Kun Yang

A hybrid model for estimating global solar radiation

Abstract In view of the site-dependence of Angstrom correlation, this study developed a hybrid model to estimate global radiation H. Unlike Angstrom correlation H=(α+βS/S0)H0, this model suggested that H=(a+b S/S0)Hb+(c+d S/S0)Hd, Hb and Hd are effective beam radiation and effective diffuse radiation, which imply latitude, elevation and seasonal effect on radiation. Hb and Hd are calculated by an arithmetic model derived from spectral model. The hybrid model was designed for estimating monthly mean daily global radiation with hourly-recorded bright sunshine time, and its applicability was verified at observatories in Japan.

Turbulent flux transfer over bare-soil surfaces: Characteristics and parameterization

Abstract Parameterization of turbulent flux from bare-soil and undercanopy surfaces is imperative for modeling land–atmosphere interactions in arid and semiarid regions, where flux from the ground is dominant or comparable to canopy-sourced flux. This paper presents the major characteristics of turbulent flux transfers over seven bare-soil surfaces. These sites are located in arid, semiarid, and semihumid regions in Asia and represent a variety of conditions for aerodynamic roughness length (z0m; from <1 to 10 mm) and sensible heat flux (from −50 to 400 W m−2). For each site, parameter kB−1 [=ln(z0m/z0h), where z0h is the thermal roughness length] exhibits clear diurnal variations with higher values during the day and lower values at night. Mean values of z0h for the individual sites do not change significantly with z0m, resulting in kB−1 increasing with z0m, and thus the momentum transfer coefficient increases faster than the heat transfer coefficient with z0m. The term kB−1 often becomes negative at nig...

Evaporative cooling over the Tibetan Plateau induced by vegetation growth

Significance Understanding land-surface biophysical feedbacks to the atmosphere is needed if we are to simulate regional climate accurately. In the Arctic, previous studies have shown that enhanced vegetation growth decreases albedo and amplifies warming. In contrast, on the Tibetan Plateau, a statistical model based on in situ observations and decomposition of the surface energy budget suggests that increased vegetation activity may attenuate daytime warming by enhancing evapotranspiration (ET), a cooling process. A regional climate model also simulates daytime cooling when prescribed with increased vegetation activity, but with a magnitude smaller than observed, likely because this model simulates weaker ET enhancement in response to increased vegetation growth. In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.

A MULTISCALE SOIL MOISTURE AND FREEZE-THAW MONITORING NETWORK ON THE THIRD POLE

Multisphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydrometeorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established a dense monitoring network on the central Tibetan Plateau to measure two state variables (soil moisture and temperature) at three spatial scales (1.0°, 0.3°, and 0.1°) and four soil depths (0–5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze–thaw cycle. The network consists of 56 stations with their elevation varying over 4470–4950 m. As auxiliary parameters of this network, soil texture and soil organic carbon content are measured at each station to support further studies. To guarantee continuous and high-quality data, tremendous efforts have been made t...

Simultaneous estimation of both soil moisture and model parameters using particle filtering method through the assimilation of microwave signal

[1] Soil moisture is a very important variable in land surface processes. Both field moisture measurements and estimates from modeling have their limitations when being used to estimate soil moisture on a large spatial scale. Remote sensing is becoming a practical method to estimate soil moisture globally; however, the quality of current soil surface moisture products needs to be improved in order to meet practical requirements. Data assimilation (DA) is a promising approach to merge model dynamics and remote sensing observations, thus having the potential to estimate soil moisture more accurately. In this study, a data assimilation algorithm, which couples the particle filter and the kernel smoothing technique, is presented to estimate soil moisture and soil parameters from microwave signals. A simple hydrological model with a daily time step is utilized to reduce the computational burden in the process of data assimilation. An observation operator based on the ratio of two microwave brightness temperatures at different frequencies is designed to link surface soil moisture with remote sensing measurements, and a sensitivity analysis of this operator is also conducted. Additionally, a variant of particle filtering method is developed for the joint estimation of soil moisture and soil parameters such as texture and porosity. This assimilation scheme is validated against field moisture measurements at the CEOP/Mongolia experiment site and is found to estimate near-surface soil moisture very well. The retrieved soil texture still contains large uncertainties as the retrieved values cannot converge to fixed points or narrow ranges when using different initial soil texture values, but the retrieved soil porosity has relatively small uncertainties.

Improving the Noah Land Surface Model in Arid Regions with an Appropriate Parameterization of the Thermal Roughness Length

Daytime land surface temperatures in arid and semiarid regions are typically not well simulated in current land surface models (LSMs). This study first evaluates the importance of parameterizing the thermal roughness length (z0h) to model the surface temperature (Tsfc) and turbulent sensible heat flux (H) in arid regions. Six schemes for z0h are implemented into the Noah LSM, revealing the high sensitivity of the simulations to its parameterization. Comparisons are then performed between the original Noah LSM and a revised version with a novel z0h scheme against observations at four arid or semiarid sites, including one in Arizona and three in western China. The land they cover is sparse grass or bare soil. The results indicate that the original Noah LSM significantly underestimates Tsfc and overestimates H in the daytime, whereas the revised model can simulate well both Tsfc and H simultaneously. The improved version benefits from the successful modeling of the diurnal variation of z0h, which the original model cannot produce.

Response of inland lake dynamics over the Tibetan Plateau to climate change

The water balance of inland lakes on the Tibetan Plateau (TP) involves complex hydrological processes; their dynamics over recent decades is a good indicator of changes in water cycle under rapid global warming. Based on satellite images and extensive field investigations, we demonstrate that a coherent lake growth on the TP interior (TPI) has occurred since the late 1990s in response to a significant global climate change. Closed lakes on the TPI varied heterogeneously during 1976–1999, but expanded coherently and significantly in both lake area and water depth during 1999–2010. Although the decreased potential evaporation and glacier mass loss may contribute to the lake growth since the late 1990s, the significant water surplus is mainly attributed to increased regional precipitation, which, in turn, may be related to changes in large-scale atmospheric circulation, including the intensified Northern Hemisphere summer monsoon (NHSM) circulation and the poleward shift of the Eastern Asian westerlies jet stream.

Validation of a Dual-Pass Microwave Land Data Assimilation System for Estimating Surface Soil Moisture in Semiarid Regions

This study examines the capability of a new microwave land data assimilation system (LDAS) for estimating soil moisture in semiarid regions, where soil moisture is very heterogeneous. This system assimilates the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) 6.9- and 18.7-GHz brightness temperatures into a land surface model (LSM), with a radiative transfer model as an observation operator. To reduce errors caused by uncertainties of system parameters, the LDAS uses a dual-pass assimilation algorithm, with a calibration pass to estimate major model parameters from satellite data and an assimilation pass to estimate the near-surface soil moisture. Validation data of soil moisture were collected in a Mongolian semiarid region. Results show that (i) the LDAS-estimated soil moistures are comparable to areal averages of in situ measurements, though the measured soil moistures were highly variable from site to site; (ii) the LSM-simulated soil moistures show less biases when the LSM uses LDAS-calibrated parameter values instead of default parameter values, indicating that the satellite-based calibration does contribute to soil moisture estimations; and (iii) compared to the LSM, the LDAS produces more robust and reliable soil moisture when forcing data become worse. The lower sensitivity of the LDAS output to precipitation is particularly encouraging for applying this system to regions where precipitation data are prone to errors.

SURFACE FLUX PARAMETERIZATION IN THE TIBETAN PLATEAU

This study investigates some basic aspects related to surface-flux parameterization in the Tibetan Plateau, based on the measurement at three sites. These sites are essentially flat and covered by very sparse and short grasses in the monsoon season. The main contributions include: (1) an optimization technique is proposed to estimate aerodynamic roughness length based on wind and temperature profiles. The approach is not sensitive to random measurement errors if the number of data samples is large enough. The optimized values reasonably vary with surface characteristics. (2) At the three sites, kB-1 (the logarithm of the ratio of aerodynamic roughness length to thermal roughness length) experiences seasonal and diurnal variations in addition to a dependence on surface types. The mean values for the individual sites vary over a range of 2.7 to 6.4 with large standard deviations. (3) A formula for estimatingthe value of kB-1 isproposed to account for the effect of seasonal variation of aerodynamic roughness length and diurnal variation of surface temperature. With the formula, the flux parameterization with surface temperature estimates sensible heat flux better than profile parameterization for all the sites.

Observed Coherent Trends of Surface and Upper-Air Wind Speed over China since 1960

Previous studies indicated that surface wind speed over China declined during past decades, and several explanations exist in the literature. This study presents long-term (1960‐2009) changes of both surface and upper-air wind speeds over China and addresses observed evidence to interpret these changes. It is found that surface wind over China underwent a three-phase change over the past 50 yr: (i) it step changed to a strong wind level at the end of the 1960s, (ii) it declined until the beginning of the 2000s, and (iii) it seemed to be steady and even recovering during the very recent years. The variability of surface wind speed is greater at higher elevations and less at lower elevations. In particular, surface wind speed over the elevated Tibetan Plateau has changed more significantly. Changes in upper-air wind speed observed from rawinsonde are similar to surface wind changes. The NCEP‐NCAR reanalysis indicates that wind speed changes correspond to changes in geopotential height gradient at 500 hPa. The latter are further correlated with the changes of latitudinal surface temperature gradient, with a correlation coefficient of 0.88 for the past 50 yr over China. This strongly suggests that the spatial gradient of surface global warming or cooling may significantly change surface wind speed at a regional scale through atmospheric thermal adaption. The recovery of wind speed since the beginning of the 2000s over the Tibetan Plateau might be a precursor of the reversal of wind speed trends over China, as wind over high elevations can respond more rapidly to the warming gradient and atmospheric circulation adjustment.