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Courtney Schumacher
,
Paul E. Ciesielski
, and
Minghua H. Zhang

Abstract

Diabatic heating (or Q1) profiles associated with specific cloud types are produced by matching synoptic cloud observations with a sounding budget analysis during the Tropical Rainfall Measuring Mission (TRMM) Kwajalein Experiment (KWAJEX), which took place in the Marshall Islands from late July through mid-September 1999. Fair-weather cumulus clouds produce up to 1 K day−1 of heating below 850 hPa and are associated with cooling throughout much of the rest of the troposphere. Cumulus congestus clouds produce heating on the order of 1 K day−1 up to 575 hPa and cooling in the mid- to upper troposphere. Cumulonimbus clouds produce heating through the depth of the troposphere, with a maximum of 3.7 K day−1 near 550 hPa. Cloud types indicating widespread rain (stratus or cumulus fractus of bad weather at low levels and nimbostratus at midlevels) have the largest and most elevated heating, with values >10 K day−1 above 600 hPa. Other mid- and high-level cloud types are shown to be consistent with area-averaged rain rates and Q1 profiles. Profiles of the divergence and apparent moisture sink (or Q2) for convective clouds are also analyzed and are shown to be consistent with the physics of the heating profiles just described.

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Hye-Mi Kim
,
Edmund K. M. Chang
, and
Minghua Zhang

Abstract

This study attempts, for the first time, to predict the annual number of tropical cyclones (TCs) affecting New York State (NYS), as part of the effort of the New York State Resiliency Institute for Storms and Emergencies (RISE). A pure statistical prediction model and a statistical–dynamical hybrid prediction model have been developed based on the understanding of the physical mechanism between NYS TCs and associated large-scale climate variability. During the cold phase of El Niño–Southern Oscillation, significant circulation anomalies in the Atlantic Ocean provide favorable conditions for more recurving TCs into NYS. The pure statistical prediction model uses the sea surface temperature (SST) over the equatorial Pacific Ocean from the previous months. Cross validation shows that the correlation between the observed and predicted numbers of NYS TCs is 0.56 for the June 1979–2013 forecasts. Forecasts of the probability of one or more TCs impacting NYS have a Brier skill score of 0.35 compared to climatology. The statistical–dynamical hybrid prediction model uses Climate Forecast System, version 2, SST predictions, which are statistically downscaled to forecast the number of NYS TCs based on a stepwise regression model. Results indicate that the initial seasonal prediction for NYS TCs can be issued in February using the hybrid model, with an update in June using the pure statistical prediction model. Based on the statistical model, for 2014, the predicted number of TCs passing through NYS is 0.33 and the probability of one or more tropical cyclones crossing NYS is 30%, which are both below average and in agreement with the actual activity (0 NYS TCs).

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Minghua Zhang
,
Richard C. J. Somerville
, and
Shaocheng Xie
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Courtney Schumacher
,
Minghua H. Zhang
, and
Paul E. Ciesielski

Abstract

Heating profiles calculated from sounding networks and other observations during three Tropical Rainfall Measuring Mission (TRMM) field campaigns [the Kwajalein Experiment (KWAJEX), TRMM Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA), and South China Sea Monsoon Experiment (SCSMEX)] show distinct geographical differences between oceanic, continental, and monsoon regimes. Differing cloud types (both precipitating and nonprecipitating) play an important role in determining the total diabatic heating profile. Variations in the vertical structure of the apparent heat source, Q 1, can be related to the diurnal cycle, large-scale forcings such as atmospheric waves, and rain thresholds at each location. For example, TRMM-LBA, which occurred in the Brazilian Amazon, had mostly deep convection during the day while KWAJEX, which occurred in the western portion of the Pacific intertropical convergence zone, had more shallow and moderately deep daytime convection. Therefore, the afternoon height of maximum heating was more bottom heavy (i.e., heating below 600 hPa) during KWAJEX compared to TRMM-LBA. More organized convective systems with extensive stratiform rain areas and upper-level cloud decks tended to occur in the early and late morning hours during TRMM-LBA and KWAJEX, respectively, thereby causing Q 1 profiles to be top heavy (i.e., maxima from 600 to 400 hPa) at those times. SCSMEX, which occurred in the South China Sea during the monsoon season, had top-heavy daytime and nighttime heating profiles suggesting that mesoscale convective systems occurred throughout the diurnal cycle, although more precipitation and upper-level cloud in the afternoon caused the daytime heating maximum to be larger. A tendency toward bottom- and top-heavy heating profile variations is also associated with the different cloud types that occurred before and after the passage of easterly wave troughs during KWAJEX, the easterly and westerly regimes during TRMM-LBA, and the monsoon onset and postonset active periods during SCSMEX. Rain thresholds based on heavy, moderate, and light/no-rain amounts can further differentiate top-heavy heating, bottom-heavy heating, and tropospheric cooling. These budget studies suggest that model calculations and satellite retrievals of Q 1 must account for a large number of factors in order to accurately determine the vertical structure of diabatic heating associated with tropical cloud systems.

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Xue Long Zhou
,
Marvin A. Geller
, and
Minghua Zhang

Abstract

There has been increasing recognition of the role of the tropical tropopause layer (TTL) in determining stratospheric water vapor concentrations—the TTL being a layer of transition between air showing tropospheric properties below and stratospheric properties above. This study investigates the spatial structure of temperatures in the TTL. A dehydration index based on the atmospheric region with temperatures colder than a specific reference temperature was defined to examine the TTL temperature structure and possible influences on stratospheric water vapor. The results indicate that dehydration regions with cold temperatures (e.g., <190 K) occur mainly over the western Pacific and are about 1.5–2.0 km in depth during Northern Hemisphere winter. The dehydration index is mainly dependent on the annual cycle of the TTL temperatures, but is strongly affected by interannual variations associated with the quasi-biennial oscillation (QBO) and El Niño–Southern Oscillation (ENSO). Dehydration regions with extremely cold temperatures and large sizes occur when cold temperature anomalies associated with the QBO arrive at the TTL in wintertime while the TTL is at the coldest phase of the annual cycle and under La Niña conditions. La Niña events have a more dramatic influence on the dehydration index than El Niño events.

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Weihua Yuan
,
Rucong Yu
,
Haoming Chen
,
Jian Li
, and
Minghua Zhang

Abstract

Subseasonal characteristics of the diurnal variation of the summer monsoon rainfall over central eastern China (25°–40°N, 110°–120°E) are analyzed using hourly station rain gauge data. Results show that the rainfall in the monsoon rain belt is dominated by the long-duration rainfall events (≥7 h) with early-morning peaks. The long-duration rainfall events and early-morning diurnal peaks experience subseasonal movement that is similar to that of the monsoon rain belt. When the monsoon rainfall is separated into the active and break periods, the long-duration early-morning precipitation dominates the active period, which is in sharp contrast to the short-duration (≤6 h) rainfall with leading late-afternoon diurnal peaks during the break period. The combination of different diurnal features of monsoon rainfall in the active and break monsoon periods also explains the less coherent diurnal phases of summer mean rainfall over central eastern China. The cause of the early-morning peak of rainfall during the active monsoon period is discussed.

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Marvin A. Geller
,
Weixing Shen
,
Minghua Zhang
, and
Wei-Wu Tan

Abstract

One-dimensional calculations are carried out for the time evolution of the equatorial lower stratospheric mean zonal wind forced by time-varying equatorial Kelvin and mixed Rossby–gravity waves. If the time variation of the wave momentum forcing is given by a steady forcing plus a sinusoidal modulation, a tendency toward phase locking between the period of the wave forcing’s modulation and the period of the resulting mean wind oscillation is found in some cases, depending on the period and magnitude of the wave forcing as well as the phase difference between variations of the easterly and westerly momentum fluxes. Regime diagrams are shown to make these dependences clearer. If the wave forcings are irregularly modulated, the resulting time variation of the wind oscillation shows no resemblance to the imposed time variation of the wave forcing. These simple calculations are used to indicate that for nonlinear phenomena, such as the quasi-biennial oscillation (QBO), one cannot conclude that a lack of correlation between two data records means that these are physically unrelated. When the equatorial wave momentum fluxes are modulated according to the eastern Pacific sea surface temperatures, the simulated time variation of the QBO period sometimes (depending on the phase relation between the easterly and westerly time-varying fluxes) shows a great resemblance to the observations. This suggests that easterly and westerly momentum fluxes into the equatorial lower stratosphere are related to SST variations.

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Tingting Han
,
Minghua Zhang
,
Botao Zhou
,
Xin Hao
, and
Shangfeng Li

Abstract

The relationship between the tropical west Pacific (TWP) and East Asian summer monsoon/precipitation has been documented in previous studies. However, the stability for the signals of midsummer precipitation in the TWP sea surface temperature (SST_TWP), which is important for climate variation, has drawn little attention. This study identifies a strengthened relationship between the leading empirical orthogonal function mode (EOF1) of midsummer precipitation over Northeast China (NEC) and the SST_TWP after the mid-1990s. The EOF1 mode shows a significant positive correlation with the SST_TWP for 1996–2016, whereas the relationship is statistically insignificant for 1961–90. Further results indicate that the North Pacific multidecadal oscillation (NPMO) shifts to a positive phase after the 1990s. In the positive NPMO phase, the anomalous circulation over the northeast Pacific expands westward over the central North Pacific–Aleutian Islands region. Concurrently, the SST_TWP-associated wavelike pattern propagates northeastward from the west Pacific to the northwest Pacific and farther to the North Pacific, facilitating the poleward expansion and intensification of the SST_TWP-related circulation anomalies over the North Pacific. Therefore, the SST_TWP has an enhanced influence on NEC precipitation through the modulation of the circulation anomalies over the central North Pacific–Aleutian Islands region after the mid-1990s. Additionally, the tropical anticyclone/cyclone associated with the SST_TWP expands westward to South China, exerting an intensified impact on meridional wind anomalies along eastern China and on moisture transport over NEC. These conditions jointly contribute to the strengthened relationship between the SST_TWP and the EOF1 mode of NEC midsummer precipitation after the mid-1990s.

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Brian A. Colle
,
Zhenhai Zhang
,
Kelly A. Lombardo
,
Edmund Chang
,
Ping Liu
, and
Minghua Zhang

Abstract

Extratropical cyclone track density, genesis frequency, deepening rate, and maximum intensity distributions over eastern North America and the western North Atlantic were analyzed for 15 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical period (1979–2004) and three future periods (2009–38, 2039–68, and 2069–98). The cyclones were identified using an automated tracking algorithm applied to sea level pressure every 6 h. The CMIP5 results for the historical period were evaluated using the Climate Forecast System Reanalysis (CFSR). The CMIP5 models were ranked given their track density, intensity, and overall performance for the historical period. It was found that six of the top seven CMIP5 models with the highest spatial resolution were ranked the best overall. These models had less underprediction of cyclone track density, more realistic distribution of intense cyclones along the U.S. East Coast, and more realistic cyclogenesis and deepening rates. The best seven models were used to determine projected future changes in cyclones, which included a 10%–30% decrease in cyclone track density and weakening of cyclones over the western Atlantic storm track, while in contrast there is a 10%–20% increase in cyclone track density over the eastern United States, including 10%–40% more intense (<980 hPa) cyclones and 20%–40% more rapid deepening rates just inland of the U.S. East Coast. Some of the reasons for these CMIP5 model differences were explored for the selected models based on model generated Eady growth rate, upper-level jet, surface baroclinicity, and precipitation.

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Tao Zhang
,
Wuyin Lin
,
Yanluan Lin
,
Minghua Zhang
,
Haiyang Yu
,
Kathy Cao
, and
Wei Xue

Abstract

Tropical cyclone (TC) genesis is a problem of great significance in climate and weather research. Although various environmental conditions necessary for TC genesis have been recognized for a long time, prediction of TC genesis remains a challenge due to complex and stochastic processes involved during TC genesis. Different from traditional statistical and dynamical modeling of TC genesis, in this study, a machine learning framework is developed to determine whether a mesoscale convective system (MCS) would evolve into a tropical cyclone. The machine learning models 1) are built upon a number of essential environmental predictors associated with MCSs/TCs, 2) predict whether MCSs can become TCs at different lead times, and 3) provide information about the relative importance of each predictor, which can be conducive to discovering new aspects of TC genesis. The results indicate that the machine learning classifier, AdaBoost, is able to achieve a 97.2% F1-score accuracy in predicting TC genesis over the entire tropics at a 6-h lead time using a comprehensive set of environmental predictors. A robust performance can still be attained when the lead time is extended to 12, 24, and 48 h, and when this machine learning classifier is separately applied to the North Atlantic Ocean and the western North Pacific Ocean. In contrast, the conventional approach based on the genesis potential index can have no more than an 80% F1-score accuracy. Furthermore, the machine learning classifier suggests that the low-level vorticity and genesis potential index are the most important predictors to TC genesis, which is consistent with previous discoveries.

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