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Melinda S. Peng
and
Simon W. Chang

Abstract

Special Sensor Microwave/Imager (SSM/I) retrieved rainfall rates were assimilated into a limited-area numerical prediction model in an attempt to improve the initial analysis and forecast of a tropical cyclone. Typhoon Flo of 1990, which was observed in an intensive observation period of the Tropical Cyclone Motion Experiment-1990, was chosen for this study. The SSM/I retrieved rainfall rates within 888 km (8° latitude) of the storm center were incorporated into the initial fields by a reversed Kuo cumulus parameterization. In the procedure used here, the moisture field in the model is adjusted so that the model generates the SSM/I-observed rainfall rates. This scheme is applied through two different assimilation methods. The first method is based on a dynamic initialization in which the prediction model is integrated backward adiabatically to t = −6 h and then forward diabatically for 6 h to the initial time. During the diabatic forward integration, the SSM/I rainfall rates are incorporated using the reversed Kuo cumulus parameterization. The second method is a forward data assimilation integration starting from t = −12 h. From t = −6 h to t = 0, the SSM/I rainfall rates are incorporated, also using the reversed Kuo scheme. During this period, the momentum fields are relaxed to the initial (t = 0) analysis to reduce the initial position error generated during the preforecast integration. Five cases for which SSM/I overpasses were available were tested, including two cases before and three after Flo's recurvature. Forecasts at 48 h are compared with the actual storm track and intensifies estimated by the Joint Typhoon Warning Center. For the five cases tested, the assimilation of SSM/I retrieved rainfall rates reduced the average 48-h forecast distance error from 239 km in the control runs to 81 km in the assimilation experiments. It is postulated that the large positive impact was a consequence of the improved forecast intensity and speed of the typhoon when the SSM/I rain-rate data were assimilated.

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Donald C. Norquist
and
Sam S. Chang

Abstract

Accuracy of humidity forecasts has been considered relatively unimportant to much of the operational numerical weather prediction (NWP) community. However, the U.S. Air Force is interested in accurate water vapor and cloud forecasts as end products. It is expected that the NWP community as a whole will become more involved in improving their humidity forecasts as they recognize the important role of accurate water vapor distributions in data assimilation, forecasts of temperature and precipitation, and climate change research.

As a modeling community, we need to begin now to identify and rectify the systematic humidity forecast errors that are present in NWP models. This will allow us to take full advantage of the new types of remotely sensed water vapor and cloud measurements that are on the horizon. The research reported in this paper attempts to address this issue in a simple, straightforward manner, using the Phillips Laboratory Global Spectral Model (PL GSM).

It was found that significant systematic specific humidity errors exist in the much-used FGGE [First CARP (Global Atmospheric Research Program) Global Experimental] (initialized) analyses. However, when a correction on the analyses was imposed and the PL GSM forecasts rerun, forecast errors similar to the forecast errors generated from the uncorrected analyses were observed. The errors were diagnosed through an evaluation of the tendency terms in the model's specific humidity prognostic equation. The results showed that systematic low-level tropical drying and upper-level global moistening could be attributed to the convective terms and the horizontal and vertical advection terms, respectively. Alternative formulations of the model were identified in an attempt to reduce or eliminate these errors. In general, it was found that the alternative formulations that do not modify the convection parameterization of the model reduced the upper-level moistening, while those that do modify the convection scheme reduced low-level tropical drying but introduced low-level and midlevel moistening in the summer hemisphere extratropics. The authors conclude that the nonconvective modifications could be instituted in the model as is. However, more work is needed on improving the way that convective parameterizations distribute water vapor in the vertical.

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Alfred T. C. Chang
and
Long S. Chiu

Abstract

About 10 yr (July 1987–December 1997 with December 1987 missing) of oceanic monthly rainfall based on data taken by the Special Sensor Microwave/Imager (SSM/I) on board the Defense Meteorological Satellite Program satellites have been computed. The technique, based on the work of Wilheit et al., includes improved parameterization of the beam-filling correction, a refined land mask and sea ice filter. Monthly means are calculated for both 5° and 2.5° latitude–longitude boxes.

Monthly means over the latitude band of 50°N–50°S and error statistics are presented. The time-averaged rain rate is 3.09 mm day−1 (std dev of 0.15 mm day−1) with an error of 38.0% (std dev of 3.0%) for the 5° monthly means over the 10-yr period. These statistics compare favorably with 3.00 mm day−1 (std dev of 0.19 mm day−1) and 46.7% (std dev of 3.4%) computed from the 2.5° monthly means for the period January 1992–December 1994. Examination of the different rain rate categories shows no distinct discontinuity, except for months with a large number of missing SSM/I data.

An independent estimate of the error using observations from two satellites shows an error of 31% (std dev of 2.7%), consistent with the 38% estimated using (a.m. and p.m.) data from one satellite alone. Error estimates (31%) based on the 5° means by averaging four neighboring 2.5° boxes are larger than those (23%) estimated by assuming the means for these neighboring boxes are independent, thus suggesting spatial dependence of the 2.5° means.

Multiple regression analyses show that the error varies inversely as the square root of the number of samples but exhibits a somewhat weaker dependence on the mean rain rate. Regression analyses show a power law dependence of −0.255 to −0.265 on the rain rate for the 5° monthly means using data from a single satellite and a dependence of −0.366 for the 5° monthly means and −0.337 for the 2.5° monthly means based on two satellite measurements. The latter estimate is consistent with that obtained by Bell et al. using a different rainfall retrieval technique.

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A. T. C. Chang
,
L. S. Chiu
, and
G. Yang

Abstract

Four and a half years of the global monthly oceanic rain rates derived from the DMSP (Defense Meteorological Satellite Program) F-8 SSM/I (Special Sensor Microwave/Imager) data are used to study the diurnal cycles. Annual mean rainfall maps based on the SSM/I morning and evening observations are presented, and their differences are examined using a paired t test. The morning estimates are larger than the afternoon estimates by about 20% over the oceanic region between 50°S and 50°N, with significant differences located mainly along the intertropical convergence zone region. Using the measurements from two satellites, either DMSP F-8 and F-10 or DMSP F-10 and F-11, amplitudes and phases of the 24-h harmonic are estimated. The diurnal cycle shows a nocturnal or early morning maximum in 35%–40% of the oceanic regions. Monte Carlo simulations show that the rms errors associated with the estimated amplitude and phase are about 100% and 2 h, respectively, mainly due to the large random errors (50%) associated with the present rainfall estimates and the nonoptimal separation times of the DMSP satellite sampling.

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Alfred T. C. Chang
,
Long S. Chiu
, and
Thomas T. Wilheit

Abstract

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50%–60% for each 5° × 5° box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8%, a correlation of 0.7, and an rms difference of 55%.

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L. P. Chang
,
E. S. Takle
, and
R. L. Sani

Abstract

We have developed a two-dimensional finite-element model for simulating atmospheric flow in the planetary boundary layer (PBL) of the earth. The finite-element method provides a useful alternative to the conventional finite-difference method in studying Bow phenomena that involve graded meshes and (or) irregular computational domains. It also provides a more natural way of incorporating Dirichlet-type boundary conditions. These properties make the finite-element method especially suitable for studying PBL flows. With the Deardorff-O'Brien turbulence scheme, the model was able to generate reasonable results in the simulations of a neutral PBL wind profile and a sea-breeze circulation.

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J-W. Kim
,
J-T. Chang
,
N. L. Baker
,
D. S. Wilks
, and
W. L. Gates

Abstract

The estimation of the most probable local or mesoscale distribution of a climatic variable when only the large-scale value is given may be viewed as a sort of climate inversion problem. As an initial statistical study of this question, the monthly-averaged surface temperature and monthly total precipitation for stations in Oregon are analyzed for the purpose of relating their most probable mesoscale distributions to the large-scale monthly anomalies.

The first empirical orthogonal mode of the covariance matrix of mesoscale transient departures explains 78.2 and 80.8% of the total variance of temperature and precipitation, respectively. The time structure of the first mode is predominantly seasonal and is in phase with the large-scale anomalies, and the correlation coefficient between this oscillation and the large-scale anomaly is 0.96 for temperature and 0.95 for precipitation. The most probable mesoscale distribution as specified by only the first empirical orthogonal function is predictable with relative error of less than 37.9% for temperature and 37.1% for precipitation if the corresponding large-scale anomaly is known with an error of less than 10%. These results may be useful in the study of local climatic impacts with large-scale climate models.

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Ying-Hwa Kuo
,
Marina Skumanich
,
Philip L. Haagenson
, and
Julius S. Chang

Abstract

Fourteen observing system simulation experiments (OSSE) wore conducted using the results from a mesoscale model on the Oxidation and Scavenging Characteristics of April Rains(OSCAR) experiment to test the accuracy of trajectory models. Our results indicate that the current synoptic network and observational frequency over North America are inadequate for accurate computation of long-range transport of episodic events. It appears that improving the Observational frequency would be more cost effective than improving the spatial resolution for the existing network.

Reducing the three-dimensional air flow to two dimensions leads to a substantial amount of error for air parcel trajectories. Among the three simplifying assumptions—isobaric, isosigma, and isentropic—the isentropic model gives considerably better results than the isobaric or isosigma models, especially for the vertical transport.

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C-P. Chang
,
S. C. Hou
,
H. C. Kuo
, and
G. T. J. Chen

Abstract

The East Asian summer monsoon (Mei-yu) disturbance of 17–25 June 1992 was the most intense 850-hPa low center of such systems during a 7-yr period. Due to the moisture fluxes associated with the southwesterlies from the warm tropical oceans, diabatic heating has generally been considered the main energy source of these heavy-precipitation disturbances as they propagate eastward from the eastern flank of the Tibetan Plateau across southeastern China and move into the East China Sea. In this study piecewise potential vorticity inversion is used to analyze the physical mechanisms of this intense case, particularly the possible roles of midlatitude baroclinic processes in its development and evolution.

The development of the low-level vortex involved the coupling with two upper-level disturbances, one at 500 hPa that also originated from the eastern flank of the Tibetan Plateau, and another at 300 hPa. Both disturbances appeared later than and upstream of the low-level vortex. Faster eastward movements allowed them to catch up with the low-level vortex and led to a strong vertical coupling and deep tropopause folding. Initially, diabatic heating was the dominant mechanism for the low-level vortex while the tropopause process opposed it. Both mechanisms supported the 500-hPa disturbance, and tropopause folding was the dominant mechanism for the 300-hPa disturbance. As the vertical coupling developed, the tropopause process reversed its earlier role in the low-level disturbance and contributed to its development. Boundary layer and adiabatic effects also became contributive as the disturbance moved out of eastern China to the oceanic region.

The vertical coupling of the three disturbances was a major factor in the development. The timing and position of the middle-tropospheric disturbance was critical in bridging the upper- and lower-level disturbances and a deep tropopause folding. This midlatitude-originated process compounded the diabatic heating effect that was sustained by tropical moist air, leading to the strong intensification.

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Dong-Eon Chang
,
James A. Weinman
,
Carlos A. Morales
, and
William S. Olson

Abstract

This study seeks to evaluate the impact of several newly available sources of meteorological data on mesoscale model forecasts of the extratropical cyclone that struck Florida on 2 February 1998. Intermittent measurements of precipitation and integrated water vapor (IWV) distributions were obtained from Special Sensor Microwave/Imager (SSM/I) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations. The TMI also provided sea surface temperatures (SSTs) with structural detail of the Loop Current and Gulf Stream. Continuous lightning distributions were measured with a network of very low frequency radio receivers. Lightning data were tuned with intermittent spaceborne microwave radiometer data through a probability matching technique to continuously estimate convective rainfall rates.

A series of experiments were undertaken to evaluate the effect of those data on mesoscale model forecasts produced after assimilating processed rainfall and IWV for 6 h. Assimilating processed rainfall, IWV, and SSTs from TMI measurements in the model yielded improved forecasts of precipitation distributions and vertical motion fields. Assimilating those data also produced an improved 9-h forecast of the radar reflectivity cross section that was validated with a coincident observation from the TRMM spaceborne precipitation radar.

Sensitivity experiments showed that processed rainfall information had greater impact on the rainfall forecast than IWV and SST information. Assimilating latent heating in the correct location of the forecast model was found to be more important than an accurate determination of the rainfall intensity.

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