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Guoqing Ge, Jidong Gao, and Ming Xue

Abstract

A diagnostic pressure equation is incorporated into a storm-scale three-dimensional variational data assimilation (3DVAR) system in the form of a weak constraint in addition to a mass continuity equation constraint (MCEC). The goal of this diagnostic pressure equation constraint (DPEC) is to couple different model variables to help build a more dynamic consistent analysis, and therefore improve the data assimilation results and subsequent forecasts. Observational System Simulation Experiments (OSSEs) are first performed to examine the impact of the pressure equation constraint on storm-scale radar data assimilation using an idealized tornadic thunderstorm simulation. The impact of MCEC is also investigated relative to that of DPEC. It is shown that DPEC can improve the data assimilation results slightly after a given period of data assimilation. Including both DPEC and MCEC yields the best data assimilation results. Sensitivity tests show that MCEC is not very sensitive to the choice of its weighting coefficients in the cost function, while DPEC is more sensitive and its weight should be carefully chosen. The updated 3DVAR system with DPEC is further applied to the 5 May 2007 Greensburg, Kansas, tornadic supercell storm case assimilating real radar data. It is shown that the use of DPEC can speed up the spinup of precipitation during the intermittent data assimilation process and also improve the follow-on forecast in terms of the general evolution of storm cells and mesocyclone rotation near the time of observed tornado.

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Guoqing Ge, Jidong Gao, and Ming Xue

Abstract

This paper investigates the impacts of assimilating measurements of different state variables, which can be potentially available from various observational platforms, on the cycled analysis and short-range forecast of supercell thunderstorms by performing a set of observing system simulation experiments (OSSEs) using a storm-scale three-dimensional variational data assimilation (3DVAR) method. The control experiments assimilate measurements every 5 min for 90 min. It is found that the assimilation of horizontal wind can reconstruct the storm structure rather accurately. The assimilation of vertical velocity , potential temperature , or water vapor can partially rebuild the thermodynamic and precipitation fields but poorly retrieves the wind fields. The assimilation of rainwater mixing ratio can build up the precipitation fields together with a reasonable cold pool but is unable to properly recover the wind fields. Overall, data have the greatest impact, while have the second largest impact. The impact of is the smallest. The impact of assimilation frequency is examined by comparing results using 1-, 5-, or 10-min assimilation intervals. When is assimilated every 5 or 10 min, the analysis quality can be further improved by the incorporation of additional types of observations. When are assimilated every minute, the benefit from additional types of observations is negligible, except for . It is also found that for , , and measurements, more frequent assimilation leads to more accurate analyses. For and , a 1-min assimilation interval does not produce a better analysis than a 5-min interval.

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Xuan Wang, Romain Husson, Haoyu Jiang, Ge Chen, and Guoping Gao

Abstract

Wave measurements retrieved by Sentinel-1A level-2 ocean (OCN) products are sensitive to swells other than wind seas, and are considered to provide a finer resolution of ocean swells. To assess the capability of swell retrieval globally, OCN products are validated against WAVEWATCH III (WW3) wave spectra for two available incidence angles [“wave mode” (WV); WV1: 23°; WV2: 36°], focused on the integral wave parameters and most energetic wave system of Sentinel-1A. The wave parameter difference between Sentinel-1A and WW3 along antenna look angles for WV1 demonstrates the obvious impact of the nonlinearity influence in the azimuth direction, resulting in an unrealistically high wave height at the low wave frequency, and the spurious split of wave systems in the range direction, due to the vanishing of velocity bunching modulation. WV2 is less pronounced in these two aspects, but tends to shift wave energy to a higher wave frequency in the range direction. The inside discrepancy of wave energy has two noticeable features: the difference in peak wavelengths in the wave spectrum is positively clustered in the azimuth direction and negatively clustered in the range direction; some of the most energetic partitions derived from Sentinel-1A are difficult to assign to any wave systems in WW3. This phenomenon could be related to wind-wave coupling as the azimuth cutoff/WW3 peak wavelength is confined to a ratio below 0.5 for the negative difference between Sentinel-1A and WW3 peak wavelengths and the spectral distance of most energetic wave system in Sentinel-1A highly resembles “swell pools.”

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Guoqing Ge, Jidong Gao, Keith Brewster, and Ming Xue

Abstract

The radar ray path and beam broadening equations are important for assimilation of radar data into numerical weather prediction (NWP) models. They can be used to determine the physical location of each radar measurement and to properly map the atmospheric state variables from the model grid to the radar measurement space as part of the forward observation operators. Historically, different degrees of approximations have been made with these equations; however, no systematic evaluation of their impact exists, at least in the context of variational data assimilation. This study examines the effects of simplifying ray path and ray broadening calculations on the radar data assimilation in a 3D variational data assimilation (3DVAR) system. Several groups of Observational System Simulation Experiments (OSSEs) are performed to test the impact of these equations to radar data assimilation with an idealized tornadic thunderstorm case. This study shows that the errors caused by simplifications vary with the distance between the analyzed storm and the radar. For single time level wind analysis, as the surface range increases, the impact of beam broadening on analyzed wind field becomes evident and can cause relatively large error for distances beyond 150 km. The impact of the earth’s curvature is more significant, even for distances beyond 60 km, because it places the data at the wrong vertical location. The impact of refractive index gradient is also tested. It is shown that the variations of refractive index gradient have a very small impact on the wind analysis results.

Two time series of 1-h-long data assimilation experiments are further conducted to illustrate the impact of the beam broadening and earth curvature on all retrieved model variables. It is shown that all model variables can be retrieved to some degrees in all data assimilation experiments. Similar to the wind analysis experiments, the impacts of both factors are not obvious when radars are relatively close to the storm. When the radars are far from the storm (especially beyond 150 km), overlooking beam broadening degrades the accuracy of assimilation results slightly, whereas ignoring the earth’s curvature leads to significant errors.

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Guoyu Ren, Hongbin Liu, Ziying Chu, Li Zhang, Xiang Li, Weijing Li, Yu Chen, Ge Gao, and Yan Zhang

Abstract

Middle and eastern routes of the South–North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°–42°N and 110°–122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50–100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness–wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160–170- and 70–80-yr oscillations in the north, and 100–150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997–2003 in the north, and the operation and management of the project in the future will also be influenced by climate change—in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP.

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Guoyu Ren, Hongbin Liu, Ziying Chu, Li Zhang, Xiang Li, Weijing Li, Yu Chen, Ge Gao, and Yan Zhang
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Shanlei Sun, Haishan Chen, Ge Sun, Weimin Ju, Guojie Wang, Xing Li, Guixia Yan, Chujie Gao, Jin Huang, Fangmin Zhang, Siguang Zhu, and Wenjian Hua

Abstract

This study investigated monthly and annual reference evapotranspiration changes over southwestern China (SWC) from 1960 to 2012, using the Food and Agriculture Organization of the United Nations’ report 56 (FAO-56) Penman–Monteith equation and routine meteorological observations at 269 weather sites. During 1960–2012, the monthly and annual decreased at most sites. Moreover, the SWC regional average trend in annual was significantly negative (p < 0.05); this trend was the same in most months. A new separation method using several numerical experiments was proposed to quantify each driving factor’s contribution to changes and exhibited higher accuracy based on several validation criteria, after which an attribution analysis was performed. Across SWC, the declining annual was mainly due to decreased net radiation (RN). Spatially, the annual changes at most sites in eastern SWC (excluding southeastern West Guangxi) were generally due to RN, whereas wind speed (WND) or vapor pressure deficit (VPD) was the determinant at other sites. Nevertheless, the determinants differed among 12 months. For the whole SWC, increased VPD in February and decreased WND in April, May, and October were the determinant of decreased ; however, decreased RN was the determinant in other months. Overall, the determinant of the monthly changes exhibited a complex spatial pattern. A complete analysis of changes and the related physical mechanisms in SWC is necessary to better understand hydroclimatological extremes (e.g., droughts) and to develop appropriate strategies to sustain regional development (e.g., water resources and agriculture). Importantly, this separation method provides new perspective for quantitative attribution analyses and thus may be implemented in various scientific fields (e.g., climatology and hydrology).

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