Abstract

Statistical structure functions are used to evaluate sounding data from the 6–7 March day of the 1982 AVE/VAS Ground Truth Field Experiment. Functional analyses are performed for five observation times starting at 1200 GMT 6 March and ending at 0000 GMT 7 March, and for the composite 12 h period. Data consist of mesoscale soundings from a special ground truth rawinsonde network and VAS-derived soundings from both a physical algorithm and a regression technique. The standard parameters of temperature, geopotential height, and mixing ratio are evaluated at the 850, 700, 500, 300 and 200 mb levels. Integrated parameters of thickness and precipitable water also are investigated.

Using structure function analyses, estimates of root-mean-square (rms) data uncertainty are obtained for the three data sources. Then, VAS soundings from the physical retrieval scheme are compared with those from the regression technique. Results indicate that both schemes have similar error characteristics and capabilities for determining gradients of mesoscale temperature and geopotential height. Signal-to-noise ratios for these parameters were quite favorable and greater than those of mixing ratio. Finally, sounding retrievals are evaluated against those from the ground-truth rawinsonde network. These results show that the VAS data generally describe weaker gradients than observed with the radiosondes. A notable exception is physically-derived mixing ratio at 850 mb.

Abstract

Satellite-derived temperature profiles are used to determine if reliable estimates of synoptic-scale vertical motion can be obtained from the adiabatic, vorticity, and omega equation techniques. The period of study contains a short-wave trough over the Midwest and a convective outbreak over the middle Mississippi River Valley. Satellite soundings are available at 1–3 h intervals at five times. The emphasis is on assessing the strengths and weaknesses of the three vertical motion procedures and determining the effects of short-interval observations on the calculations.

Results show that the quasi-geostrophic omega equation provided patterns and magnitudes most consistent with observed weather events and 12 h radiosonde-derived motions. The vorticity method produced less satisfactory results, while adiabatic motions were unacceptable. The time derivative term dominated adiabatic motions and was a major influence in the vorticity method. Unrealistic temperature tendencies resulted from the retrieval algorithm; i.e., a diurnal temperature bias extended upwards to 500 mb, and there was a compensating effect at higher levels.

Abstract

This paper evaluates and intercompares three existing algorithms for calculating precipitable water (PW) using infrared radiances from the GOES-7 VISSR (Visible and Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS). The study exclusively uses simulated, rather than observed, VAS radiances in all retrievals. The National Environmental Satellite, Data, and Information Service simultaneous physical algorithm utilizes data from all 12 VAS channels and produces a vertical profile of temperature and dewpoint from which PW can be calculated. The Chesters technique and Jedlovec’s physical split-window technique retrieve PW from radiances in the two split window channels without first computing a dewpoint profile. All three algorithms also can be used with GOES-8 and GOES-9 data.

These algorithms have not been intercompared previously. Each is applied on case days having wide variations in temperature and moisture. The algorithms are supplied with first-guess information of varying accuracy to assess their sensitivity to the guess data. The performance of the techniques relative to one another is described, including important similarities and differences among them.

Results show that all three algorithms perform well within most temperature and moisture regimes. Each retrieves PW that is generally an improvement upon the first guess and is more accurate than PW predicted by surface temperature alone. However, each algorithm is somewhat dependent upon the first guess. Warm-biased first-guess surface temperatures are generally associated with moist-biased PW retrievals, while cold-biased first-guess surface temperatures are generally associated with dry-biased retrievals. The first-guess surface temperature errors reflect the presence, in either the first-guess or observed temperature profiles, of low-level inversions that cause the PW retrieval errors. Retrievals made where the observed contribution of low-level moisture to total column PW is small are usually moist biased, while those where the low-level contribution is large are usually dry biased. Both of these relationships exist irrespective of the sign of the first-guess PW error.

Abstract

The Geostationary Operational Environmental Satellite (GOES-8) temperature–moisture retrievals were compared with collocated National Weather Service radiosonde observations (RAOBs) to assess retrieval performance. Retrieved values of temperature and dewpoint were evaluated at individual levels. Precipitable water and thickness also were evaluated, and the GOES-8 retrievals were compared with the first-guess data used in the algorithm. The dataset consisted of 1113 RAOB–retrieval pairs (collocated to within 50 km) over the United States at 1200 UTC during August–November 1995.

GOES-8 temperature retrievals were found to agree better with their RAOB-derived counterparts than did the dewpoints. However, both temperatures and dewpoints were found to be highly dependent on their first-guess data from the Nested Grid Model. Retrievals generally were closer to the RAOBs than was the first guess. However, this was never guaranteed, even for large first-guess discrepancies. In fact, some retrievals did not agree as well with the RAOBs as did the first guess.

GOES-8 and RAOB-derived precipitable water (PW) and thickness showed closer agreement than the level-specific data. Both integrated parameters were dependent on their first guess. However, GOES-8 and RAOB PW agreed more often in layers above the surface where the guess was less accurate.

Comparison with a previous evaluation of retrievals from the Visible and Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) indicated that GOES-8 retrievals agreed better with RAOBs than did the VAS versions. This improvement is likely due to GOES-8’s increased number of channels and better signal-to-noise values, along with the assumed increase in quality of the first-guess data being used.

Abstract

An aircraft prototype of the High-Resolution Interferometer Sounder (HIS) was flown over Tennesse and northern Alabama during summer 1986. HIS temperature and dewpoint soundings were examined on two flight days to determine their error characteristics and utility in mesoscale analyses. Random errors were calculated from structure functions while total errors were obtained by pairing the HIS soundings with radiosonde-derived profiles. Random temperature errors were found to be less than 1°C at most levels, but random dewpoint errors ranged from 1° to 5°C. Total errors of both parameters were considerably greater, with dewpoint errors especially large on the day having a pronounced subsidence inversion.

Cumulus cloud cover on 15 June limited HIS mesoscale analyses on that day. Previously undetected clouds were found in many HIS fields of view, and these probably produced the low-level horizontal temperature and dewpoint variations observed in the retrievals. HIS dewpoints at 300 mb indicated a strong moisture gradient that was confirmed by GOES 6.7-µm imagery.

HIS mesoscale analyses on 19 June revealed a tongue of humid air stretching across the study area. The moist region was confirmed by radiosonde data and imagery from the Multispectral Atmospheric Mapping Sensor (MAMS). Convective temperatures derived from HIS retrievals helped explain the cloud formation that occurred after the HIS overflights. Crude estimates of Bowen ratio were obtained from HIS data using a mixing-line approach. Values indicated that areas of large sensible heat flux were the areas of first cloud development. These locations were also suggested by GOES visible and infrared imagery. The HIS retrievals indicated that areas of thunderstorm formation were regions of greatest instability.

Local landscape variability and atmospheric temperature and humidity fluctuations were found to be important factors in producing the cumulus clouds on 19 June. HIS soundings were capable of detecting some of this variability. The authors were impressed by HIS's performance on the two study days.

Abstract

Statistical algorithms are developed to diagnose the vertical change in equivalent potential temperature (ΔΘ _e ) between 920 and 620 hPa from GOES-8 radiance data. The models are prepared using a training dataset of radiosonde releases from 10 United States cities. Simulated GOES-8 channel brightness temperatures are calculated from these soundings. The training data are stratified into several subsets (depending on time and location). Models trained only on 0000 or 1200 UTC data explain approximately 7% more of the variance in observed ΔΘ _e than those trained on both 0000 and 1200 UTC. Values of R ² from models using training data from only one are superior to those trained on multiple stations. Inclusion of the imager channels adds little information to the algorithms.

These models then are applied to data from the Limited Area Mesoscale Prediction System model to see which performs consistently better over diurnally varying conditions. Models trained only with 0000 UTC data give the best results, explaining between 63% and 81% of the variance in the independent data. The model that performed best is studied further. Biases are present when this model is applied to times other than 0000 UTC. These biases are caused by temperature differences between the 0000 UTC training data and those at the times being examined. Strong regional biases also occur when a model trained on only one location is applied to a large area. A second model is incorporated into the procedure to reduce this bias. The two-model algorithm explains more variance than the initial one-model version (93% vs 77%), and the area of strong regional bias is greatly reduced.

This statistical procedure for ΔΘ _e is then tested on observed GOES-8 data. A new statistical model is formed using the observed GOES-8 brightness temperatures and ΔΘ _e ’s calculated from collocated radiosonde observations. The new model yields an R ² of 67% when applied to an independent dataset. This value is smaller than those from the models using simulated data, most likely due to several additional sources of discrepancy. Finally, simulated GOES-7 Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) radiances are used to prepare a ΔΘ _e algorithm. The VAS model explains approximately 5% less variance than its GOES-8 counterpart, due to the reduced vertical resolution available on VAS.

These analyses show that regionally trained regression models can accurately diagnose convective instability while using relatively little computational time.

Abstract

Passive microwave brightness temperatures (T_B 's) at 92 and 183 GHz from an aircraft thunderstorm overflight are compared with values calculated from radar-derived hydrometer profiles and a modified proximity sounding. Two methods for modeling particles in the ice canopy are contrasted. The fist is a “traditional” approach employing Marshall–Palmer ice spheres. The second, or “alternative,” method partitions 20% of the ice water content into a Marshall–Palmer component for graupel and hail, and 80% into a modified gamma spherical particle size distribution function representing ice crystals.

Results from the alternative approach are superior to those from the traditional method in the anvil and mature convective core. In the decaying convective region, the traditional approach yields better agreement with observed magnitude. Neither method, however, matches the geometry of the observed T_B depression associated with the decaying convective core. This is likely due to the presence of graupel, which is not detected as a special signature in radar reflectivity, but does diminish T_B 's through scattering. Brightness temperatures at the relatively high microwave frequencies considered are shown to be very sensitive to the ice-particle size distribution.

Abstract

An algorithm is examined that uses Visible–Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) 11- and 12-µm (split-window) data to derive column-integrated water content (IWC) at mesoscale resolution. The algorithm is physically based and derives its first-guess information from radiosonde data. The procedure is applied first to a test case dataset and then to the 19 June 1986 study day from the Cooperative Huntsville Meteorological Experiment (COHMEX). Ground truth data for verifying results from the technique include IWC from National Weather Service and COHMEX radiosondes, the Multispectral Atmospheric Mapping Sensor (MAMS), and a special set of VAS soundings (12 channel) using an independent retrieval method. Results from the test case show reasonable accuracy with the root-mean-square errors as low as ±3.8 mm. On the 19 June case study day IWC analyses depict reasonable gradients and exhibit good spatial and temporal continuity. Furthermore, they provide insight into preferred regions for cumulus cloud and thunderstorm formation. On the average, a mean absolute retrieval error of 2.4 mm (an 8.1% error) and a root-mean-square error of ±2.9 mm are obtained on the case study day. These results compare favorably with those from existing VAS IWC techniques. Overall, the findings indicate that the technique has excellent potential to depict mesoscale moisture variations.

Abstract

Satellite-derived profiles of temperature and dewpoint (retrievals) are obtained using radiance data from the Visible-infrared Spin Scan Radiometer Atmospheric Sounder. Individual fields of view that are input to the retrieval algorithm must be horizontally averaged to provide suitable signal-to-noise ratios. This paper investigates three methods for performing this averaging: 1)a blocking approach that is employed operationally, 2) a manual procedure that seeks to maximize atmospheric gradients, and 3) an objective procedure called clustering that takes advantage of similarities in satellite measurements to avoid smearing the gradient information. The three techniques are examined on 10–11 July 1989 when intense gradients of humidity were present over the Florida peninsula.

Results show that the clustering scheme produced retrievals that were very similar to those obtained manually. Both schemes indicated strong humidity gradients in the lower troposphere. The blocking procedure produced less intense gradients. The retrieval information is used to examine conditions leading to fair weather on 10 July but intense thunderstorm development on 11 July.

Abstract

Radiative transfer simulations are performed to determine how water vapor and nonprecipitating cloud liquid water and ice particles within typical midlatitude atmospheres affect brightness temperatures T _B 's of moisture sounding channels used in the Advanced Microwave Sounding Unit (AMSU) and AMSU-like instruments. The purpose is to promote a general understanding of passive top-of-atmosphere T _B 's for window frequencies at 23.8, 89.0, and 157.0 GHz, and water vapor frequencies at 176.31, 180.3 1, and 182.31 GHz by documenting specific examples. This is accomplished through detailed analyses of T _B 's for idealized atmospheres, mostly representing temperate conditions over land. Cloud effects are considered in terms of five basic properties: droplet size distribution, phase, liquid or ice water content, altitude, and thickness. Effects on T _B of changing surface emissivity also are addressed. The brightness temperature contribution functions are presented as an aid to physically interpreting AMSU T _B 's.

Both liquid and ice clouds impact the T _B 's in a variety of ways. The T _B 's at 23.8 and 89 GHZ are more strongly affected by altostratus liquid clouds than by cirrus clouds for equivalent water paths. In contrast, channels near 157 and 183 GHz are more strongly affected by ice clouds. Higher clouds have a water impact on 157- and 183-GHz T _B 's than do lower clouds. Clouds depress T _B 's of the higher-frequency channels by suppressing, but not necessarily obscuring, radiance contributions from below. Thus, T _B 's are less closely associated with cloud-top temperatures than are IR radiometric temperatures. Water vapor alone accounts for up to 89% of the total attenuation by a midtropospheric liquid cloud for channels near 183 GHz. The Rayleigh approximation is found to be adequate for typical droplet size distributions; however, Mie scattering effects from liquid droplets become important for droplet size distribution functions with modal radii greater than 20 µm near 157 and 183 GHz, and greater than 30–40 µm at 89 GHz. This is due mainly to the relatively small concentrations of droplets much larger than the mode radius. Orographic clouds and tropical cumuli have been observed to contain droplet size distributions with mode radii in the 30–40-µm range. Thus, as new instruments bridge the gap between microwave and infrared to frequencies even higher than 183 GHz, radiative transfer modelers are cautioned to explicitly address scattering characteristics of such clouds.