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Arnold Gruber

Abstract

In order to assess the role played by convective processes in the vertical transfer of energy, the mean structure and energy budget over the Florida Peninsula have been studied, when the convective scale is the dominant scale of motion present.

The study utilized 0000 and 1200 GMT radiosonde data for the period 1957-65 and the convectively dominated period was identified as June, July and August. Energy budget computations show that the Florida Peninsula provides a considerable amount of latent and sensible energy across the air-surface interface. Convective processes make a significant contribution to the vertical transport of energy. The sea-breeze circulation is found to play an important role in the physical processes taking place. When the entire tropospheric volume is considered, it is found that there is a net expert of energy.

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Arnold Gruber

Abstract

An attempt to estimate rainfall in convectively active regions using Kuo's parameterization scheme has been made. The precipitation in this model is given by P = lQ 1t, where P is the precipitation per unit time, l the fraction of a synoptic area covered by deep active convection, Q 1 the mount of condensation heating according to moist adiabatic ascent, and Δt a time parameter related to the precipitating lifetime of the convective elements.

Investigation of the above equation when P, l and Q 1 were available indicated that an appropriate time parameter was 30 min and that the main contribution to the precipitation comes from the l parameter.

A case is presented where l is obtained from satellite observations. The resulting precipitation estimate appears quite reasonable. The potential for estimating precipitation over the tropical means is pointed out.

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Mamoudou B. Ba and Arnold Gruber

Abstract

A multispectral approach is used to optimize the identification of raining clouds located at a given altitude estimated from the cloud-top temperature. The approach combines information from five channels on the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellite (GOES): visible (0.65 μm), near infrared (3.9 μm), water vapor (6.7 μm), and window channels (11 and 12 μm). The screening of nonraining clouds includes the use of spatial gradient of cloud-top temperature for cirrus clouds (this screening is applied at all times) and the effective radius of cloud-top particles derived from the measurements at 3.9 μm during daytime. During nighttime, only clouds colder than 230 K are considered for the screening; during daytime, all clouds having a visible reflectance greater than 0.40 are considered for the screening, and a threshold of 15 μm in droplet effective radius is used as a low boundary of raining clouds. A GOES rain rate for each indicated raining cloud group referenced by its cloud-top temperature is obtained by the product of probability of rain (P b) and mean rain rate (RRmean) and is adjusted by a moisture factor that is designed to modulate the evaporation effects on rain below cloud base for different moisture environments. The calibration of the algorithm for constants P b and RRmean is obtained using collocated instantaneous satellite and radar data and hourly gauge-adjusted radar products collected during 17 days in June and July 1998. A comparison of the combined visible and a temperature threshold of 230 K (e.g., previous infrared/visible algorithms) with the combined visible and a threshold of 15 μm demonstrates that the latter improves the detection of rain from warm clouds without lowering the skill of the algorithm. The quantitative validation shows that the algorithm performs well at daily and monthly scales. At monthly scales, a comparison with GOES Precipitation Index (GPI) shows that GOES Multispectral Rainfall Algorithm's performance against gauges is much better for September and October 1999.

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Arnold Gruber and James J. O'Brien

Abstract

An objective technique for adjusting wind data, such that the total mass divergence in a volume of the atmosphere is zero, is developed. The adjustment is obtained by applying a least-squares smoothing with a Lagrangian multiplier to constrain the total mass divergence to a specified amount. The computational details are derived and the method is applied to several examples. Both for theoretical wind profiles and for actual data, a very satisfactory adjustment is achieved without destroying the physical information contained in the data.

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George Ohring, Arnold Gruber, and Robert Ellingson

Abstract

Nimbus-7 satellite observations are used to determine the relationship between the total longwave radiation flux and the radiance in the 10-12 μm infrared window. The total longwave fluxes are obtained from the earth radiation budget (ERB) narrow-field-of-view (NFOV) observations of total radiance; the IR window radiances are those measured by the Temperature Humidity Infrared Radiometer (THIR). Regression equations are obtained relating the total flux equivalent brightness temperatures to the radiance equivalent brightness temperature of the IR window. These empirical equations are compared to similar regression equations based on radiative transfer calculations for a large sample of atmospheric soundings. The latter theoretical equations are used by NOAA in the processing of IR window observations from operational polar orbiting satellites to obtain total longwave flux estimates. The observational results indicate that there is a very high correlation between the flux equivalent brightness temperature and the IR window radiance equivalent brightness temperature, and that the former can indeed be determined from measurements of the latter, thus validating the general NOAA approach. Tests on independent data suggest that rms flux errors of ∼11 w m−2 are to be expected for single applications of the empirical equations. The theoretical equations used by NOAA have an average positive bias of ∼13 wm−2 or a relative bias of ∼6% with respect to the ERB NFOV observations; the relative bias disappears at high flux values and increases with decreasing flux. A preliminary attempt to determine the cause of the discrepancy between the empirical and theoretical results indicates that a major factor may be the unrepresentativeness of the atmospheric soundings used in developing the theoretical regression coefficients.

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Jeffrey R. McCollum, Arnold Gruber, and Mamoudou B. Ba

Abstract

The Global Precipitation Climatology Project (GPCP) satellite estimates have approximately twice the magnitude of estimates produced from the rain gauges used by the GPCP in central equatorial Africa. Different possible explanations are identified and investigated. The first is that there may not be enough GPCP rain gauges in the area to provide accurate estimates of rainfall for comparisons with satellite estimates. A comparison of the time-averaged GPCP rain gauge estimate with a long-term (over 40 yr) climatology indicates that the GPCP gauge estimates are similar to long-term rainfall averages, suggesting that the GPCP rain gauge analysis is not underestimating rainfall. Two other possible explanations related to the physical properties of the air masses in this region are studied. Evidence from the literature and from estimates of the effective radii of cloud droplets suggests that there may be an abundance of aerosols in central Africa, resulting in an abundance of cloud condensation nuclei, small drops, and inefficient rain processes. The second explanation is that convective clouds forming under dry conditions generally have cloud bases considerably higher than those of clouds forming in moist environments. This leads to an increase in the evaporation rate of the falling rain, resulting in less precipitation reaching the ground. Analysis of the moisture distributions from both the National Centers for Environmental Prediction numerical weather prediction model reanalysis data and the National Aeronautics and Space Administration Water Vapor Project global moisture dataset reveals that the lower troposphere in this region of Africa is relatively dry, which suggests that cloud bases are high.

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