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Xiaoyan Wang and Renhe Zhang
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Xiaoyan Wang and Renhe Zhang
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Qingnong Xiao, Liqiang Chen, and Xiaoyan Zhang

Abstract

A tropical cyclone bogus data assimilation (BDA) scheme is built in the Weather Research and Forecasting three-dimensional variational data assimilation system (WRF 3D-VAR). Experiments were conducted (21 experiments with BDA in parallel with another 21 without BDA) to assess its impacts on the predictions of seven Atlantic Ocean basin hurricanes observed in 2004 (Charley, Frances, Ivan, and Jeanne) and in 2005 (Katrina, Rita, and Wilma). In addition, its performance was compared with the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane initialization scheme in a case study of Hurricane Humberto (2007). It is indicated that hurricane initialization with the BDA technique can improve the forecast skills of track and intensity in the Advanced Research WRF (ARW). Among the three hurricane verification parameters [track, central sea level pressure (CSLP), and maximum surface wind (MSW)], BDA improves CSLP the most. The improvement of MSW is also considerable. The track has the smallest, but still noticeable, improvement. With WRF 3D-VAR, the initial vortex produced by BDA is balanced with the dynamical and statistical balance in the 3D-VAR system. It has great potential for improving the hurricane intensity forecast. The case study on Hurricane Humberto (2007) shows that BDA performs better than the GFDL bogus scheme in the ARW forecast for the case. Better definition of the initial vortex is the main reason for the advanced skill in hurricane track and intensity forecasting in this case.

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Xiaoyan Zhang, Qingnong Xiao, and Patrick J. Fitzpatrick

Abstract

Numerical experiments have been conducted to examine the impact of multisatellite data on the initialization and forecast of the rapid weakening of Hurricane Lili (in 2002) from 0000 UTC to landfall in Louisiana on 1300 UTC 3 October 2002. Fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) 4DVAR sensitivity runs were conducted separately with QuikSCAT surface winds, the Geostationary Operational Environmental Satellite-8 (GOES-8) cloud drift–water vapor winds, and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) temperature–dewpoint sounding data to investigate their individual impact on storm track and intensity. The results were compared against a simulation initialized from a Global Forecast System background interpolated to the MM5 grid. Assimilating QuikSCAT surface wind data improves the analyzed outer-core surface winds, as well as the inner-core low-level temperature and moisture fields. Substantial adjustments of winds are noted on the periphery of the hurricane by assimilating GOES-8 satellite-derived upper-level winds. Both track forecasts initialized at 1200 UTC 2 October 2002 with four-dimensional variational data assimilation (4DVAR) of QuikSCAT and GOES-8 show improvement compared to those initialized with the model background. Assimilating Aqua MODIS sounding data improves the outer-core thermodynamic features. The Aqua MODIS data has a slight impact on the track forecast, but more importantly shows evidence of impacting the model intensity predicting by retarding the incorrect prediction of intensification. All three experiments also show that bogusing of an inner-core wind vortex is required to depict the storm’s initial intensity.

To properly investigate Lili’s weakening, data assimilation experiments that incorporate bogusing vortex, QuikSCAT winds, GOES-8 winds, and Aqua MODIS sounding data were performed. The 4DVAR satellite-bogus data assimilation is conducted in two consecutive 6-h windows preceding Lili’s weakening. Comparisons of the results between the experiments with and without satellite data indicated that the satellite data, particularly the Aqua MODIS sounding information, makes an immediate impact on the hurricane intensity change beyond normal bogusing procedures. The track forecast with the satellite data is also more accurate than just using bogusing alone. This study suggests that dry air intrusion played an important role in Lili’s rapid weakening. It also demonstrates the potential benefit of using satellite data in a 4DVAR context—particularly high-resolution soundings—on unusual cases like Hurricane Lili.

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Feng Gao, Xiaoyan Zhang, Neil A. Jacobs, Xiang-Yu Huang, Xin Zhang, and Peter P. Childs

Abstract

Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observations are becoming a major data source for numerical weather prediction (NWP) because of the advantages of their high spatiotemporal resolution and humidity measurements. In this study, the estimation of TAMDAR observational errors, and the impacts of TAMDAR observations with new error statistics on short-term forecasts are presented. The observational errors are estimated by a three-way collocated statistical comparison. This method employs collocated meteorological reports from three data sources: TAMDAR, radiosondes, and the 6-h forecast from a Weather Research and Forecasting Model (WRF). The performance of TAMDAR observations with the new error statistics was then evaluated based on this model, and the WRF Data Assimilation (WRFDA) three-dimensional variational data assimilation (3DVAR) system. The analysis was conducted for both January and June of 2010. The experiments assimilate TAMDAR, as well as other conventional data with the exception of non-TAMDAR aircraft observations, every 6 h, and a 24-h forecast is produced. The standard deviation of the observational error of TAMDAR, which has relatively stable values regardless of season, is comparable to radiosondes for temperature, and slightly smaller than that of a radiosonde for relative humidity. The observational errors in wind direction significantly depend on wind speeds. In general, at low wind speeds, the error in TAMDAR is greater than that of radiosondes; however, the opposite is true for higher wind speeds. The impact of TAMDAR observations on both the 6- and 24-h WRF forecasts during the studied period is positive when using the default observational aircraft weather report (AIREP) error statistics. The new TAMDAR error statistics presented here bring additional improvement over the default error.

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Byoung-Joo Jung, Hyun Mee Kim, Thomas Auligné, Xin Zhang, Xiaoyan Zhang, and Xiang-Yu Huang

Abstract

An increasing number of observations have contributed to the performance of numerical weather prediction systems. Accordingly, it is important to evaluate the impact of these observations on forecast accuracy. While the observing system experiment (OSE) requires considerable computational resources, the adjoint-derived method can evaluate the impact of all observational components at a lower cost. In this study, the effect of observations on forecasts is evaluated by the adjoint-derived method using the Weather Research and Forecasting Model, its adjoint model, and a corresponding three-dimensional variational data assimilation system in East Asia and the western North Pacific for the 2008 typhoon season. Radiance observations had the greatest total impact on forecasts, but conventional wind observations had the greatest impact per observation. For each observation type, the total impact was greatest for radiosonde and each Advanced Microwave Sounding Unit (AMSU)-A satellite, followed by surface synoptic observation from a land station (SYNOP), Quick Scatterometer (QuikSCAT), atmospheric motion vector (AMV) wind from a geostationary satellite (GEOAMV), and aviation routine weather reports (METARs). The fraction of beneficial observations was approximately 60%–70%, which is higher than that reported in previous studies. For several analyses of Typhoons Sinlaku (200813) and Jangmi (200815), dropsonde soundings taken near the typhoon had similar or greater observation impacts than routine radiosonde soundings. The sensitivity to the error covariance parameter indicates that reducing (increasing) observation (background) error covariance helps to reduce forecast error in the current analysis framework. The observation impact from OSEs is qualitatively similar to that from the adjoint method for major observation types. This study confirms that radiosonde observations provide primary information on the atmospheric state as in situ observations and that satellite radiances are an essential component of atmospheric observation systems.

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Qingnong Xiao, Xiaoyan Zhang, Christopher Davis, John Tuttle, Greg Holland, and Patrick J. Fitzpatrick

Abstract

Initialization of the hurricane vortex in weather prediction models is vital to intensity forecasts out to at least 48 h. Airborne Doppler radar (ADR) data have sufficiently high horizontal and vertical resolution to resolve the hurricane vortex and its imbedded structures but have not been extensively used in hurricane initialization. Using the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation (3DVAR) system, the ADR data are assimilated to recover the hurricane vortex dynamic and thermodynamic structures at the WRF model initial time. The impact of the ADR data on three hurricanes, Jeanne (2004), Katrina (2005) and Rita (2005), are examined during their rapid intensification and subsequent weakening periods before landfall.

With the ADR wind data assimilated, the three-dimensional winds in the hurricane vortex become stronger and the maximum 10-m winds agree better with independent estimates from best-track data than without ADR data assimilation. Through the multivariate incremental structure in WRF 3DVAR analysis, the central sea level pressures (CSLPs) for the three hurricanes are lower in response to the stronger vortex at initialization. The size and inner-core structure of each vortex are adjusted closer to observations of these attributes. Addition of reflectivity data in assimilation produces cloud water and rainwater analyses in the initial vortex. The temperature and moisture are also better represented in the hurricane initialization.

Forty-eight-hour forecasts are conducted to evaluate the impact of ADR data using the Advanced Research Hurricane WRF (AHW), a derivative of the Advanced Research WRF (ARW) model. Assimilation of ADR data improves the hurricane-intensity forecasts. Vortex asymmetries, size, and rainbands are also simulated better. Hurricane initialization with ADR data is quite promising toward reducing intensity forecast errors at modest computational expense.

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Huawu Wu, Cicheng Zhang, Xiao-Yan Li, Congsheng Fu, Haohao Wu, Pei Wang, and Jinzhao Liu

Abstract

The northeastern Tibetan Plateau is located in a climatic junction, which is considered an ideal region to explore the interactions between the summer monsoons and the westerly circulation patterns. However, to date, the needed long-term precipitation-based isotopic dataset is too limited to predict the interactions and patterns. This paper presents an evaluation of hydrometeorological processes and climate dynamics in the northeastern Tibetan Plateau based on a 7-yr precipitation isotope dataset covering the summer monsoon periods from 2012 to 2018. Results illustrated remarkable seasonal isotopic variability, characterized by lower δ 18O and δ 2H values in June with an average of −10‰ and −66.7‰, respectively. Higher δ 18O and δ 2H values in July averaged −6.7‰ and −39.5‰, respectively. This clear isotopic variability is largely related to seasonal changes of moisture sources and hydrometeorological processes. These precipitation isotopic values were primarily determined by the amount of precipitation, relative humidity, and convective activity, but showed no correlation with air temperature. Backward trajectory model results showed that Xinjiang, northern China, the Arctic, central Asia, and the South China Sea (SCS) were the primary sources of precipitation for the study site with varying seasonal contributions. The maritime moisture source of the SCS primarily resulted in the lowest precipitation δ 18O values during the prevailing summer monsoon, which is mainly as a result of the strong convective activity and rainout processes along the air trajectory. The higher average deuterium excess (d-excess) value of precipitation in September indicated continental sources from central Asia (e.g., 75.4%) as land vapor recycling increases d-excess concentration in the atmosphere. These findings provide further insights into the main factors of precipitation isotopic variability related to atmospheric processes along the trajectory and the relevant factors in the monsoon regions.

Significance Statement

Recently, scientists and policy makers have become aware that Tibetan hydroclimate variability provides evidence of changes in regional and global circulation patterns that may result in the intensification of climate-driven extremes. However, these studies largely depend on crucial paleoclimate records of past precipitation isotopes in monsoon regions, which contain great uncertainties because of the complex relationship between climatic variability and precipitation isotopes. This study first presented a 7-yr isotopic dataset to understand the hydrological processes and climate dynamics controlling the isotopic variability in the northeastern Tibetan Plateau. The findings reveal important factors on the isotopic variability associated with atmospheric processes and their key climatic variables, which can enhance our interpretation of the paleoclimate records in monsoon regions.

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Xiaoyan Zhang, Jianping Huang, Gang Li, Yongwei Wang, Cheng Liu, Kaihui Zhao, Xinyu Tao, Xiao-Ming Hu, and Xuhui Lee

Abstract

The Weather Research and Forecasting (WRF) Model is used in large-eddy simulation (LES) mode to investigate a lake-breeze case occurring on 12 June 2012 over the Lake Taihu region of China. Observational data from 15 locations, wind profiler radar, and the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to evaluate the WRF nested-LES performance in simulating lake breezes. Results indicate that the simulated temporal and spatial variations of the lake breeze by WRF nested LES are consistent with observations. The simulations with high-resolution grid spacing and the LES scheme have a high correlation coefficient and low mean bias when evaluated against 2-m temperature, 10-m wind, and horizontal and vertical lake-breeze circulations. The atmospheric boundary layer (ABL) remains stable over the lake throughout the lake-breeze event, and the stability becomes even stronger as the lake breeze reaches its mature stage. The improved ABL simulation with LES at a grid spacing of 150 m indicates that the non-LES planetary boundary layer parameterization scheme does not adequately represent subgrid-scale turbulent motions. Running WRF fully coupled to a lake model improves lake-surface temperature and consequently the lake-breeze simulations. Allowing for additional model spinup results in a positive impact on lake-surface temperature prediction but is a heavy computational burden. Refinement of a water-property parameter used in the Community Land Model, version 4.5, within WRF and constraining the lake-surface temperature with observational data would further improve lake-breeze representation.

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Xiaoyan Sun, Yali Luo, Xiaoyu Gao, Mengwen Wu, Mingxin Li, Ling Huang, Da-Lin Zhang, and Haiming Xu

Abstract

In this study, high-resolution surface and radar observations are used to analyze 24 localized extreme hourly rainfall (EXHR; >60 mm h−1) events with strong urban heat island (UHI) effects over the Great Bay Area (GBA) in South China during the 2011–16 warm seasons. Quasi-idealized, convection-permitting ensemble simulations driven by diurnally varying lateral boundary conditions, which are extracted from the composite global analysis of 3–5 June 2013, are then conducted with a multilayer urban canopy model to unravel the influences of the UHI and various surface properties nearby on the EXHR generation in a complex geographical environment with sea–land contrast, topography, and vegetation variation. Results show that EXHR is mostly distributed over the urban agglomeration and within about 40 km on its downwind side, and produced during the afternoon-to-evening hours by short-lived meso-γ- to meso-β-scale storms. On the EXHR days, the GBA is featured by a weak gradient environment with abundant moisture, and a weak southwesterly flow prevailing in the boundary layer (BL). The UHI effects lead to the development of a deep mixed layer with “warm bubbles” over the urban agglomeration, in which the lower-BL convergence and BL-top divergence is developed, assisting in convective initiation. Such urban BL processes and associated convective development with moisture supply by the synoptic low-level southwesterly flow are enhanced by orographically increased horizontal winds and sea breezes under the influence of the herringbone coastline, thereby increasing the inhomogeneity and intensity of rainfall production over the “Π-shaped” urban clusters. Vegetation variations are not found to be an important factor in determining the EXHR production over the region.

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