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Wenjun Tang, Kun Yang, Jun Qin, Jun Li, and Jiangang Ye

Abstract

Surface solar radiation (SSR) over the ocean is essential for studies of ocean–atmosphere interactions and marine ecology, and satellite remote sensing is a major way to obtain the SSR over ocean. A new high-resolution (10 km; 3 h) SSR product has recently been developed, mainly based on the newly released cloud product of the International Satellite Cloud Climatology Project H series (ISCCP-HXG), and is available for the period from July 1983 to December 2018. In this study, we compared this SSR product with in situ observations from 70 buoy sites in the Global Tropical Moored Buoy Array (GTMBA) and also compared it with another well-known satellite-derived SSR product from the Clouds and the Earth’s Radiant Energy System (CERES; edition 4.1), which has a spatial resolution of approximately 100 km. The results show that the ISCCP-HXG SSR product is generally more accurate than the CERES SSR product for both ocean and land surfaces. We also found that the accuracy of both satellite-derived SSR products (ISCCP-HXG and CRERS) was higher over ocean than over land and that the accuracy of ISCCP-HXG SSR improves greatly when the spatial resolution of the product is coarsened to ≥ 30 km.

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Kun Yang, Toshio Koike, Ichirow Kaihotsu, and Jun Qin

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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.

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Jun Qin, Kun Yang, Shunlin Liang, and Wenjun Tang

Abstract

Photosynthetically active radiation (PAR) is absorbed by plants to carry out photosynthesis. Its estimation is important for many applications such as ecological modeling. In this study, a broadband transmittance scheme for solar radiation at the PAR band is developed to estimate clear-sky PAR values. The influence of clouds is subsequently taken into account through sunshine-duration data. This scheme is examined without local calibration against the observed PAR values under both clear- and cloudy-sky conditions at seven widely distributed Surface Radiation Budget Network (SURFRAD) stations. The results indicate that the scheme can estimate the daily mean PAR at these seven stations under all-sky conditions with root-mean-square error and mean bias error values ranging from 6.03 to 6.83 W m−2 and from −2.86 to 1.03 W m−2, respectively. Further analyses indicate that the scheme can estimate PAR values well with globally available aerosol and ozone datasets. This suggests that the scheme can be applied to regions for which observed aerosol and ozone data are not available.

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Changgui Lin, Kun Yang, Jun Qin, and Rong Fu

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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.

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Tongren Xu, Shaomin Liu, Shunlin Liang, and Jun Qin

Abstract

Four data assimilation scheme combinations derived from two strategies and two optimization algorithms [the ensemble Kalman filter (EnKF) and the shuffled complex evolution method developed at The University of Arizona (SCE-UA)] are developed based on the Common Land Model (CLM) to improve predictions of water and heat fluxes. The first strategy is constructed through adjusting the soil temperature, while the second strategy adjusts the soil moisture. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products are compared with ground-measured surface temperature, and assimilated into the CLM. The relationship equation between the MODIS LST products and CLM surface temperature is taken as the observation operator and the root-mean-square error (RMSE) is applied as the observation error. The assimilation results are validated by measurements from six observation sites located in Germany, the United States, and China. Results indicate that the developed data assimilation schemes can improve estimates of water and heat fluxes. Overall, strategy 2 is superior to strategy 1 when using the same optimization algorithm. The EnKF algorithm performs slightly better than the SCE-UA algorithm when using the same strategy. Strategy 2 combined with the EnKF algorithm performs best for water and heat fluxes, and the reductions in the RMSE are found to be 24.0 and 15.2 W m−2 for sensible and latent heat fluxes, respectively. The joint assimilation of the MODIS LST and soil moisture observations can produce better results for strategy 2 with the SCE-UA. Since preprocessing model parameters are used in this study, the uncertainties in the model parameters may have resulted in suboptimal assimilation results. Therefore, model calibrations should be conducted in the future.

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Yingying Chen, Kun Yang, Degang Zhou, Jun Qin, and Xiaofeng Guo

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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 (z 0h) to model the surface temperature (T sfc) and turbulent sensible heat flux (H) in arid regions. Six schemes for z 0h 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 z 0h 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 T sfc and overestimates H in the daytime, whereas the revised model can simulate well both T sfc and H simultaneously. The improved version benefits from the successful modeling of the diurnal variation of z 0h, which the original model cannot produce.

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Kun Yang, Xiaofeng Guo, Jie He, Jun Qin, and Toshio Koike

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Atmospheric heating over the Tibetan Plateau (TP) enhances the Asian summer monsoon. This study presents a state-of-the-art estimate of the heating components and their total over the TP, with the aid of high-accuracy experimental data, an updated land surface model, and carefully selected satellite data.

The new estimate differs from previous estimates in three aspects: 1) different seasonality—the new estimation shows the maximum total heat source occurs in July (the mature period of the monsoon), rather than in the previously reported month of May or June (around the onset of the monsoon), because previous studies greatly overestimated radiative cooling during the monsoon season [June–August (JJA)]; 2) different regional pattern—the eastern TP exhibits stronger heating than the western TP in summer, whereas previous studies gave either an opposite spatial pattern because of overestimated sensible heat flux over the western TP or an overall weaker heat source because of overestimated radiative cooling; and 3) different trend—sensible heat, radiative convergence, and the total heat source have decreased since the 1980s, but their weakening trends were overestimated in a recent study. These biases in previous studies are due to fairly empirical methods and data that were not evaluated against experimental data.

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Kun Yang, Jun Qin, Xiaofeng Guo, Degang Zhou, and Yaoming Ma

Abstract

To clarify the thermal forcing of the Tibetan Plateau, long-term coarse-temporal-resolution data from the China Meteorological Administration have been widely used to estimate surface sensible heat flux by bulk methods in many previous studies; however, these estimates have seldom been evaluated against observations. This study at first evaluates three widely used bulk schemes against Tibet instrumental flux data. The evaluation shows that large uncertainties exist in the heat flux estimated by these schemes; in particular, upward heat fluxes in winter may be significantly underestimated, because diurnal variations of atmospheric stability were not taken into account. To improve the estimate, a new method is developed to disaggregate coarse-resolution meteorological data to hourly according to statistical relationships derived from high-resolution experimental data, and then sensible heat flux is estimated from the hourly data by a well-validated flux scheme. Evaluations against heat flux observations in summer and against net radiation observations in winter indicate that the new method performs much better than previous schemes, and therefore it provides a robust basis for quantifying the Tibetan surface energy budget.

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Jun Qin, Ailin Shi, Guoyu Ren, Zhenghong Chen, Yuda Yang, Xukai Zou, and Panfeng Zhang

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The White Crane Ridge (WCR) Rock Fish, now submerged under the backwater of the Three Gorges Reservoir in the Yangtze River, are affirmed as one of the earliest hydrologic observations ever made in any large river in the world. The usually in-water monument provides highly valuable historical records of severe droughts in the upper Yangtze over the last 1,200 years. This article updated the historical drought chronology previously developed based on the WCR inscriptions, which can be applied in assessment of extreme climatic and hydrological risks, and also made a preliminary analysis of changes of the severe drought frequency during the last thousand years in the upper Yangtze. The analysis shows that the severe droughts occurred more frequently during the Medieval Climate Anomaly (MCA), relatively less so during the Little Ice Age (LIA), and once again more often under the background of modern global warming. It was suggested that a generally warmer Euro-Asian continent during the MCA was in favor of the stronger East Asian summer monsoon, and the resulting less precipitation and more severe droughts of the Yangtze and the lower water level at the Three Gorges area on the centennial scale, and vice versa for the period of the LIA. The results would help in understanding the causes and mechanisms of the regional climate change and variability, and also in taking measures in the fields of the watershed management to cope with the long-term change in climatic and hydrologic droughts.

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Ning Lu, Kevin E. Trenberth, Jun Qin, Kun Yang, and Ling Yao

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Long-term trends in precipitable water (PW) are an important component of climate change assessments for the Tibetan Plateau (TP). PW products from Moderate Resolution Imaging Spectroradiometer (MODIS) are able to provide good spatial coverage of PW over the TP but limited in time coverage, while the meteorological stations in the TP can estimate long-term PW but unevenly distributed. To detect the decadal trend in PW over the TP, Bayesian inference theory is used to construct long-term and spatially continuous PW data for the TP based on the station and MODIS observations. The prior information on the monthly-mean PW from MODIS and the 63 stations over the TP for 2000–06 is used to get the posterior probability knowledge that is utilized to build a Bayesian estimation model. This model is then operated to estimate continuous monthly-mean PW for 1970–2011 and its performance is evaluated using the monthly MODIS PW anomalies (2007–11) and annual GPS PW anomalies (1995–2011), with RMSEs below 0.65 mm, to demonstrate that the model estimation can reproduce the PW variability over the TP in both space and time. Annual PW series show a significant increasing trend of 0.19 mm decade−1 for the TP during the 42 years. The most significant PW increase of 0.47 mm decade−1 occurs for 1986–99 and an insignificant decrease occurs for 2000–11. From the comparison of the PW data from JRA-55, ERA-40, ERA-Interim, MERRA, NCEP-2, and ISCCP, it is found that none of them are able to show the actual long-term trends and variability in PW for the TP as the Bayesian estimation.

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