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Ning Lu, Kevin E. Trenberth, Jun Qin, Kun Yang, and Ling Yao

Abstract

Long-term trends in precipitable water (PW) are an important component of climate change assessments for the Tibetan Plateau (TP). PW products from Moderate Resolution Imaging Spectroradiometer (MODIS) are able to provide good spatial coverage of PW over the TP but limited in time coverage, while the meteorological stations in the TP can estimate long-term PW but unevenly distributed. To detect the decadal trend in PW over the TP, Bayesian inference theory is used to construct long-term and spatially continuous PW data for the TP based on the station and MODIS observations. The prior information on the monthly-mean PW from MODIS and the 63 stations over the TP for 2000–06 is used to get the posterior probability knowledge that is utilized to build a Bayesian estimation model. This model is then operated to estimate continuous monthly-mean PW for 1970–2011 and its performance is evaluated using the monthly MODIS PW anomalies (2007–11) and annual GPS PW anomalies (1995–2011), with RMSEs below 0.65 mm, to demonstrate that the model estimation can reproduce the PW variability over the TP in both space and time. Annual PW series show a significant increasing trend of 0.19 mm decade−1 for the TP during the 42 years. The most significant PW increase of 0.47 mm decade−1 occurs for 1986–99 and an insignificant decrease occurs for 2000–11. From the comparison of the PW data from JRA-55, ERA-40, ERA-Interim, MERRA, NCEP-2, and ISCCP, it is found that none of them are able to show the actual long-term trends and variability in PW for the TP as the Bayesian estimation.

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Anthony D. Del Genio, Yonghua Chen, Daehyun Kim, and Mao-Sung Yao

Abstract

The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden–Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10 MJO events show the following anticipated MJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E) column water vapor (CWV) increases by ~5 mm during the shallow–deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between ~46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow–deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV.

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Anthony D. Del Genio, Mao-Sung Yao, William Kovari, and Kenneth K-W. Lo

Abstract

An efficient new prognostic cloud water parameterization designed for use in global climate models is described. The scheme allows for life cycle effects in stratiform clouds and permits cloud optical properties to be determined interactively. The parameterization contains representations of all important microphysical processes, including autoconversion, accretion, Bergeron–Findeisen diffusional growth, and cloud/rain water evaporation. Small-scale dynamical processes, including detrainment of convective condensate, cloud-top entrainment instability, and stability-dependent cloud physical thickness variations, are also taken into account. Cloud optical thickness is calculated from the predicted liquid/ice water path and a variable droplet effective radius estimated by assuming constant droplet number concentration. Microphysical and radiative properties are assumed to be different for liquid and ice clouds, and for liquid clouds over land and ocean.

The parameterization is validated in several simulations using the Goddard Institute for Space Studies (GISS) general circulation model (GCM). Comparisons are made with a variety of datasets, including ERBE radiative fluxes and cloud forcing, ISCCP and surface-observed cloud properties, SSM/I liquid water path, and SAGE II thin cirrus cover. Validation is judged on the basis of the model's depiction of both the mean state; diurnal, seasonal, and interannual variability; and the temperature dependence of cloud properties. Relative to the diagnostic cloud scheme used in the previous GISS GCM, the prognostic parameterization strengthens the model's hydrologic cycle and general circulation, both directly and indirectly (via increased cumulus heating). Sea surface temperature (SST) perturbation experiments produce low climate sensitivity and slightly negative cloud feedback for globally uniform SST changes, but high sensitivity and positive cloud feedback when tropical Pacific SST gradients weaken with warming. Changes in the extent and optical thickness of tropical cumulus anvils appear to be the primary factor determining the sensitivity. This suggests that correct simulations of upward transport of convective condensate and of Walker circulation changes are of the highest priority for a realistic estimate of cloud feedback in actual greenhouse gas increase scenarios.

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Wei-Chyung Wang, William B. Rossow, Mao-Sung Yao, and Marilyn Wolfson

Abstract

We illustrate the potential complexity of the feedback between global mean cloud amount and global mean surface temperature when variations of the vertical cloud distribution are included by studying the behavior of a one-dimensional radiative–convective model with two types of cloud variation: 1) variable cloud cover with constant optical thickness and 2) variable optical thickness with constant cloud cover. The variable parameter is calculated assuming a correlation between cloud amount and precipitation or the vertical flux convergence of latent heat. Since the vertical latent heat flux is taken to be a fraction of the total heat flux, modeled by convective adjustment, we examine the sensitivity of the results to two different critical lapse rates, a constant 6.5 K km−1 lapse rate and a temperature-dependent, moist adiabatic lapse rate. The effects of the vertical structure of climate perturbations on the nature of the cloud feedback are examined using two cases: a 2% increase in the solar constant and a doubling of the atmospheric carbon dioxide concentration. The model results show that changes in the vertical cloud distribution and mean cloud optical thickness can be as important to climate variations as are changes in the total cloud cover. Further the variety and complexity of the feedbacks exhibited even by this simple model suggest that proper determination of cloud feedbacks must include the effects of varying vertical distribution.

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Chuan-Yao Lin, Wan-Chin Chen, Pao-Liang Chang, and Yang-Fan Sheng

Abstract

To evaluate the impacts of the urban heat island (UHI) effect on precipitation over a complex geographic environment in northern Taiwan, the next-generation mesoscale model, the Weather Research and Forecasting (WRF) model, coupled with the Noah land surface model and urban canopy model (UCM), was used to study this issue. Based on a better land use classification derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data (the MODIS case), it has significantly improved simulation results for the accumulation rainfall pattern as compared with the original U.S. Geological Survey (USGS) 25-category land use classification (the USGS case). The precipitation system was found to develop later but stronger in the urban (MODIS) case than in the nonurban (USGS) case. In comparison with the observation by radar, simulation results predicted reasonably well; not only was the rainfall system enhanced downwind of the city over the mountainous area, but it also occurred at the upwind plain area in the MODIS case. The simulation results suggested that the correct land use classification is crucial for urban heat island modeling study. The UHI effect plays an important role in perturbing thermal and dynamic processes; it affects the location of thunderstorms and precipitation over the complex geographic environment in northern Taiwan.

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Anthony D. Del Genio, Jingbo Wu, Audrey B. Wolf, Yonghua Chen, Mao-Sung Yao, and Daehyun Kim

Abstract

Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden–Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

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Dan-Qing Huang, Jian Zhu, Yao-Cun Zhang, Jun Wang, and Xue-Yuan Kuang

Abstract

Spring persistent rainfall (SPR) over southern China has great impact on its society and economics. A remarkable feature of the SPR is high frequency. However, SPR frequency obviously decreases over the period of 1997–2011. In this study, the possible causes have been investigated from the perspective of the individual and concurrent effects of the East Asian subtropical jet (EASJ) and East Asian polar front jet (EAPJ). A close relationship is detected between SPR frequency and EASJ intensity (but not EAPJ intensity). Associated with strong EASJ, abundant water vapor is transported to southern China by the southwesterly flow, which may trigger the SPR. Additionally, frequencies of both strong EASJ and weak EAPJ events are positively correlated with SPR frequency. Further investigation of the concurrent effect indicates a significant positive correlation between the frequencies of SPR and the strong EASJ–weak EAPJ configuration. Associated with this configuration, southwesterly flow strengthens in the lower troposphere, while northerly wind weakens in the upper troposphere. This provides a dynamic and moist condition, as enhanced ascending motion and intensified convergence of abundant water vapor over southern China, which favors the SPR. All analyses suggest that the EASJ may play a dominant role in the SPR occurrence and that the EAPJ may play a modulation role. Finally, a possible mechanism maintaining the strong EASJ–weak EAPJ configuration is proposed. Significant cooling over the northeastern Tibetan Plateau may induce a cyclone anomaly in the upper troposphere, which could result in an accelerating EASJ and a decelerating EAPJ.

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Chao-Lin Wang, Shao-Bo Zhong, Guan-Nan Yao, and Quan-Yi Huang

Abstract

Drought disasters cause great economic losses in China every year, especially in its southwest, and they have had a major influence on economic development, lives, and property. In this study, precipitation and drought hazards were examined for a region covering Yunnan, Guizhou, and Guangxi Provinces to assess the spatial and temporal distribution of different drought hazard grades in this region. Annual precipitation data from 90 meteorological stations in or around the study area were collected and organized for the period of 1964–2013. A spatiotemporal covariance model was calculated and fitted. The Bayesian maximum entropy (BME) method, which considers physical knowledge bases to reduce errors, was used to provide an optimal estimation of annual precipitation. Regional annual precipitation distributions were determined. To analyze the spatiotemporal patterns of the drought hazard, the annual standardized precipitation index was used to measure drought severity. A method that involves space–time scan statistics was used to detect the most likely spatiotemporal clusters of the drought hazards. Test-significance p values for all of the calculated clusters were less than 0.001, indicating a high significance level. The results showed that Yunnan Province was a drought-prone area, especially in its northwest and center, followed by Guizhou Province. In addition, Yunnan and Guizhou Provinces were cluster areas of severe and extreme drought. The most likely cluster year was 1966; it was clustered five times during the study period. In this study, the evolutionary process of drought hazards, including spatiotemporal distribution and spatiotemporal clustering characteristics, was considered. The results may be used to provide support for prevention and mitigation of drought in the study area such as optimizing the distribution of drought-resisting resources, drought monitoring, and evaluating potential drought impacts.

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Dan-Qing Huang, Jian Zhu, Yao-Cun Zhang, and An-Ning Huang

Abstract

To investigate the concurrent impacts of the East Asian polar front jet (EAPJ) and subtropical jet (EASJ) on the summer rainfall over eastern China, positive (strengthened EAPJ with weakened EASJ) and negative (weakened EAPJ with strengthened EASJ) configurations are identified. In the positive configuration, rainfall decreases in the northern part of eastern China and increases in the southern part, vice versa in the negative configuration. The possible mechanisms maintaining the two jet configurations are further proposed from the perspectives of sea surface temperature (SST) and synoptic-scale transient eddy activities (STEA). In the positive configuration, meridional distributed cold–warm SST anomalies over the eastern North Pacific may induce regional circulation and meridional temperature gradient anomalies, which can strengthen the EAPJ and weaken the EASJ. The central Pacific La Niña–like SST anomalies are related with the Arctic vortexlike anomalies in the stratosphere, which may strengthen the EAPJ. Furthermore, the divergence of Eliassen–Palm vectors and the conversion from eddy kinetic energy to mean kinetic energy over the active region of the EAPJ may strengthen the EAPJ, vice versa for the weakened EASJ. In the negative configuration, associated with the warm SST anomalies over the western North Pacific, the enhanced convective activities may lead to a strengthened EASJ via meridional teleconnection. The teleconnection may be intensified by the strengthened easterly vertical shear. Additionally, eastern Pacific La Niña–like SST anomalies may intensify the Walker circulation, which may strengthen the EASJ via the Hadley circulation. The STEA-related anomalies are almost opposite those in the positive configuration, especially for the weakened EAPJ.

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Jun Yang, Weitao Lyu, Ying Ma, Yijun Zhang, Qingyong Li, Wen Yao, and Tianshu Lu

Abstract

The macroscopic characteristics of clouds in the Tibetan Plateau are crucial to understanding the local climatic conditions and their impact on the global climate and water vapor cycle. In this study, the variations of cloud cover and cloud types are analyzed by using total-sky images of two consecutive years in Shigatse, Tibetan Plateau. The results show that the cloud cover in Shigatse presents a distinct seasonal difference that is characterized by low cloud cover in autumn and winter and high cloud cover in summer and spring. July is the month with the largest cloud coverage, and its average cloud cover exceeds 75%. The probability of clouds in the sky is the lowest in November, with an average cloud cover of less than 20%. The diurnal variations of cloud cover in different months also have considerable differences. Specifically, cloud cover is higher in the afternoon than that in the morning in most months, whereas the cloud cover throughout the day varies little from July to September. The dominant cloud types in different months are also not the same. The proportion of clear sky is large in autumn and winter. Stratiform cloud occupies the highest percentage in March, April, July, and August. The probability of emergence of cirrus is highest in May and June. The Shigatse region has clear rainy and dry seasons, and correlation analysis between precipitation and clouds shows that the largest cumulative precipitation, the highest cloud cover, and the highest proportion of stratiform clouds occur simultaneously in July.

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