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J. C. Hubbert
,
S. M. Ellis
,
W.-Y. Chang
,
S. Rutledge
, and
M. Dixon

Abstract

Data collected by the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) during the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX) in Taiwan are analyzed and used to infer storm microphysics in the ice phase of convective storms. Both simultaneous horizontal (H) and vertical (V) (SHV) transmit polarization data and fast-alternating H and V (FHV) transmit polarization data are used in the analysis. The SHV Z dr (differential reflectivity) data show radial stripes of biased data in the ice phase that are likely caused by aligned and canted ice crystals. Similar radial streaks in the linear depolarization ratio (LDR) are presented that are also biased by the same mechanism. Dual-Doppler synthesis and sounding data characterize the storm environment and support the inferences concerning the ice particle types. Small convective cells were observed to have both large positive and large negative K dp (specific differential phase) values. Negative K dp regions suggest that ice crystals are vertically aligned by electric fields. Since high |K dp| values of 0.8° km−1 in both negative and positive K dp regions in the ice phase are accompanied by Z dr values close to 0 dB, it is inferred that there are two types of ice crystals present: 1) smaller aligned ice crystals that cause the K dp signatures and 2) larger aggregates or graupel that cause the Z dr signatures. The inferences are supported with simulated ice particle scattering calculations. A radar scattering model is used to explain the anomalous radial streaks in SHV and LDR.

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P. Chang
,
T. Yamagata
,
P. Schopf
,
S. K. Behera
,
J. Carton
,
W. S. Kessler
,
G. Meyers
,
T. Qu
,
F. Schott
,
S. Shetye
, and
S.-P. Xie

Abstract

The tropical oceans have long been recognized as the most important region for large-scale ocean–atmosphere interactions, giving rise to coupled climate variations on several time scales. During the Tropical Ocean Global Atmosphere (TOGA) decade, the focus of much tropical ocean research was on understanding El Niño–related processes and on development of tropical ocean models capable of simulating and predicting El Niño. These studies led to an appreciation of the vital role the ocean plays in providing the memory for predicting El Niño and thus making seasonal climate prediction feasible. With the end of TOGA and the beginning of Climate Variability and Prediction (CLIVAR), the scope of climate variability and predictability studies has expanded from the tropical Pacific and ENSO-centric basis to the global domain. In this paper the progress that has been made in tropical ocean climate studies during the early years of CLIVAR is discussed. The discussion is divided geographically into three tropical ocean basins with an emphasis on the dynamical processes that are most relevant to the coupling between the atmosphere and oceans. For the tropical Pacific, the continuing effort to improve understanding of large- and small-scale dynamics for the purpose of extending the skill of ENSO prediction is assessed. This paper then goes beyond the time and space scales of El Niño and discusses recent research activities on the fundamental issue of the processes maintaining the tropical thermocline. This includes the study of subtropical cells (STCs) and ventilated thermocline processes, which are potentially important to the understanding of the low-frequency modulation of El Niño. For the tropical Atlantic, the dominant oceanic processes that interact with regional atmospheric feedbacks are examined as well as the remote influence from both the Pacific El Niño and extratropical climate fluctuations giving rise to multiple patterns of variability distinguished by season and location. The potential impact of Atlantic thermohaline circulation on tropical Atlantic variability (TAV) is also discussed. For the tropical Indian Ocean, local and remote mechanisms governing low-frequency sea surface temperature variations are examined. After reviewing the recent rapid progress in the understanding of coupled dynamics in the region, this study focuses on the active role of ocean dynamics in a seasonally locked east–west internal mode of variability, known as the Indian Ocean dipole (IOD). Influences of the IOD on climatic conditions in Asia, Australia, East Africa, and Europe are discussed. While the attempt throughout is to give a comprehensive overview of what is known about the role of the tropical oceans in climate, the fact of the matter is that much remains to be understood and explained. The complex nature of the tropical coupled phenomena and the interaction among them argue strongly for coordinated and sustained observations, as well as additional careful modeling investigations in order to further advance the current understanding of the role of tropical oceans in climate.

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William W. Hager
,
John S. Nisbet
,
John R. Kasha
, and
Wei-Chang Shann

Abstract

Numerical simulations based on a three-dimensional model for the electric fields in a thunderstorm are presented. In some of the simulations, we solve problems with known analytical solutions in order to determine the relevant physical properties that must be incorporated in a thunderstorm model. We then examine the inverse problem: Given measurements for the electric fields in a thunderstorm what are the associated current generators? Fits based on an analytic formula that neglects conduction currents give approximations to the current generators while simulations based on the thunderstorm model yield refinements to the generators. As a specific illustration, we obtain estimates for current generators associated with a storm observed at the Kennedy Space Center on 11 July 1978. Finally, we explore qualitative properties of our method used to simulate lightning. It is observed that as the charged particles associated with the thunderstorm are spread over a larger and larger volume, the flesh rate decreases while the charge transfer associated with each flash increases. Also, it is seen that a series of intracloud flashes can produce a charge imbalance in the cloud that will eventually lead to a cloud-to-ground discharge.

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Tsing-Chang Chen
,
Jin-ho Yoon
,
Kathryn J. St. Croix
, and
Eugene S. Takle

Analyzing the Global Historical Climatology Network, outgoing longwave radiation, and NCEP–NCAR reanalysis data over the Amazon Basin, the authors find a clear interdecadal increasing trend over the past four decades in both rainfall and intensity of the hydrological cycle. These interdecadal variations are a result of the interdecadal change of the global divergent circulation. On the contrary, the impact of the Amazon deforestation as evaluated by all numerical studies has found a reduction of rainfall and evaporation, and an increase of temperature in the Amazon Basin extending its dry season. Evidently, the interdecadal trend of the basin's hydrological cycle revealed from observations functions in a course opposite to the deforestation scenario. Results of this study suggest that future studies analyzing the impact of the basin-scale deforestation on the regional hydrological cycle and climate should be reassessed with multidecade numerical simulations including both schemes handling the land-surface processes and the mechanism generating proper interdecadal variation of the global divergent 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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S. D. Schubert
,
Y. Chang
,
H. Wang
,
R. D. Koster
, and
A. M. Molod

Abstract

We outline a framework for identifying the geographical sources of biases in climate models. By forcing the model with time-averaged short-term analysis increments [tendency bias corrections (TBCs)] over well-defined regions, we can quantify how the associated reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections. Companion experiments in which the model is fully corrected [constrained to remain close to the analysis at each time step, termed replay (RPL)] in the various regions provide an upper bound to the local and remote TBC impacts. An example is given based on MERRA-2 and the NASA/GMAO GEOS AGCM used to generate MERRA-2. The results highlight the ability of the approach to isolate the geographical sources of some of the long-standing boreal summer biases of the GEOS model, including a stunted North Pacific summer jet, a dry bias in the U.S. Great Plains, and a warm bias over most of the Northern Hemisphere land. In particular, we show that the TBC over a region that encompasses Tibet has by far the largest impact (compared with all other regions) on the NH summer jets and related variables, leading to significant improvements in the simulation of North American temperature and, to a lesser degree, precipitation. It is further shown that the results of the regional TBC experiments are for the most part linear in the summer hemisphere, allowing a robust interpretation of the results.

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Y. Chang
,
S. D. Schubert
,
R. D. Koster
,
A. M. Molod
, and
H. Wang

Abstract

We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.

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