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Qingyun Zhao
,
Fuqing Zhang
,
Teddy Holt
,
Craig H. Bishop
, and
Qin Xu

Abstract

An ensemble Kalman filter (EnKF) has been adopted and implemented at the Naval Research Laboratory (NRL) for mesoscale and storm-scale data assimilation to study the impact of ensemble assimilation of high-resolution observations, including those from Doppler radars, on storm prediction. The system has been improved during its implementation at NRL to further enhance its capability of assimilating various types of meteorological data. A parallel algorithm was also developed to increase the system’s computational efficiency on multiprocessor computers. The EnKF has been integrated into the NRL mesoscale data assimilation system and extensively tested to ensure that the system works appropriately with new observational data stream and forecast systems. An innovative procedure was developed to evaluate the impact of assimilated observations on ensemble analyses with no need to exclude any observations for independent validation (as required by the conventional evaluation based on data-denying experiments). The procedure was employed in this study to examine the impacts of ensemble size and localization on data assimilation and the results reveal a very interesting relationship between the ensemble size and the localization length scale. All the tests conducted in this study demonstrate the capabilities of the EnKF as a research tool for mesoscale and storm-scale data assimilation with potential operational applications.

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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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J. Ballabrera-Poy
,
R. Murtugudde
,
R-H. Zhang
, and
A. J. Busalacchi

Abstract

The ability to use remotely sensed ocean color data to parameterize biogenic heating in a coupled ocean–atmosphere model is investigated. The model used is a hybrid coupled model recently developed at the Earth System Science Interdisciplinary Center (ESSIC) by coupling an ocean general circulation model with a statistical atmosphere model for wind stress anomalies. The impact of the seasonal cycle of water turbidity on the annual mean, seasonal cycle, and interannual variability of the coupled system is investigated using three simulations differing in the parameterization of the vertical attenuation of downwelling solar radiation: (i) a control simulation using a constant 17-m attenuation depth, (ii) a simulation with the spatially varying annual mean of the satellite-derived attenuation depth, and (iii) a simulation accounting for the seasonal cycle of the attenuation depth. The results indicate that a more realistic attenuation of solar radiation slightly reduces the cold bias of the model. While a realistic attenuation of solar radiation hardly affects the annual mean and the seasonal cycle due to anomaly coupling, it significantly affects the interannual variability, especially when the seasonal cycle of the attenuation depth is used. The seasonal cycle of the attenuation depth interacts with the low-frequency equatorial dynamics to enhance warm and cold anomalies, which are further amplified via positive air–sea feedbacks. These results also indicate that interannual variability of the attenuation depths is required to capture the asymmetric biological feedbacks during cold and warm ENSO events.

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Harry H. Hendon
,
Matthew C. Wheeler
, and
Chidong Zhang

Abstract

Observations of the development of recent El Niño events suggest a pivotal role for the Madden–Julian oscillation (MJO). Previous attempts to uncover a systematic relationship between MJO activity and the El Niño–Southern Oscillation (ENSO), however, have yielded conflicting results. In this study the MJO–ENSO relationship is stratified by season, and the focus is on MJO activity in the equatorial western Pacific. The results demonstrate that MJO activity in late boreal spring leads El Niño in the subsequent autumn–winter for the period 1979–2005. Spring is the season when MJO activity is least asymmetric with respect to the equator and displays the most sensitivity to SST variations at the eastern edge of the warm pool. Enhanced MJO activity in the western Pacific in spring is associated with an eastward-expanded warm pool and low-frequency westerly surface zonal wind anomalies. These sustained westerly anomalies in the western Pacific are hypothesized to project favorably onto a developing El Niño in spring.

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R. W. Lindsay
,
J. Zhang
,
A. Schweiger
,
M. Steele
, and
H. Stern

Abstract

The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.

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Wei Cheng
,
John C. H. Chiang
, and
Dongxiao Zhang

Abstract

The Atlantic meridional overturning circulation (AMOC) simulated by 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical (1850–2005) and future climate is examined. The historical simulations of the AMOC mean state are more closely matched to observations than those of phase 3 of the Coupled Model Intercomparison Project (CMIP3). Similarly to CMIP3, all models predict a weakening of the AMOC in the twenty-first century, though the degree of weakening varies considerably among the models. Under the representative concentration pathway 4.5 (RCP4.5) scenario, the weakening by year 2100 is 5%–40% of the individual model's historical mean state; under RCP8.5, the weakening increases to 15%–60% over the same period. RCP4.5 leads to the stabilization of the AMOC in the second half of the twenty-first century and a slower (then weakening rate) but steady recovery thereafter, while RCP8.5 gives rise to a continuous weakening of the AMOC throughout the twenty-first century. In the CMIP5 historical simulations, all but one model exhibit a weak downward trend [ranging from −0.1 to −1.8 Sverdrup (Sv) century−1; 1 Sv ≡ 106 m3 s−1] over the twentieth century. Additionally, the multimodel ensemble–mean AMOC exhibits multidecadal variability with a ~60-yr periodicity and a peak-to-peak amplitude of ~1 Sv; all individual models project consistently onto this multidecadal mode. This multidecadal variability is significantly correlated with similar variations in the net surface shortwave radiative flux in the North Atlantic and with surface freshwater flux variations in the subpolar latitudes. Potential drivers for the twentieth-century multimodel AMOC variability, including external climate forcing and the North Atlantic Oscillation (NAO), and the implication of these results on the North Atlantic SST variability are discussed.

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Wei Zhang
,
H.-F. Graf
,
Yee Leung
, and
Michael Herzog

Abstract

This study examines whether there exist significant differences in tropical cyclone (TC) landfall between central Pacific (CP) El Niño, eastern Pacific (EP) El Niño, and La Niña during the peak TC season (June–October) and how and to what extent CP El Niño influences TC landfall over East Asia for the period 1961–2009. The peak TC season is subdivided into summer [June–August (JJA)] and autumn [September–October (SO)]. The results are summarized as follows: (i) during the summer of CP El Niño years, TCs are more likely to make landfall over East Asia because of a strong easterly steering flow anomaly induced by the westward shift of the subtropical high and northward-shifted TC genesis. In particular, TCs have a greater probability of making landfall over Japan and Korea during the summer of CP El Niño years. (ii) In the autumn of CP El Niño years, TC landfall in most areas of East Asia, especially Indochina, the Malay Peninsula, and the Philippines, is likely to be suppressed because the large-scale circulation resembles that of EP El Niño years. (iii) During the whole peak TC season [June–October (JJASO)] of CP El Niño years, TCs are more likely to make landfall over Japan and Korea. TC landfall in East Asia as a whole has an insignificant association with CP El Niño during the peak TC season. In addition, more (less) TCs are likely to make landfall in China, Indochina, the Malay Peninsula, and the Philippines during the peak TC season of La Niña (EP El Niño) years.

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Guilong Li
,
Xuebin Zhang
,
Francis Zwiers
, and
Qiuzi H. Wen

Abstract

A framework for the construction of probabilistic projections of high-resolution monthly temperature over North America using available outputs of opportunity from ensembles of multiple general circulation models (GCMs) and multiple regional climate models (RCMs) is proposed. In this approach, a statistical relationship is first established between RCM output and that from the respective driving GCM and then this relationship is applied to downscale outputs from a larger number of GCM simulations. Those statistically downscaled projections were used to estimate empirical quantiles at high resolution. Uncertainty in the projected temperature was partitioned into four sources including differences in GCMs, internal variability simulated by GCMs, differences in RCMs, and statistical downscaling including internal variability at finer spatial scale. Large spatial variability in projected future temperature changes is found, with increasingly larger changes toward the north in winter temperature and larger changes in the central United States in summer temperature. Under a given emission scenario, downscaling from large scale to small scale is the most important source of uncertainty, though structural errors in GCMs become equally important by the end of the twenty-first century. Different emission scenarios yield different projections of temperature change. This difference increases with time. The difference between the IPCC’s Special Report on Emissions Scenarios (SRES) A2 and B1 in the median values of projected changes in 30-yr mean temperature is small for the coming 30 yr, but can become almost as large as the total variance due to internal variability and modeling errors in both GCM and RCM later in the twenty-first century.

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M. H. Zhang
,
R. D. Cess
, and
S. C. Xie

Abstract

Satellite measurements from January 1985 to December 1989 show that warmer tropical oceans as a whole are associated with less longwave greenhouse effect of clouds and less cloud reflection of solar radiation to the space. The regression slopes of longwave and shortwave cloud radiative forcings against sea surface temperatures averaged from 30°N to 30°S are about −3 and 2 W m−2 K−1, respectively. Relationships of cloud forcings and sea surface temperatures are analyzed for regions with different sizes. As has been reported in previous studies, the magnitude of area-averaged cloud radiative forcing for both longwave and shortwave radiations increases with sea surface temperatures in the equatorial eastern Pacific and is insensitive to sea surface temperatures over the tropical Pacific basin. Yet, when the region extends beyond the tropical Pacific, the magnitude decreases with sea surface temperatures. This phenomenon is shown to relate to changes in clouds over the tropical Indian Ocean and Atlantic, where sea surface temperatures increased but clouds decreased during the 1987 El Niño event. Relevance of the results to other climate changes is discussed.

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Gang Zhang
,
Kerry H. Cook
, and
Edward K. Vizy

Abstract

This study provides an improved understanding of the diurnal cycle of warm season (June–September) rainfall over West Africa, including its underlying physical processes. Rainfall from the Tropical Rainfall Measuring Mission and atmospheric dynamics fields from reanalyses are used to evaluate the 1998–2013 climatology and a case study for 2006.

In both the climatology and the 2006 case study, most regions of West Africa are shown to have a single diurnal peak of rainfall either in the afternoon or at night. Averaging over West Africa produces a diurnal cycle with two peaks, but this type of diurnal cycle is quite atypical on smaller space scales. Rainfall systems are usually generated in the afternoon and propagate westward, lasting into the night. Afternoon rainfall peaks are associated with an unstable lower troposphere. They occur either over topography or in regions undisturbed by nocturnal systems, allowing locally generated instability to dominate. Nocturnal rainfall peaks are associated with the westward propagation of rainfall systems and not generally with local instability. Nocturnal rainfall peaks occur most frequently about 3°–10° of longitude downstream of regions with afternoon rainfall peaks. The diurnal cycle of rainfall is closely associated with the timing of extreme rainfall events.

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