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Tianming Li
and
Timothy F. Hogan

Abstract

The role of the annual-mean climate on seasonal and interannual variability in the tropical Pacific is investigated by means of a coupled atmosphere–ocean general circulation model. The atmospheric component of this coupled model is the Naval Operational Global Atmospheric Prediction System and the oceanic component is the Geophysical Fluid Dynamics Laboratory Modular Ocean Model. Three sets of experiments are conducted. In case A, no annual-mean flux adjustment is applied so that the coupled model generates its own time-mean state. In case B, an annual-mean flux adjustment for SST is applied. In case C, both the annual-mean SST and surface wind are adjusted. It is found that a realistic simulation of both the seasonal and interannual variations can be achieved when a realistic annual-mean state is presented. The long-term (40 yr) simulations of the coupled GCM demonstrate the importance of the annual-mean climate on seasonal and interannual variability in the Tropics. The mechanism that causes an annual rather than a semiannual cycle at the equator is discussed. The authors particularly notice that the interannual oscillations in the model capture essentially all three ENSO phase transition modes: the delayed oscillator mode, the slow SST mode, and the stationary SST mode.

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K. Goubanova
,
L. Li
,
P. Yiou
, and
F. Codron

Abstract

The idea of using large-scale information to predict local climate variability is widely exploited in climate change impact studies as an alternative to computationally expensive high-resolution models. This approach implies the hypothesis that the statistical relationship between large-scale climate states and local variables defined for the present-day climate remains valid in the altered climate. In this paper, the concept of weather regimes is used to deduce a relationship between large-scale circulation and European winter temperature. The change in temperature with increased greenhouse gases is, however, not homogeneous among the individual regimes. As a result, the impact of the weather regimes on local temperature changes varies in the future, limiting its usefulness for refining temperature changes to the small scale.

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X. Zou
,
X. Wang
,
F. Weng
, and
G. Li

Abstract

After the successful launches of the first two polar-orbiting satellites in a new Fengyun-3 (FY-3) series, FY-3A/B, into a morning- and afternoon-configured orbit in May 2008 and November 2010, respectively, China will launch its next three polar-orbiting satellites before 2020. The Microwave Temperature Sounder (MWTS) on the FY-3A/B satellites has four channels that have the same channel frequency as channels 3, 5, 7, and 9 of Advanced Microwave Sounding Unit-A (AMSU-A). Thus, the quality of the brightness temperature measurements from the FY-3A MWTS can be assessed using the AMSU-A brightness temperature observations from the NOAA-18 satellite. Overall, MWTS data compare favorably with AMSU-A data in terms of its global bias to NWP simulations. The standard deviations of global MWTS brightness temperatures are slightly larger than those of AMSU-A data. The scan-angle dependence of the brightness temperature bias is found to be symmetric for MWTS channel 3 as well as AMSU-A channel 7, and asymmetric for MWTS channels 2 and 4 and AMSU-A channels 5 and 9; there is a warm (cold) bias located at the beginning (end) of a scan line for all asymmetric channels except for MWTS channel 4. A major difference between the two instruments is that the MWTS biases in channels 3 and 4 are negative in low latitudes and positive in high latitudes, while the AMSU-A biases are negative in all latitudes. A detailed analysis of the data reveals that such a difference is closely related to the difference in the temperature dependence of biases between the two instruments. The AMSU-A biases are independent of the scene temperature, but MWTS biases vary with the earth scene brightness temperature. The root cause of the bias could be a combination of several factors, including solar contamination on its calibration target, detector nonlinearity, and the center frequency drift. This study further demonstrates the utility of a well-calibrated radiometer like AMSU-A for the assessment of a new instrument with NWP fields that are used as inputs to forward radiative transfer simulations.

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F. Li
,
A. M. Vogelmann
, and
V. Ramanathan

Abstract

This study uses data collected from the Clouds and the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments to determine Saharan dust broadband shortwave aerosol radiative forcing over the Atlantic Ocean near the African coast (15°–25°N, 45°–15°W). The clear-sky aerosol forcing is derived directly from these data, without requiring detailed information about the aerosol properties that are not routinely observed such as chemical composition, microphysical properties, and their height variations. To determine the diurnally averaged Saharan dust radiative forcing efficiency (i.e., broadband shortwave forcing per unit optical depth at 550 nm, W m−2 τ −1 a ), two extreme seasons are juxtaposed: the high-dust months [June–August (JJA)] and the low-dust months [November–January (NDJ)]. It is found that the top-of-atmosphere (TOA) diurnal mean forcing efficiency is −35 ± 3 W m−2 τ −1 a for JJA, and −26 ± 3 W m−2 τ −1 a for NDJ. These efficiencies can be fit by reducing the spectrally varying aerosol single-scattering albedo such that its value at 550 nm is reduced from 0.95 ± 0.04 for JJA to about 0.86 ± 0.04 for NDJ. The lower value for the low-dust months might be influenced by biomass-burning aerosols that were transported into the study region from equatorial Africa. Although the high-dust season has a greater (absolute value of the) TOA forcing efficiency, the low-dust season may have a greater surface forcing efficiency. Extrapolations based on model calculations suggest the surface forcing efficiencies to be about −65 W m−2 τ −1 a for the high-dust season versus −81 W m−2 τ −1 a for the low-dust season. These observations indicate that the aerosol character within a region can be readily modified, even immediately adjacent to a powerful source region such as the Sahara. This study provides important observational constraints for models of dust radiative forcing.

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Gerald F. Herman
,
Man-Li C. Wu
, and
Winthrop T. Johnson

Abstract

The effect of global cloudiness on the solar and infrared components of the earth's radiation balance is studied in general circulation model experiments. A wintertime simulation is conducted in which the cloud radiative transfer calculations use realistic cloud optical properties and are fully interactive with model-generated cloudiness. This simulation is compared to others in which the clouds are alternatively non-interactive with respect to the solar or thermal radiation calculations. Other cloud processes (formation, latent heat release, precipitation, vertical mixing) were accurately simulated in these experiments.

We conclude that on a global basis clouds increase the global radiation balance by 40 W m−2 by absorbing longwave radiation, but decrease it by 56 W m−2 by reflecting solar radiation to space. The net cloud effect is therefore a reduction of the radiation balance by 16 W m−2, and is dominated by the cloud albedo effect.

Changes in cloud frequency and distribution and in atmospheric and land temperatures are also reported for the control and for the non-interactive simulations. In general, removal of the clouds’ infrared absorption cools the atmosphere and causes additional cloudiness to occur, while removal of the clouds’ solar radiative properties warms the atmosphere and causes fewer clouds to form. It is suggested that layered clouds and convective clouds over water enter the climate system as positive feedback components, while convective clouds over land enter as negative components.

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Yalei You
,
F. Joseph Turk
,
Ziad S. Haddad
,
Li Li
, and
Guosheng Liu

Abstract

The microwave land surface emissivity (MLSE) over the continental United States was examined during 2011 as a function of prior rainfall conditions using two independent emissivity estimation techniques, one providing instantaneous estimates based on a clear-scene emissivity principal component (PC) analysis and the other based on physical radiative transfer modeling. Results show that over grass, closed shrub, and cropland, prior rainfall can cause the horizontally polarized 10-GHz brightness temperature (TB) to drop by as much as 20 K, with a corresponding emissivity drop of approximately 0.06, whereby prior rain exhibited little influence on the emissivity over forest because of the dense vegetation. The correlation between emissivity and its leading principal components and the prior rainfall over grass, closed shrub, and cropland is −0.6, while it is only −0.1 over forested areas. Forward-simulated TB using the PC-based emissivity derived from instantaneous Tropical Rainfall Measuring Mission (TRMM) satellite overpasses agrees much better with TRMM Microwave Imager (TMI) observations relative to a climatologically based emissivity, especially after a period of heavy rain. Two potential applications of the PC-based emissivity are demonstrated. The first exploits the time history change of the MLSE to estimate the amount of prior rainfall. The second application is a method to estimate the emissivity underneath precipitating radiometric scenes by first adjusting the surface-sensitive principal components that were derived under clear-sky scenes and then by reconstructing the joint emissivity (all channels simultaneously) from the modified PC structure. The results are applicable to future overland passive microwave rainfall retrieval algorithms to simultaneously detect and estimate precipitation amounts under dynamically changing surface conditions.

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Puxi Li
,
Christopher Moseley
,
Andreas F. Prein
,
Haoming Chen
,
Jian Li
,
Kalli Furtado
, and
Tianjun Zhou

Abstract

Mesoscale convective systems (MCSs) play an important role in modulating the global water cycle and energy balance and frequently generate high-impact weather events. The majority of existing literature studying MCS activity over East Asia is based on specific case studies and more climatological investigations revealing the precipitation characteristics of MCSs over eastern China are keenly needed. In this study, we use an iterative rain cell tracking method to identify and track MCS precipitation during 2008–16 to investigate regional differences and seasonal variations of MCS precipitation characteristics. Our results show that the middle-to-lower reaches of the Yangtze River basin (YRB-ML) receive the largest amount and exhibit the most pronounced seasonal cycle of MCS precipitation in eastern China. MCS precipitation over YRB-ML can exceed 2.6 mm day−1 in June, contributing over 30.0% of April–July total rainfall. Particularly long-lived MCSs occur over the eastern periphery of the Tibetan Plateau (ETP), with 25% of MCSs over the ETP persisting for more than 18 h in spring. In addition, spring MCSs feature larger rainfall areas, longer durations, and faster propagation speeds. Summer MCSs have a higher precipitation intensity and a more pronounced diurnal cycle except for southeastern China, where MCSs have similar precipitation intensity in spring and summer. There is less MCS precipitation in autumn, but an MCS precipitation center over the ETP still persists. MCSs reach peak hourly rainfall intensities during the time of maximum growth (a few hours after genesis), reach their maximum size around 5 h after genesis, and start decaying thereafter.

Open access
J. Li
,
Y. Li
,
J. Steppeler
,
A. Laurian
,
F. Fang
, and
D. Knapp
Open access
Liqiang Sun
,
Huilan Li
,
M. Neil Ward
, and
David F. Moncunill

Abstract

Understanding of climate influence on crop yields can help in the design of policies to reduce climate-related vulnerability in many parts of the world, including the target of this case study—the state of Ceará, Brazil. The study has examined the relationships between climate variations and corn yields and, in addition, has estimated the potential predictability of corn yields in Ceará drawing on the now well-established seasonal predictability of the region’s climate based on prevailing patterns of sea surface temperature (SST), especially in the tropical Atlantic and tropical Pacific Oceans. The relationships between corn yields and climate variables have been explored using observed data for the period of 1952–2001. A linear regression–based corn-yield model was evaluated by comparing the model-simulated yields with the observations using three goodness-of-fit measures: the coefficient of determination, the index of agreement, and the mean absolute error. A comparative performance analysis was carried out on several climate variables to determine the most appropriate climate index for simulating corn yields in Ceará. A weather index was defined to measure the severity of drought and flooding conditions in the growing season for corn. The analysis indicated that the weather index is the best climate parameter for simulating corn yields in Ceará. The observed weather index can explain 56.8% of the variance of the observed corn yields. High potential predictability of the weather index was revealed by the evaluation of an ensemble of 10 runs with the NCEP Regional Spectral Model nested into the ECHAM4.5 atmospheric general circulation model, driven with observed SSTs in each season for the period of 1971–2000. Whereas these runs are based on the actual observed SST pattern in each season, other studies have shown that persistence of SST over several months is sufficient for a true predictive capability. The aim here was to show that the SST-forced component of climate variation does translate into the weather features that are important for crop yields. Indeed, the results demonstrate the striking extent to which the year-to-year changes in SST force local climate characteristics that can specify the year-to-year variations in corn yields. The variance of corn yield explained by the SST-driven model was 49.5%.

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Qiang Li
,
David M. Farmer
,
Timothy F. Duda
, and
Steve Ramp

Abstract

The performance of pressure sensor–equipped inverted echo sounders for monitoring nonlinear internal waves is examined. The inverted echo sounder measures the round-trip acoustic travel time from the sea floor to the sea surface and thus acquires vertically integrated information on the thermal structure, from which the first baroclinic mode of thermocline motion may be inferred. This application of the technology differs from previous uses in that the wave period (∼30 min) is short, requiring a more rapid transmission rate and a different approach to the analysis. Sources of error affecting instrument performance include tidal effects, barotropic adjustment to internal waves, ambient acoustic noise, and sea surface roughness. The latter two effects are explored with a simulation that includes surface wave reconstruction, acoustic scattering based on the Kirchhoff approximation, wind-generated noise, sound propagation, and the instrument’s signal processing circuitry. Bias is introduced as a function of wind speed, but the simulation provides a basis for bias correction.

The assumption that the waves do not significantly affect the mean stratification allows for a focus on the dynamic response. Model calculations are compared with observations in the South China Sea by using nearby temperature measurements to provide a test of instrument performance. After applying corrections for ambient noise and surface roughness effects, the inverted echo sounder exhibits an RMS variability of approximately 4 m in the estimated depth of the eigenfunction maximum in the wind speed range 0 ≤ U 10 ≤ 10 m s−1. This uncertainty may be compared with isopycnal excursions for nonlinear internal waves of 100 m, showing that the observational approach is effective for measurements of nonlinear internal waves in this environment.

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