Development and test verification of air temperature model for Chinese solar and Spainish Almeria-type greenhouses

Growth can be defined as an increment in biomass or an increment in weight or height of the organs of the plant influenced by physiological processes.Many of these processes have their limits genetically determined,but climate and irrigation play an important role.Because of its importance,microclimate has been extensively studied in the modeling as a surrounding condition which is imposed by the exterior climate.The main objective of this work was to develop a temperature model based on the energy balance dynamics at two different greenhouse locations-South-eastern Spain and Northern China,and the traditional structures of Chinese solar greenhouse and Almería-type multi-span greenhouse were taken into account.The final model was developed by combining the external conditions,the actuator influence and the crop growth,where the temperature is influenced by soil,crop,cover,actuators,back wall and greenhouse geometry.The model took into account the energy lost by convective and conductive fluxes,as well as the energy supplied by solar radiation and heating systems.The soil and the back wall are the main media for energy storage.The temperature dynamic was determined by a physical model,which considered the energy balance from a holistic point of view-as a sub-model for a customizable interface among the external climate,the plant and the greenhouse system.The influences of different subsystems included in the temperature model were analyzed and evaluated.The results showed a high R^(2)value of 0.94 for Beijing and 0.95 for Almeria,and the average error was low,of which the MAE and RMSE were 0.71 and 1.365 for Almeria and 0.62 and 1.102 for Beijing,respectively.Thus,the model can be considered as a powerful tool for control design purposes in microclimate systems.

Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations and Future Projections

Based on observations and Coupled Model lntercomparison Project Phase 5 （CMIP5） results, multidecadal variations and trends in annual mean surface air temperature anomalies （SATa） at global, hemispheric, and hemispheric land and ocean scales in the past and under the future scenarios of two representative concentration pathways （RCPs） are analyzed. Fifteen models are selected based on their performances in capturing the temporal variability, long-term trend, multidecadal variations, and trends in global annual mean SATa. Observational data analysis shows that the multidecadal variations in annual mean SATa of the land and ocean in the northern hemisphere （NH） and of the ocean in the southern hemisphere （SH） are similar to those of the global mean, showing an increase during the 1900-1944 and 1971-2000 periods, and flattening or even cooling during the 1945-1970 and 2001-2013 periods. These observed characteristics are basically reproduced by the models. However, SATa over SH land show an increase during the 1945-1970 period, which differs from the other hemispheric scales, and this feature is not captured well by the models. For the recent hiatus period （2001-2013）, the projected trends of BCC-CSM1-1-m, CMCC-CM, GFDL-ESM2M, and NorESM1-ME at the global and hemispheric scales are closest to the observations based on RCP4.5 and RCP8.5 scenarios, suggesting that these four models have better projection capability in SATa. Because these four models are better at simulating and projecting the multidecadal trends of SATa, they are selected to analyze future SATa variations at the global and hemispheric scales during the 2006-2099 period. The selected multi-model ensemble （MME） projected trends in annual mean SATa for the globe, NH, and SH under RCP4.5 （RCP8.5） are 0.17 （0.29） ℃, 0.22 （0.36） ℃, and 0.11 （0.23） ℃-decade-1 in the 21st century, respectively. These values are significantly lower than the projections of CMIP5 MME without model selection.

Simulation of permafrost changes on the Qinghai–Tibet Plateau, China, over the past three decades

Permafrost is one of the largest elements of the terrestrial cryosphere and is extremely sensitive to climate change.Based on mean annual ground temperature(MAGT)data from 189 boreholes on the Qinghai–Tibet Plateau(QTP),terrain factors,and climate data from China Meteorological Forcing Dataset,we propose a new mean annual ground air temperature(MAGAT)statistical model between meteorological parameters with subsurface temperatures to simulate permafrost distribution and variation of MAGT on the QTP over the past three decades(1981–2010).Validation of the model with MAGT data from 13 boreholes and permafrost maps of the QTP indicated that the MAGAT model is applicable to simulate the distribution and evolution of permafrost on the QTP.Simulation results show that the spatiotemporal MAGT of permafrost significantly increased by 0.37℃,or 0.25℃/10 yr,and the total area of permafrost decreased by 2.48×10^(5)km^(2) on the QTP over the past three decades.Regionally,the changes of permafrost in the southwestern QTP were greater than other regions of the QTP.