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Light is one of the most important natural resources for plant growth. Light interception (LI) and use efficiency (LUE) are often affected by the structure of canopy caused by growing pattern and agronomy managements. Agronomy practices, such as the ridge–furrow system and plastic film cover, might affect the leaf morphology and then light transmission within the canopy, thus change light extinction coefficient (k), and LI and LUE. The objective of this study is to quantify LI and LUE in rain-fed maize (Zea Mays L.), a major cropping system in Northeast China, under different combinations of ridge–furrow and film covering ratios. The tested ridge–furrow system (DRF: “double ridges and furrows”) was asymmetric and alternated with wide ridge (0.70 m in width and 0.15 m in height), narrow furrow (0.10 m), narrow ridge (0.40 m in width and 0.20 m in height), and narrow furrow (0.10 m). Field experiments were conducted in 2013 and 2014 in Jilin Province, Northeast China. Four treatments were tested: no ridges and plastic film cover (control, NRF), ridges without film cover (DRF0), ridges with 58% film cover (DRF58), and ridges with 100% film cover (DRF100). DRF0 significantly increased LI by 9% compared with NRF, while film cover showed a marginal improvement. Specific leaf area in DRF experiments with film cover was significantly lower than in NRF, and leaf angle was 16% higher than in NRF, resulting in a 4% reduction in k. LUE of maize was not increased by DRF0, but was significantly enhanced by covering film in other DRF experiments, especially by 22% in DRF100. The increase of LUE by film cover was due to a greater biomass production and a lower assimilation portioning to vegetative organs, which caused a higher harvest index. The results could help farmers to optimize maize managements, especially in the region with decreased solar radiation under climate change.

This study evaluated the simulated cloud radiative feedbacks (CRF) during the El Nino-Southern Oscillation (ENSO) cycle in the latest version of the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). We conducted two experimental model simulations: the Atmospheric Model Intercomparison Project (AMIP), forced by the observed sea surface temperature (SST); and the preindustrial control (PIcontrol), a coupled run without flux correction. We found that both the experiments generally reproduced the observed features of the shortwave and longwave cloud radiative forcing (SWCRF and LWCRF) feedbacks. The AMIP run exhibited better simulation performance in the magnitude and spatial distribution than the PIcontrol run. Furthermore, the simulation biases in SWCRF and LWCRF feedbacks were linked to the biases in the representation of the corresponding total cloud cover and precipitation feedbacks. It is interesting to further find that the simulation bias originating in the atmospheric component was amplified in the PIcontrol run, indicating that the coupling aggravated the simulation bias. Since the PIcontrol run exhibited an apparent mean SST cold bias over the cold tongue, the precipitation response to the SST anomaly (SSTA) changes during the ENSO cycle occurred towards the relatively warmer western equatorial Pacific. Thus, the corresponding cloud cover and CRF shifted westward and showed a weaker magnitude in the PI-control run versus observational data. In contrast, the AMIP run was forced by the observational SST, hence representing a more realistic CRF. Our results demonstrate the challenges of simulating CRF in coupled models. This study also underscores the necessity of realistically representing the climatological mean state when simulating CRF during the ENSO cycle.

Considering the characteristics of nonlinear problems, a new method based on the L-curve method and including the concept of entropy was designed to select the regularization parameter in the one-dimensional variational analysis-based sounding retrieval method. In the first iteration, this method uses an empirical regularization parameter derived by minimizing the entropy of variables. During subsequent iterations, it uses the L-curve method to select the regularization parameter in the vicinity of the regularization parameter selected in the last iteration. The new method was employed to select the regularization parameter in retrieving atmospheric temperature and moisture profiles from Atmospheric Infrared Sounder radiance measurements selected from the first day of each month in 2008. The results show that compared with the original L-curve method, the new method yields 5.5% and 2.5% improvements on temperature and relative humidity profiles, respectively. Compared with the discrepancy principle method, the improvements on temperature and relative humidity profiles are 1.6% and 2.0%, respectively.

Soil moisture is an important variable in the fields of hydrology, meteorology, and agriculture, and has been used for numerous applications and forecasts. Accurate soil moisture predictions on both a large scale and local scale for different soil depths are needed. In this study, a soil moisture assimilation and prediction based on the Ensemble Kalman Filter (EnKF) and Simple Biosphere Model (SiB2) have been performed in Meilin watershed, eastern China, to evaluate the initial state values with different assimilation frequencies and precipitation influences on soil moisture predictions. The assimilated results at the end of the assimilation period with different assimilation frequencies were set to be the initial values for the prediction period. The measured precipitation, randomly generated precipitation, and zero precipitation were used to force the land surface model in the prediction period. Ten cases were considered based on the initial value and precipitation. The results indicate that, for the summer prediction period with the deeper water table depth, the assimilation results with different assimilation frequencies influence soil moisture predictions significantly. The higher assimilation frequency gives better soil moisture predictions for a long lead-time. The soil moisture predictions are affected by precipitation within the prediction period. For a short lead-time, the soil moisture predictions are better for the case with precipitation, but for a long lead-time, they are better without precipitation. For the winter prediction period with a lower water table depth, there are better soil moisture predictions for the whole prediction period. Unlike the summer prediction period, the soil moisture predictions of winter prediction period are not significantly influenced by precipitation. Overall, it is shown that soil moisture assimilations improve its predictions.

In this study, local circulations and their responses to land use and land cover (LULC) changes over the Yellow Mountains of China are examined by using Weather Research and Forecast (WRF) model simulations of a selected case under weak-gradient synoptic conditions. The results show that mountain-valley breezes over the region are characterized by an intense upslope flow lasting for about 11 h (0600-1700 LST) along the northern slope during daytime. A convergence zone occurs at the mountain ridge and moves northwest-ward with time. During nighttime, wind directions are reversed, starting first at higher elevations. Three sensitivity experiments are conducted, in which the current land covers are replaced by grassland, mixed forest, and bare soil, respectively, while keeping the other model conditions identical to a control run. These sensitivity simulations are designed to represent the changes of LULC over the Yellow Mountains area during the past decades. The results show that changes in land cover could affect substantially land-surface and atmosphere interactions, the evolution of local circulations, and characteristics of the planetary boundary layer (PBL). Significant differences are noted in horizontal winds, and sensible and latent heat fluxes. On the other hand, when the surface is covered by mixed forest, slight variations in local winds and surface variables are identified. The results appear to have important implications to urban planning and constructions as well as the transport of air pollutants over mountainous regions.

The water in the air is composed of water vapor and hydrometeors, which are inseparable in the global atmosphere. Precipitation basically comes from hydrometeors instead of directly from water vapor, but hydrometeors are rarely focused on in previous studies. When assessing the maximum potential precipitation, it is necessary to quantify the total amount of hydrometeors present in the air within an area for a certain period of time. Those hydrometeors that have not participated in precipitation formation in the surface, suspending in the atmosphere to be exploited, are defined as the cloud water resource (CWR). Based on the water budget equations, we defined 16 terms (including 12 independent ones) respectively related to the hydrometeors, water vapor, and total water substance in the atmosphere, and 12 characteristic variables related to precipitation and CWR such as precipitation efficiency (PE) and renewal time (RT). Correspondingly, the CWR contributors are grouped into state terms, advection terms, and source/sink terms. Two methods are developed to quantify the CWR (details of which are presented in the companion paper) with satellite observations, atmospheric reanalysis data, precipitation products, and cloud resolving models. The CWR and related variables over North China in April and August 2017 are thus derived. The results show that CWR has the same order of magnitude as surface precipitation (Ps). The hydrometers converted from water vapor (Cvh) during the condensation process is the primary source of precipitation. It is highly correlated with Ps and contributes the most to the CWR over a large region. The state variables and advection terms of hydrometeors are two orders of magnitude lower than the corresponding terms of water vapor. The atmospheric hydrometeors can lead to higher PE than water vapor (several tens of percent versus a few percent), with a shorter RT (only a few hours versus several days). For daily CWR, the state terms are important, but for monthly and longer-time mean CWR, the source/sink terms (i.e., cloud microphysical processes) contribute the largest; meanwhile, the advection terms contribute less for larger study areas.

The impact of solar activity on climate system is spatiotemporally selective and usually more significant on the regional scale. Using statistical methods and solar radio flux (SRF) data, this paper investigates the impact of the solar 11-yr cycle on regional climate of Northeast Asia in recent decades. Significant differences in winter temperature, precipitation, and the atmospheric circulation over Northeast Asia are found between peak and valley solar activity years. In peak years, temperature is higher over vast areas of the Eurasian continent in middle and high latitudes, and prone to producing anomalous high pressure there. Northeast Asia is located to the south of the anomalous high pressure, where the easterlies prevail and transport moisture from the western Pacific Ocean to the inland of East Asia and intensify precipitation there. In valley years, temperature is lower over the Eurasian continent and northern Pacific Ocean in middle and high latitudes, and there maintain anomalous low pressure systems in the two regions. Over the Northeast Asian continent, north winds prevail, which transport cold and dry air mass from the high latitude to Northeast Asia and reduce precipitation there. The correlation coefficient of winter precipitation in Northeast China and SRF reaches 0.4, and is statistically significant at the 99% confidence level based on the Student’s t-test. The latent heat flux anomalies over the Pacific Ocean caused by solar cycle could explain the spatial pattern of abnormal winter precipitation of China, suggesting that the solar activity may change the climate of Northeast Asia through air-sea interaction.

Based on the NCEP/NCAR reanalysis data and Chinese observational data during 1961–2013, atmospheric circulation patterns over East Asia in summer and their connection with precipitation and surface air temperature in eastern China as well as associated external forcing are investigated. Three patterns of the atmospheric circulation are identified, all with quasi-barotropic structures: (1) the East Asia/Pacific (EAP) pattern, (2) the Baikal Lake/Okhotsk Sea (BLOS) pattern, and (3) the eastern China/northern Okhotsk Sea (ECNOS) pattern. The positive EAP pattern significantly increases precipitation over the Yangtze River valley and favors cooling north of the Yangtze River and warming south of the Yangtze River in summer. The warm sea surface temperature anomalies over the tropical Indian Ocean suppress convection over the northwestern subtropical Pacific through the Ekman divergence induced by a Kelvin wave and excite the EAP pattern. The positive BLOS pattern is associated with below-average precipitation south of the Yangtze River and robust cooling over northeastern China. This pattern is triggered by anomalous spring sea ice concentration in the northern Barents Sea. The anomalous sea ice concentration contributes to a Rossby wave activity flux originating from the Greenland Sea, which propagates eastward to North Pacific. The positive ECNOS pattern leads to below-average precipitation and significant warming over northeastern China in summer. The reduced soil moisture associated with the earlier spring snowmelt enhances surface warming over Mongolia and northeastern China and the later spring snowmelt leads to surface cooling over Far East in summer, both of which are responsible for the formation of the ECNOS pattern.