37 research outputs found

    Nondimensional Wind and Temperature Profiles in the Atmospheric Surface Layer over the Hinterland of the Taklimakan Desert in China

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    Observed turbulent fluxes, wind, and temperature profiles at Tazhong station over the hinterland of the Taklimakan Desert in China have been analyzed to evaluate empirical parameters used in the profile functions of desert surface layer. The von Kármán constant derived from our observations is about 0.396 in near-neutral stratification, which is in good agreement with many other studies for different underlying surface. In our analysis, the turbulent Prandtl number is about 0.75 in near-neutral conditions. For unstable range, the nondimensional wind and temperature profile functions are best fitted by the exponents of −1/4 and −1/2, respectively. The linear relations still hold for stable stratification in this extremely arid desert. However, the parameters used in their profile functions need to be revised to be applicable for desert surfaces

    Analyses of temperature and humidity profiles and heat balance of the surface boundary-layer in the hinterland of the Taklimakan Desert

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    The daily variation regularities of micro-meteorological features, such as the surface layer temperature and humidity profiles of the inner desert in summer, the temperature of sand bed, the radiation of the earth's surface and the heat balance, were analyzed by combination method and logarithm regression according to the data obtained from the Atmospheric Environmental Observation Station of Taklimakan Desert in July-August of 2006 and 2007. It has been shown that temperature inversion occurred near the surface layer at night in summer, the temperature increased with the height within a certain altitude range, and the reverse was true during the daytime. The ground surface radiation balance of the Taklimakan Desert was mainly positive; other radiation components (the global radiation, the reflective radiation, the ground upward long wave radiation and the net radiation) exhibited daily variation characteristics evidently and showed normal diurnal cycle, except for the downward atmospheric long-wave radiation. The heat exchange of the surface layer of the desert was dominated by turbulence sensible heat, and only a small portion of heat was transferred to the atmospheric surface layer in the form of latent heat. The surface sensible heat and latent heat changed with the increase and decrease of sun elevation angle, with maximum of the latent heat appearing in wee hours and the peak value of the sensible heat appearing at noon. Observation and analysis showed that heating effect of the underlying surface of the desert was great on the aerosphere; the surface was a high heat source during the day and became a weak cold source at night

    Improving Forecast Accuracy with an Auto Machine Learning Post-Correction Technique in Northern Xinjiang

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    Reliable meteorological forecasts of temperature and relative humidity are critically important to take necessary measures to avoid potential damage and losses. An operational meteorological forecast model based on the Weather Research and Forecast (WRF) model has been built in Xinjiang. Numerical forecasts usually have significant uncertainties and errors due to imperfections in models themselves. In this study, a straightforward automated machine learning (AutoML) approach has been developed to post-process the raw forecasts of the WRF model. The method was implemented and evaluated to post-process forecasts from 13 stations in northern Xinjiang. The post-processed temperature forecasts were significantly improved from the raw forecasts, with average RMSE values in the 13 stations decreasing from 3.24 °C to 2.34 °C by a large margin of 28%. As for relative humidity, the mean RMSE at 13 stations decreased from 19.54% to 11.54%, or it showed a percentage decrease of 41%. Meanwhile, biases were also significantly decreased, with average ME values being reduced from around 2 °C to ~0.33 °C for temperature and improved from −15.6% to ~0% for relative humidity. Moreover, forecast performance values after post-correction became much closer to each other than raw forecast performance values, improving forecast applicability at regional scales

    The Radial Growth of Schrenk Spruce (Picea schrenkiana Fisch. et Mey.) Records the Hydroclimatic Changes in the Chu River Basin over the Past 175 Years

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    The Chu River is one of the most important rivers in arid Central Asia. Its discharge is affected by climate change. Here, we establish a tree-ring chronology for the upper Chu River Basin and analyze the relationships between radial growth, climate, and discharge. The results show that the radial growth of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) is controlled by moisture. We also reconstruct a 175-year standardized precipitation-evapotranspiration index (SPEI) for the Chu River Basin. A comparison of the reconstructed and observed indices reveal that 39.5% of the variance occurred during the calibration period of 1952–2014. The SPEI reconstruction and discharge variability of the Chu River show consistent long-term change. They also show that the Chu River Basin became increasingly dry between the 1840s and the 1960s, with a significant drought during the 1970s. A long and rapid wetting period occurred between the 1970s and the 2000s, and was followed by increasing drought since 2004. The change in the SPEI in the Chu River Basin is consistent with records of long-term precipitation, SPEI and Palmer Drought Severity Indices (PDSI) in other proximate regions of the western Tianshan Mountains. The hydroclimatic change of the Chu River Basin may be associated with westerly wind. This study is helpful for disaster prevention and water resource management in arid central Asia

    Physical Mechanisms of Deep Convective Boundary Layer Leading to Dust Emission in the Taklimakan Desert

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    Abstract Deserts play an important role in the climate system, which is closely associated with the emission and transport of dust aerosols. Based on the intensive observation experiment in the Taklimakan Desert, the potential physical processes between the deep convective boundary layer (CBL) and dust emission are revealed in this study. Deep CBL enables the formation of clouds in the late afternoon, leading to significant cooling of surface. Large‐scale buoyant coherent structures thereby transform into the mechanical coherent structures confined near the surface. The responses promote the earlier occurrence of low‐level jet (LLJ) than in cloudless conditions, which allows the downward transport of LLJ momentum and substantially increases surface wind. Therefore, dust emission is initiated by strong wind at dusk and lasts for several hours. The results are useful to predict dust emissions and improve our understanding of distinctive boundary‐layer processes in desert regions

    Evaluation of CAMEL over the Taklimakan Desert Using Field Observations

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    Infrared (IR) land surface emissivity (LSE) plays an important role in numerical weather prediction (NWP) models through the satellite radiance assimilation. However, due to the large uncertainties in LSE over the desert, many land-surface sensitive channels of satellite IR sensors are not assimilated. This calls for further assessments of the quality of satellite-retrieved LSE in these desert regions. A set of LSE observations were made from field experiments conducted on 16–18 October 2013 along a south/north desert road in the Taklimakan Desert (TD), China. The observed LSEs (EOBS) are thus used in this study as the reference values to evaluate the quality of Combined ASTER MODIS Emissivity over Land (CAMEL) data. Analysis of these data shows four main results. First, the CAMEL datasets appear to sufficiently capture the spatial variations in LSE from the oasis to the hinterland of the TD (this is especially the case in the quartz reststrahlen band). From site 1 at the southern edge of the Taklimakan Desert to site 10 at the northern edge, the measured LSE and the corresponding CAMEL observation in the quartz reststrahlen band first decrease and reach their minimum around sites 4–6 in the hinterland of the Taklimakan Desert. Then, the LSE increases gradually and finally reaches its maximum at site 10, which has a clay ground surface, showing that the LSE is higher at the edges of the desert and lower in the center. Second, the CAMEL values at 11.3 μm have a zonal distribution characterized by a northeast–southwest strike, though such an artifact might have been introduced by ASTER LSE data during the merging process that created the CAMEL dataset. Third, the unrealistic variation of the original EOBS can be filtered out with useful signals, as identified by the first six principal components of the PCA conducted on the laboratory-measured hyperspectral emissivity spectra (ELAB). Fourth, the CAMEL results correlate well with the measured LSE at the 10 observation sites, with the observed LSE being slightly smaller than the CAMEL values in general

    Seasonal Variations of the Near-Surface Atmospheric Boundary Layer Structure in China’s Gurbantünggüt Desert

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    As the largest fixed and semifixed desert in China, the Gurbantünggüt Desert has a longperiod of snow in winter and the rapid growth of ephemeral plants in spring, presentingthe obvious seasonal changes in the underlying desert surface type, which could lead to the significantvariety in the near-surface boundary layer over this desert. To clarify the influence of the underlying surface change on the near-surface atmospheric boundary layer, gradient tower data and Eddy covariance data in 2017 were analyzed. The results were as follows: the wind profile can be divided into the nocturnal stable boundary layer and the daytime unstable boundary in spring, summer, and autumn, while the wind profile dominating nighttime stability in winter. During the study period, the four-season temperature profiles can be divided into four types: night radiation type, morning transition type, daylight solar radiation type, and evening transition type, and the temperature difference between spring and summer is more than that of autumn and winter. The vertical temperature lapse rate can reach 4.5°C/100 m in spring and summer, while the vertical temperature lapse rate is 0.5°C/100 m in winter. The special humidity value in summer and spring is greater than autumn and winter. The profile is almost in the inverse humidity state at almost all periods in winter. The inverse humidity phenomenon occurred on the autumn night. Besides, the specific humidity is closely related to the temperature and the near-surface wind speed. The “rapid change” of the underlying surface of the spring desert region affects the surface energy budget, which affects the turbulent energy and the stability of the near-surface layer, thus affecting the changes in temperature, humidity, and wind profile
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