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Ji-Qin Zhong, Bing Lu, Wei Wang, Cheng-Cheng Huang, and Yang Yang

Abstract

In this study, the causes of the underestimated diurnal 2-m temperature range and the overestimated 2-m specific humidity in the winter of northern China in the Rapid-Refresh Multiscale Analysis and Prediction System–Short Term (RMAPS-ST) are investigated. Three simulations based on RMAPS-ST are conducted from 1 November 2016 to 28 February 2017. Further analyses show that the partitioning of surface upward sensible heat fluxes and downward ground heat fluxes might be the main contributing factor to the 2-m temperature forecast bias. In this study, two simulations are conducted to examine the effect of soil moisture initialization and soil hydraulic property on the 2-m temperature and 2-m specific humidity forecasts. First, the High-Resolution Land Data Assimilation System (HRLDAS) is used to provide an alternative soil moisture initialization. The results show that the drier soil moisture could lead to noticeable change in energy partitioning at the land surface, which in turn results in improved prediction of the diurnal 2-m temperature range, although it also enlarges the 2-m specific humidity bias in some parts of the domain. Second, a soil texture dataset developed by Beijing Normal University and the revised hydraulic parameters are applied to provide a more detailed description of soil properties, which could further improve the 2-m specific humidity bias. In summary, the combination of using optimized soil moisture initialization, an updated soil map, and revised soil hydraulic parameters can help improve the 2-m temperature and 2-m specific humidity prediction in RMAPS-ST.

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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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Liqi Chen, Wei Li, Jianqiong Zhan, Jianjun Wang, Yuanhui Zhang, and Xulin Yang

Abstract

To investigate the concentrations, sources, and temporal variations of atmospheric black carbon (BC) in the summer Arctic, routine ground-level observations of BC by optical absorption were made in the summer from 2005 to 2008 at the Chinese Arctic “Yellow River” Station (78°55′N, 11°56′E) at Ny-Ålesund on the island of Spitsbergen in the Svalbard Archipelago. Methods of the ensemble empirical-mode decomposition analysis and back-trajectory analysis were employed to assess temporal variation embedded in the BC datasets and airmass transport patterns. The 10th-percentile and median values of BC concentrations were 7.2 and 14.6 ng m−3, respectively, and hourly average BC concentrations ranged from 2.5 to 54.6 ng m−3. A gradual increase was found by 4 ng m−3 a−1. This increase was not seen in the Zeppelin Station and it seemed to contrast with the prevalent conception of generally decreasing BC concentration since 1989 in the Arctic. Factors responsible for this increase such as changes in emissions and atmospheric transport were taken into consideration. The result indicated that BC from local emissions was mostly responsible for the observed increase from 2005 to 2008. BC temporal variation in the summer was controlled by the atmospheric circulation, which presented a significant 6–14-day variation and coherent with 1–3- and 2–5-day and longer cycle variation. Although the atmospheric circulation changes from 2005 to 2008, there was not a marked trend in long-range transportation of BC. This study suggested that local emissions might have significant implication for the regional radiative energy balance at Ny-Ålesund.

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Michael R. Riches, Wei-Chyung Wang, Panqin Chen, Shiyan Tao, Shuguang Zhou, and Yihui Ding

This report summarizes the progress since 1991 of two agreements on “global and regional climate change” studies between the U.S. Department of Energy (DOE) and two state agencies of the People's Republic of China. The first agreement is the DOE–Chinese Academy of Science joint project on the “Study of the Greenhouse Effect” and the second agreement is the DOE–China Meteorological Administration joint project on the “Study of Regional Climate.” While development of general circulation climate models and analysis of climate data over China continues, the joint research produced several unique Chinese climate datasets, including the reconstruction of 2000 years of historical climate, quality assured instrumental climate data, and an archive of methane emissions from rice fields in southern China.

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Thomas R. Karl, Wei-Chyung Wang, Michael E. Schlesinger, Richard W. Knight, and David Portman

Abstract

Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.

We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.

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Hainan Gong, Lin Wang, Wen Chen, Renguang Wu, Ke Wei, and Xuefeng Cui

Abstract

In this paper the model outputs from the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) are used to examine the climatology and interannual variability of the East Asian winter monsoon (EAWM). The multimodel ensemble (MME) is able to reproduce reasonably well the circulation features of the EAWM. The simulated surface air temperature still suffers from a cold bias over East Asia, but this bias is reduced compared with CMIP phase 3 models. The intermodel spread is relatively small for the large-scale circulations, but is large for the lower-tropospheric meridional wind and precipitation along the East Asian coast. The interannual variability of the EAWM-related circulations can be captured by most of the models. A general bias is that the simulated variability is slightly weaker than in the observations. Based on a selected dynamic EAWM index, the patterns of the EAWM-related anomalies are well reproduced in MME although the simulated anomalies are slightly weaker than the observations. One general bias is that the northeasterly anomalies over East Asia cannot be captured to the south of 30°N. This bias may arise both from the inadequacies of the EAWM index and from the ability of models to capture the EAWM-related tropical–extratropical interactions. The ENSO–EAWM relationship is then evaluated and about half of the models can successfully capture the observed ENSO–EAWM relationship, including the significant negative correlation between Niño-3.4 and EAWM indices and the anomalous anticyclone (or cyclone) over the northwestern Pacific. The success of these models is attributed to the reasonable simulation of both ENSO’s spatial structure and its strength of interannual variability.

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Xidong Wang, Peter C. Chu, Guijun Han, Wei Li, Xuefeng Zhang, and Dong Li

Abstract

A new, fully conserved minimal adjustment scheme with temperature and salinity (T, S) coherency is presented for eliminating false static instability generated from analyzing and assimilating stable ocean (T, S) profiles data, that is, from generalized averaging over purely observed data (data analysis) or over modeled/observed data (data assimilation). This approach consists of a variational method with (a) fully (heat, salt, and potential energy) conserved conditions, (b) minimal adjustment, and (c) (T, S) coherency. Comparison with three existing schemes (minimal adjustment, conserved minimal adjustment, and convective adjustment) using observational profiles and a simple one-dimensional ocean mixed layer model shows the superiority of this new scheme.

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Fuyao Wang, Yan Yu, Michael Notaro, Jiafu Mao, Xiaoying Shi, and Yaxing Wei

Abstract

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled control run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.

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Christopher A. Davis, David A. Ahijevych, Wei Wang, and William C. Skamarock

Abstract

An evaluation of medium-range forecasts of tropical cyclones (TCs) is performed, covering the eastern North Pacific basin during the period 1 August–3 November 2014. Real-time forecasts from the Model for Prediction Across Scales (MPAS) and operational forecasts from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) are evaluated. A new TC-verification method is introduced that treats TC tracks as objects. The method identifies matching pairs of forecast and observed tracks, missed and false alarm tracks, and derives statistics using a multicategory contingency table methodology. The formalism includes track, intensity, and genesis.

Two configurations of MPAS, a uniform 15-km mesh and a variable-resolution mesh transitioning from 60 km globally to 15 km over the eastern Pacific, are compared with each other and with the operational GFS. The two configurations of MPAS reveal highly similar forecast skill and biases through at least day 7. This result supports the effectiveness of TC prediction using variable resolution.

Both MPAS and the GFS suffer from biases in predictions of genesis at longer time ranges; MPAS produces too many storms whereas the GFS produces too few. MPAS better discriminates hurricanes than does the GFS, but the false alarms in MPAS lower overall forecast skill in the medium range relative to GFS. The biases in MPAS forecasts are traced to errors in the parameterization of shallow convection south of the equator and the resulting erroneous invigoration of the ITCZ over the eastern North Pacific.

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Xiaodong Huang, Zhaoyun Wang, Zhiwei Zhang, Yunchao Yang, Chun Zhou, Qingxuan Yang, Wei Zhao, and Jiwei Tian

Abstract

The role of mesoscale eddies in modulating the semidiurnal internal tide (SIT) in the northern South China Sea (SCS) is examined using the data from a cross-shaped mooring array. From November 2013 to January 2014, an anticyclonic eddy (AE) and cyclonic eddy (CE) pair crossed the westward SIT beam originating in Luzon Strait. Observations showed that, because of the current and stratification modulations by the eddy pair, the propagation speed of the mode-1 SIT sped up (slowed down) by up to 0.7 m s−1 (0.4 m s−1) within the AE’s (CE’s) southern portion. As a result of the spatially varying phase speed, the mode-1 SIT wave crest was clockwise rotated (counterclockwise rotated) within the AE (CE) core, while it exhibited convex and concave (concave and convex) patterns on the southern and northern peripheries of the AE (CE), respectively. In mid-to-late November, most of the mode-1 SIT energy was refracted by the AE away from Dongsha Island toward the north part of the northern SCS, which resulted in enhanced internal solitary waves (ISWs) there. Corresponding to the energy refraction, responses of the depth-integrated mode-1 SIT energy to the eddies were generally in phase at the along-beam-direction moorings but out of phase in the south and north parts of the northern SCS at the cross-beam-direction moorings. From late December to early January, intensified mode-2 SIT was observed, whose energy was likely transferred from the mode-1 SIT through eddy–wave interactions. The observation results reported here are helpful to improve the capability to predict internal tides and ISWs in the northern SCS.

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