA NTRS2016

The CubeSat Infrared Atmospheric Sounder (CIRAS), Pathfinder for the Earth Observing Nanosatellite-Infrared (EON-IR)

The CubeSat Infrared Atmospheric Sounder (CIRAS) will measure upwelling infrared radiation of the Earth in the MWIR region of the spectrum from space on a CubeSat. CIRAS will demonstrate two new infrared sounding technologies. The first is a 2D array of High Operating Temperature Barrier Infrared Detector (HOT-BIRD) material, selected for its high uniformity, low cost, low noise and higher operating temperatures than traditional materials. The detectors are hybridized to a commercial ROIC and commercial camera electronics. The second technology is an MWIR Grating Spectrometer (MGS) to be designed and developed by Ball Aerospace to provide imaging spectroscopy for atmospheric sounding in a CubeSat volume. The MGS has no moving parts and is based on heritage spectrometers including the Ball Aerospace Spaceborne Infrared Atmospheric Sounder for GEO (SIRAS-G) IIP of 2007. JPL will develop the mechanical, electronic and thermal subsystems for CIRAS. The spacecraft will be a commercially available CubeSat. The integrated system will be a complete 6U CubeSat capable of measuring temperature and water vapor profiles with good lower tropospheric sensitivity. The CIRAS is the first step towards the development of an Earth Observing Nanosatellite Infrared (EON-IR) for potential use in a future operational forecasting system.

Pagano, Thomas↗

NASA NTRS2018

WRF Hindcasts of Cold Front Passages over the ARM Eastern North Atlantic Site: A Sensitivity Study

The present study explores the ability of the Weather Research and Forecasting (WRF) Model to accurately reproduce the passage of extratropical cold fronts at the DOE-ARM Eastern North Atlantic (ENA) observation site on the Azores Islands. An analysis of three case studies is performed in which the impact of the WRF domain size, position of the model boundary relative to the ENA site, grid spacing, and spectral nudging conditions are explored. The results from these case studies indicate that model biases in the timing and duration of cold front passages change with the distance between the model domain boundary and the ENA site. For these three cases, if the western model boundary is further than 1500 km from the site, the front becomes too meridional and fails to reach the site, making 1000 km or 1500 km the optimal distances. In contrast, integrations with small distances (e.g., 500 km) between the site and domain boundaries have inadequate spatial spin-up, i.e. the domain is too small for the model to properly stabilize. For all 3 cases, regardless of domain size, the model has biases in its upper-level circulation that impact the position and timing of the front. However, this issue is most serious for 4000 km2 domains and larger. For these domains, prolonged spectral nudging can correct cold front biases. As such, this analysis provides a framework to optimize the WRF model configuration necessary for a realistic hindcast of a cold front passage at a fixed location centered in a domain as large as computationally possible.

Faycal Lamraoui↗

NASA NTRS1983

A case study of the sensitivity of forecast skill to data and data analysis techniques

A series of experiments have been conducted to examine the sensitivity of forecast skill to various data and data analysis techniques for the 0000 GMT case of January 21, 1979. These include the individual components of the FGGE observing system, the temperatures obtained with different satellite retrieval methods, and the method of vertical interpolation between the mandatory pressure analysis levels and the model sigma levels. It is found that NESS TIROS-N infrared retrievals seriously degrade a rawinsonde-only analysis over land, resulting in a poorer forecast over North America. Less degradation in the 72-hr forecast skill at sea level and some improvement at 500 mb is noted, relative to the control with TIROS-N retrievals produced with a physical inversion method which utilizes a 6-hr forecast first guess. NESS VTPR oceanic retrievals lead to an improved forecast over North America when added to the control.

Baker, W. E.↗

NASA NTRS2022

Impact of Meteorological Factors on the Mesoscale Morphology of Cloud Streets during a Cold-Air Outbreak over the Western North Atlantic

Postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario

Jingyi Chen↗

NASA NTRS2021

Weather Intelligent Navigation Data and Models for Aviation Planning (WINDMAP)

WINDMAP addresses the emerging needs in the aviation community of providing real-time weather forecasting to improve the safety of low altitude aircraft operations. This is accomplished through the integration of real-time observations from autonomous systems, such as drones and urban air taxis, with numerical weather prediction models and flight management and safety systems. To solve this problem, several technical challenges have been identified. These include (1) developing autonomous UAS capable of conducting observations accurately and reliably; (2) determining the number and frequency of required observations and the sensitivity of these observations in data sparse regions of the lower atmosphere;(3) assimilating dense observational data into models in real-time with sufficient resolution and accuracy; (4) developing novel physics-based reduced order models capable of incorporating diverse data sets; and (5)integrating real-time forecasting into UTM and DAA (detect-and-avoid) architectures for path planning and navigation. The goal of this proposed effort is to demonstrate the value of using small UAS to collect measurements of the dynamic and thermodynamic properties of the lower atmosphere at scales that match or exceed the spatio-temporal resolution of today’s best numerical weather prediction models

Koushik Datta↗

NASA NTRS2002

Impact of Mineral Aerosol on TOVS Temperature and Moisture Retrievals

Mineral aerosols can absorb significant radiation in the infrared spectrum. Consequently, there may be errors in TIROS Operational Vertical Sounder (TOVS) retrieved temperature and moisture profiles in regions of heavy dust loading. We first investigate the potential error in the temperature retrievals and secondly attempt to account for radiative effects of the dust in retrievals. Information on the dust concentrations and size distribution is from the Goddard Chemistry Aerosol Transport model (GOCART). Aerosol optical parameters are calculated from mie scattering theory assuming a composition of pure illite. We used the cloud-clearing DAO TOVS retrieval system of Joiner and Rokke (2000). It is incorporated into the Data Assimilation Office (DAO) Finite Volume Data Assimilation System (NDAS). The advantage of this approach is that the first guess temperature profile used in the TOVS retrieval are forecasted temperatures from the previous assimilated time period. The operational DAO fvDAS was run for 10 days during June 2001 during a period of dust outbreaks off the coast of Africa over the Atlantic. The observed minus the forecast (O-F) brightness temperature at each TOVS channel is a measure of the accuracy of the retrieval. Since there was no account of dust during this operational run, a dependence of O-F on the estimated atmospheric dust concentrations from GOCART indicates that the dust is contaminating the TOVS retrievals. Channels that measure the surface temperature, lower tropospheric temperature and moisture show this dependence. There are errors in the retrieved brightness temperature of a half a degree or more during heavy dust loading conditions. The forecasted brightness temperature is always greater than the observed value. The radiative transfer module used in the DAO TOVS retrieval system was modified to account for dust. We calculate the sensitivity of the brightness temperature of the TOVS channels to the dust concentrations in GOCART assuming pure illite. For most channels the observed relationship between O-F and dust concentrations in GOCART is consistent with these calculated sensitivities. The fvDAS run was repeated using the modified DAO TOVS retrieval system that accounts for dust. Preliminary results from this run show that there are significant effects on the retrieved surface temperature and tropospheric moisture.

Weaver, Clark↗