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AndréA. Doneaud
,
Amos Makarau
, and
L. Ronald Johnson

Abstract

Digital radar data from the North Dakota Cloud Modification Project (NDCMP)—the 1981 and 1982 summer experiments—are used to further investigate the relationship between convective rain volumes and area-time-integrals (ATI). The ATI technique provides a means of estimating total rain volumes using area covered by rain events (for reflectivities ≥ 25 dBz) integrated over the cluster duration (Doneaud et al., 1984a).

The purpose of this investigation is twofold: (a) to estimate ATIs only for the growth portion of a convective storm (while the rain volume is computed using the entire life history of the convective event); and (b) to nowcast the total rain volume of a convective system at the stage of its maximum development. For the aforementioned purpose, the ATIs were computed using the maximum echo area ≥ 25 dBz (ATIA), the maximum reflectivity (ATIR), and the maximum echo height (ATIH) as the end of the growth portion of the convective event.

A simple linear regression analysis demonstrated that correlations between total rain volume (TVR) or the maximum rain volume (MYR) versus ATIA were the strongest. In a log-log plot, the correlation coefficient and the standard error of estimates of total rain volume versus ATIA were 0.98 and 0.23 for the summer 1982 data, and 0.96 and 0.24 for the summer 1981 data, respectively. In percentage terms, the corresponding range of variation of the rain volume for a given ATIA lies between 70% and − 41% (1982 data) and between 74% and − 44% (1981 data). That is comparable to the uncertainties which typically occur in rain volume estimates obtained from radar data employing Z-R conversion followed by space and time integration. This demonstrates that the total rain volume of a storm can be nowcasted at its maximum stage of development (max ATIA).

The scatter in the rain volume and in the maximum volumetric rain rate estimates are somewhat smaller if a multiple linear regression instead of a simple linear regression is considered, but the improvement is of little significance. The tests with independent data confirmed the consistency of the results for the region considered.

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AndréA. Doneaud
,
James R. Miller Jr.
,
David L. Priegnitz
, and
Lakshmana Viswanath

Abstract

Two mesoscale case studies in the semi-arid climate of southeastern Montana were carried out on 1 May and 3 June 1980. I May was an unstable, rainy day with two rain periods over the mesonet area, and 3 June was a potentially unstable day, with a cold frontal passage in the afternoon producing a very intense convective event.

Data from an instrumented mesoscale network (supporting the HIPLEX Montana experiment located between Miles City and Baker), a 5 cm radar, soundings, satellite (GOES), and synoptic maps were considered. The mesonet wind, temperature and moisture data were processed, computed every 15 min, and compared with radar rain patterns.

The study confirmed that convergence cell development within the surface kinematic fields precedes radar echoes and is directly related to the convective event. The areas involved in the vertical motions generating storms are much larger compared to those reported in humid climates. The “areal convergence” is a better storm predictor than the maximum convergence point value. A cloud merging effect related to the storm intensity and reduced rain efficiencies were also found.

The structure of the divergence field over the whole network experienced a cyclic evolution in both cases. This cyclic evolution is identified as a potential predictor for rain beginning 25–70 min after the last cycle before the rain phase.

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AndréA. Doneaud
,
Stefano Ionescu-Niscov
, and
James R. Miller Jr.

Abstract

Rain rates and their evolution during summertime convective storms were analyzed for the semiarid climate of the northern High Plains. Radar data from a total of 750 radar echo clusters from the 1980 and 1981 summer cloud seeding operations of the North Dakota Cloud Modification project (NDCMP) were used. The analysis suggests that the average rain rate R¯ among storm is, in a first approximation, independent of the total rain volume if the entire storm duration is considered in the averaging process. This average rain rate depends primarily on the reflectivity threshold considered in calculating the area coverage integrated over the lifetime of the storm, the storm, the area-time integral (ATI). For the 25 dBz reflectivity threshold used in the ATI computations, R¯ was 4.0 mm h−1 with a standard deviation of 1.55 mm h−1, being ∼20% higher for wet mason conditions.

The evolution of rain rates during storms was analyzed by dividing each storm lifetime into 10 min. 1, 2 and 4 h, and growing and decaying periods. A 10 min time increment was used in computing the parameters for all time intervals. A storm cluster reached its maximum growth after an average of 56% of its lifetime. The average rain rate for the growing period exceeded that for the decaying period by about 10%. As the time interval used in computations approached the storm lifetime, the scatter of the average rain rates was reduced, thus increasing the accuracy of rainfall estimates using the area time integral. The value of R¯ remained independent of the total rain volume when the growing or decaying periods of storms were considered separately. The total rain volume was also well correlated with the maximum single-scan rain volume. These findings suggest the possibility of estimating total storm rain volume at its maximum stage of development.

It is hoped that improvements in rainfall estimation over area using satellite data may result from further studies since the precipitating part of a cloud picture can be more accurately defined for the growing period of a cloud's history.

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AndréA. Doneaud
,
Stefano Ionescu-Niscov
,
David L. Priegnitz
, and
Paul L. Smith

Abstract

Digital radar data are used to investigate further a simple technique for estimating rainfall amounts on the basis of area coverage information. The basis of the technique is the existence of a strong correlation between a measure of the rain area coverage and duration called the Area-Time Integral (ATI) and the rain volume. This strong correlation is again demonstrated using echo cluster data from the North Dakota Cloud Modification Project 5 cm radars.

Integration on a scan-by-scan basis proved to be superior for determining ATI values to the hour-by-hour integration used previously. A 25 dB(z) reflectivity threshold was found suitable for the ATI calculation. The correlation coefficient on log-log plots of cluster rain volume versus ATI is approximately 0.98, indicating a power-law relationship between the variables. The exponent of that relationship is just a little higher than one, which indicates that the cluster average rainfall rate is almost independent of the storm size and duration.

A test of the relationship derived from one set of data (1980) against an independent set (1981) showed it to be consistent. Using the 1980 relationship to estimate the 1981 cluster rain volume for a given ATI, the uncertainty of the rain volume estimates was found to be −31%, +46%.

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AndréA. Doneaud
,
James R. Miller Jr.
,
L. Ronald Johnson
,
Thomas H. Vonder Haar
, and
Patrick Laybe

Abstract

Early work attempting to apply GOES rapid scan satellite data to a recently developed simple radar technique used to estimate convective rain volumes over areas in a semiarid environment (the northern Great Plains) is described.

Called the Area-Time-Integral (ATI) technique, it provides a means of estimating total rain volumes over fixed and floating target areas. The basis of the method is the existence of a strong correlation between the radar echo area coverage integrated over the lifetime of the storm and the radar estimated rain volume. The technique does not require the consideration of the structure of the radar intensities to generate rain volumes. but only the area covered by radar echoes. This fact might reduce the source of errors generated by the structure differences between the radar and the satellite signatures above given thresholds.

Satellite and radar data from the 1981 Cooperative Convective Precipitation Experiment (CCOPE) and the North Dakota Cloud Modification Project (NDCMP) are used. Consecutive time steps with both radar reflectivities and satellite (VIS and IR) rapid wan data were considered during the evolution of six convective clusters: three on 12 June, and three on 2 July 1981. Radar echoes with reflectivity values ≥ 25 dBZ were used to define the area of rainfall and the respective digital unit thresholds within the satellite data delineating the rainy part of the cloud area. Correlation of the ATI versus IR digital count values was obtained for every time step and for the storm lifetime, respectively.

A comparison of the stepwise evolution of radar parameters such as echo areas maximum echo heights, maximum reflectivities and satellite parameters such as threshold count values and coldest cloud top temperature is presented graphically and reflects the multicell characteristics of the convective clusters. Also, a comparison of radar and satellite parameters for the cluster lifetime is made. Satellite parameters pertaining to the cluster lifetime were derived both dependently and independently of radar data.

The main purpose of this investigation is to compute convective rain volume of a convective cluster by application of the ATI technique based only on satellite data. As such, the key element is to determine the ATI from satellite data without consideration of radar data. This is possible if trends of satellite products generated independently are similar to those of satellite products based upon radar observations as done here.

A parallel with the two-step techniques generally used to estimate rain volume from satellite data is made. To delineate the rainy part of a cloud area, a regression analysis is used. The regression relate a satellite-independent product to a satellite-dependent product. For a given storm. the satellite-independent product is first computed; then the regression equation gives the ATI, Finally, the rain volume is obtained by using the ATI versus rain volume relationship.

By applying the ATI/rain volume relationship to satellite data, the errors generated by the complicated multiple area-volume transform relations am reduced, as similar errors were reduced when the technique was applied to radar data. In addition, a regression analysis gives more accurate estimates than a single threshold when used to delineate an area covered by rain events from an area covered by clouds. The advantages of the ATI technique are based on the fact that the technique operates on a storm lifetime integrated basis, while the previous techniques operate on a time-step basis. The new technique generates only total rain volume estimates (not rain rates). This indeed is a limitation.

The analyses of six convective clusters suggest that the extension of the ATI technique using satellite data holds promise.

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