Abstract

Cloud detection is a basic research for achieving cloud-cover state and other cloud characteristics. Because of the influence of sunlight, the brightness of sky background on the ground-based cloud image is usually nonuniform, which increases the difficulty for cirrus cloud detection, and few detection methods perform well for thin cirrus clouds. This paper presents an effective background estimation method to eliminate the influence of variable illumination conditions and proposes a background subtraction adaptive threshold method (BSAT) to detect cirrus clouds in visible images for the small field of view and mixed clear–cloud scenes. The BSAT algorithm consists of red-to-blue band operation, background subtraction, adaptive threshold selection, and binarization. The experimental results show that the BSAT algorithm is robust for all types of cirrus clouds, and the quantitative evaluation results demonstrate that the BSAT algorithm outperforms the fixed threshold (FT) and adaptive threshold (AT) methods in cirrus cloud detection.

Abstract

A heavy rainfall event during the Taiwan Area Mesoscale Experiment intensive observing period 13 has been studied using upper-air, surface mesonet, and dual-Doppler radar data. The heavy rainfall (≥231 mm day⁻¹) occurred over northwestern Taiwan with the maximum rainfall along the northwestern coast and was caused by a long-lived, convective rainband in the prefrontal atmosphere. It occurred in an upper-level divergence region and along the axis of the maximum equivalent potential temperature at the 850-hPa level.

As a Mei-Yu front advanced southeastward, the postfrontal cold air in the lowest levels was retarded by the hilly terrain along the southeastern China coast. As a result, a low-level wind-shift line associated with a pressure trough at the 850-hPa level moved over the Taiwan Strait before the arrival of the surface front. The westerly flow behind the trough interacted with a barrier jet along the northwestern coast of Taiwan. The barrier jet is caused by the interaction between the prefrontal southwest monsoon flow and the island obstacle. A low-level convergence zone (∼3 km deep) was observed along the wind-shift line between the westerly flow coming off the southeastern China coast and the barrier jet. A long-lived rainband developed within the low-level convergence zone and moved southeastward toward the northwestern Taiwan coast with the wind-shift line.

There were several long-lived (>2 h) reflectivity maxima embedded in the rainband. They often had several individual cells with a much shorter lifetime. The reflectivity maxima formed on the southwestern tip of the rainband and along the low-level wind-shift line. They intensified during their movement from the southwest to the northeast along the rainband. The continuous generation of the reflectivity maxima along the wind-shift line and the intensification of them over the low-level convergence zone maintained the long lifetime of the rainband and produced persistent heavy rainfall along the northwestern coast as these reflectivity maxima moved toward the coast. During the early stage of their lifetime, the reflectivity maxima were observed along the wind-shift line with upward motion in the lower troposphere. As they moved toward the northeastern part of the rainband and matured, the reflectivity maxima were observed southeast of the convergence zone with sinking motion in the lower troposphere. The upward motion was rooted along the wind-shift line and tilted southeastward with height. The reflectivity maxima dissipated as they moved inland. During the early stage of the rainband, the reflectivity maxima on the northeastern part of the rainband also merged with the convective line associated with the land-breeze front offshore of the northwestern coast.

The Mei-Yu front was shallow (<1 km) and moved slowly southward along the western coast. Convection associated with the front was weak with echo tops (∼10 dBZ) below 6 km.

Abstract

Precipitation is one of the most important meteorological factors affecting the water cycle and ecological system over the Source Region of the Three Rivers (SRTR), where the Yangtze River, Yellow River, and Lantsang River originate. The characteristics of annual and summer water vapor transport and budget over the SRTR are analyzed using monthly observational and reanalysis datasets during 1980–2019. The linkage between water vapor transport and summer precipitation is also explored in this study. The results show that the Global Precipitation Climatology Project (GPCP) data are in agreement with the measured precipitation. The SRTR is a sink region for water vapor, where the water vapor content shows an increasing trend with a rate of 0.2 mm (10 yr)⁻¹ annually and 0.3 mm (10 yr)⁻¹ in the summer. The water vapor mainly flows into the SRTR from the lower (521.2 × 10⁶ kg s⁻¹) and the middle (195.7 × 10⁶ kg s⁻¹) layers of the southern boundary in summer, while it exports from the middle (208.1 × 10⁶ kg s⁻¹) layer of the eastern boundary. The abnormal wind convergence and the low pressure system, combined with the effects of the western Pacific subtropical high and the Mongolian high, provide conditions for the transport of water vapor and precipitation over the SRTR. A close relationship is found between water vapor flux and precipitation from the singular value decomposition (SVD) analysis. The Brahmaputra River basin is the key region of water vapor transport over the SRTR, which contributes to further understanding the mechanisms of water vapor transport and the regional water cycle.

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.

Abstract

The Hurricane Weather Research and Forecasting (HWRF) system was used in an idealized framework to gain a fundamental understanding of the variability in tropical cyclone (TC) structure and intensity prediction that may arise due to vertical diffusion. The modeling system uses the Medium-Range Forecast parameterization scheme. Flight-level data collected by a NOAA WP-3D research aircraft during the eyewall penetration of category 5 Hurricane Hugo (1989) at an altitude of about 450–500 m and Hurricane Allen (1980) were used as the basis to best match the modeled eddy diffusivities with wind speed. While reduction of the eddy diffusivity to a quarter of its original value produced the best match with the observations, such a reduction revealed a significant decrease in the height of the inflow layer as well which, in turn, drastically affected the size and intensity changes in the modeled TC. The cross-isobaric flow (inflow) was observed to be stronger with the decrease in the inflow depth. Stronger inflow not only increased the spin of the storm, enhancing the generalized Coriolis term in the equations of motion for tangential velocity, but also resulted in enhanced equivalent potential temperature in the boundary layer, a stronger and warmer core, and, subsequently, a stronger storm. More importantly, rapid acceleration of the inflow not only produced a stronger outflow at the top of the inflow layer, more consistent with observations, but also a smaller inner core that was less than half the size of the original.

Abstract

Roughness height for heat transfer is a crucial parameter in the estimation of sensible heat flux. In this study, the performance of the Surface Energy Balance System (SEBS) has been tested and evaluated for typical land surfaces on the Tibetan Plateau on the basis of time series of observations at four sites with bare soil, sparse canopy, dense canopy, and snow surface, respectively. Both under- and overestimation at low and high sensible heat fluxes by SEBS was discovered. Through sensitivity analyses, it was identified that these biases are related to the SEBS parameterization of bare soil’s excess resistance to heat transfer (kB ⁻¹, where k is the von Kármán constant and B ⁻¹ is the Stanton number). The kB ⁻¹ of bare soil in SEBS was replaced. The results show that the revised model performs better than the original model.

ABSTRACT

Current land surface models still have difficulties with producing reliable surface heat fluxes and skin temperature (T _sfc) estimates for high-altitude regions, which may be addressed via adequate parameterization of the roughness lengths for momentum (z _0m) and heat (z _0h) transfer. In this study, the performance of various z _0h and z _0m schemes developed for the Noah land surface model is assessed for a high-altitude site (3430 m) on the northeastern part of the Tibetan Plateau. Based on the in situ surface heat fluxes and profile measurements of wind and temperature, monthly variations of z _0m and diurnal variations of z _0h are derived through application of the Monin–Obukhov similarity theory. These derived values together with the measured heat fluxes are utilized to assess the performance of those z _0m and z _0h schemes for different seasons. The analyses show that the z _0m dynamics are related to vegetation dynamics and soil water freeze–thaw state, which are reproduced satisfactorily with current z _0m schemes. Further, it is demonstrated that the heat flux simulations are very sensitive to the diurnal variations of z _0h. The newly developed z _0h schemes all capture, at least over the sparse vegetated surfaces during the winter season, the observed diurnal variability much better than the original one. It should, however, be noted that for the dense vegetated surfaces during the spring and monsoon seasons, not all newly developed schemes perform consistently better than the original one. With the most promising schemes, the Noah simulated sensible heat flux, latent heat flux, T _sfc, and soil temperature improved for the monsoon season by about 29%, 79%, 75%, and 81%, respectively. In addition, the impact of T _sfc calculation and energy balance closure associated with measurement uncertainties on the above findings are discussed, and the selection of the appropriate z _0h scheme for applications is addressed.

Abstract

This study evaluates the Noah land surface model (LSM) in its ability to simulate water and heat exchanges over frozen ground in a Tibetan meadow ecosystem. A comprehensive dataset including in situ micrometeorological and soil moisture–temperature profile measurements collected between November and March is utilized, and analyses of the measurements reveal that the measured soil freezing characteristics are better captured by 1) modifying the parameter b _l implemented in the current Noah LSM that constrains the shape parameter of soil water retention curve utilized by the water potential freezing point depression equation to produce appropriate liquid water content θ _liq under subzero temperature conditions and 2) neglecting the ice effect on soil-specific surface and thus matric potential via setting the empirical parameter that accounts for the effect of increase in specific surface of soil particles and ice–liquid water c _k to zero. The numerical experiments performed with the Noah model run show that in comparison to the default Noah LSM, adoption of c _k = 0 and site-specific b _l values reduces the overestimation of θ _liq across the soil profile. Implementation of augmentations such as the parameterization of diurnally varying thermal roughness length resolves the overestimation of daytime turbulent heat fluxes and underestimation of surface temperature. Further adoption of a new heat conductivity parameterization reduces the overestimation of nighttime surface temperature. An appropriate treatment of phase change efficiency that accounts for changing freezing rate with varying liquid water contents is also needed to reduce the temperature underestimation across soil profiles.

Abstract

The potential for soil moisture and vegetation water content retrieval using Special Sensor Microwave Imager (SSM/I) brightness temperature over a corn and soybean field region was analyzed and assessed using datasets from the Soil Moisture Experiment 2002 (SMEX02). Soil moisture retrieval was performed using a dual-polarization 19.4-GHz data algorithm that requires the specification of two vegetation parameters—single scattering albedo and vegetation water content. Single scattering albedo was estimated using published values. A method for estimating the vegetation water content from the microwave polarization index using SSM/I 37.0-GHz data was developed for the region using extensive datasets developed as part of SMEX02. Analyses indicated that the sensitivity of the brightness temperature to soil moisture decreased as vegetation water content increased. However, there was evidence that SSM/I brightness temperatures changed in response to soil moisture increases resulting from rainfall during the later stages of crop growth. This was partly attributed to the lower soil and vegetation thermal temperatures that typically followed a rainfall. Comparisons between experimentally measured volumetric soil moisture and SSM/I-retrieved soil moisture indicated that soil moisture retrieval was feasible using SSM/I data, but the accuracy highly depended upon the levels of vegetation and atmospheric precipitable water; the standard error of estimate over the 3-week study period was 5.49%. The potential for using this approach on a larger scale was demonstrated by mapping the state of Iowa. Results of this investigation provide new insights on how one might operationally correct for vegetation effects using high-frequency microwave observations.