Review on simulation of land-surface processes on the Tibetan Plateau

The Tibetan Plateau(TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospecting the latest research progress in the simulation of land-surface processes(LSPs) over the past 20 years, this study discusses both the simulation ability of land-surface models(LSMs) and the modification of parameterization schemes from two perspectives, the models' applicability and improved parameterization schemes. Our review suggests that different LSMs can well capture the spatiotemporal variations of the physical quantities of LSPs; but none of them can be fully applied to the plateau, meaning that all need to be revised according to the characteristics specific to the TP. Avoiding the unstable iterative computation and determining the freeze-thaw critical temperature according to the thermodynamic equilibrium equation, the unreasonable freeze-thaw parameterization scheme can be improved. Due to the complex underlying surface of the TP, no parameterization scheme of roughness length can well simulate the various characteristics of the turbulent flux over the TP at different temporal scales. The uniform soil thermodynamic and hydraulic parameterization scheme is unreasonable when it is applied to the plateau, as a result of the strong soil heterogeneity. There is little research on the snow-cover process so far,and the improved scheme has no advantage over the original one due to the lack of some related physical processes. The constant interaction among subprocesses of LSPs makes the improvement of a multiparameterization scheme yield better simulation results. According to the review of existing research, adding high-quality observation stations, developing a parameterization scheme suitable for the special LSPs of the TP, and adjusting the model structures can be helpful to the simulation of LSPs on the TP.

Comparative study of surface energy and land-surface parameters in different climate zones in Northwest China

Based on observational data of arid,semi-arid and semi-humid areas in Northwest China,the characteristics of surface-wa ter heat transfer and land-surface parameters were compared and analyzed.The results show that the annual mean net radi ation was largest in the semi-humid area,followed by the semi-arid area,and then the arid area:77.72 W/m^2,67.73 W/m^2,and 55.47 W/m^2,respectively.The annual mean sensible heat flux was largest in the arid area,followed by the semi-arid and semi-humid areas,while latent heat flux showed the reverse.The annual mean sensible heat flux in arid,semi-arid,and semi-humid areas was 85.7 W/m^2,37.59 W/m^2,and 27.55 W/m^2,respectively.The annual mean latent heat flux was 0 W/m^2,26.08 W/m^2,and 51.19 W/m2,respectively.The annual mean soil-heat flux at the 5-cm soil layer in arid,semi-arid,and semi-humid areas was 1.00 W/m^2,0.82 W/m^2,and 1.25 W/m^2,respectively.The annual mean surface albedo was larg est in the arid area,followed by the semi-humid area;and the smallest was in the semi-arid area:0.24,0.21,and 0.18,re spectively.The annual mean Bowen ratio in the semi-arid area was about 2.06,and that in semi-humid area was about 0.03.The annual mean soil thermal conductivity in the arid,semi-arid,and semi-humid areas was 0.26 W/(m k),1.15 W/(m k),and 1.20 W/(m k),respectively.

Study on Numerical Simulation of the Impact of the Land-Surface Process in a Meiyu Front Rainstorm

[Objective] The research aimed to carry out numerical simulation on impact of land-surface process in a Meiyu front rainstorm.[Method] Based on the meso-scale atmospheric non-hydrostatic model GRAPES-Meso which coupled with NOAH land-surface module,a Meiyu front rainstorm in Jianghuai basin during 6-8 July,2005 was simulated.Via sensitivity tests with and without land-surface process,the impact of land-surface process on Meiyu front rainstorm was studied.[Result] GRAPES-Meso which coupled with NOAH land-surface process could simulate daily variation characteristics of Meiyu front precipitation and atmospheric low-level southwest jet.The land-surface process could improve the simulations of precipitation initiation,intensity and distribution.The improvement of precipitation initiation simulation was especially obvious,which solved spin-up problem of model to some extent.When the land-atmosphere interaction wasn’t considered,the precipitation initiation of model was very slow.The intensity evolution of simulated precipitation was different from actual situation.Moreover,it couldn’t simulate daily variation characteristics of precipitation and southwest jet.[Conclusion] The land-surface process had important impact on Meiyu process in Jianghuai basin.

MODIS-Derived Nighttime Arctic Land-Surface Temperature Nascent Trends and Non-Stationary Changes

Arctic nighttime land-surface temperatures derived by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the NASA Terra and Aqua satellites are investigated. We use the local equator crossing times of 22:30 and 01:30, respectively, in the analysis of changes, trends and variations on the Arctic region and within 120° sectors. We show increases in the number of days above 0°C and significant increase trends over their decadal periods of March 2000 through 2010 (MODIS Terra) and July 2002 through 2012 (MODIS Aqua). The MODIS Aqua nighttime Arctic land-surface temperature change, +0.2°C ± 0.2°C with P-value of 0.01 indicates a reduction relative to the MODIS Terra nighttime Arctic land-surface temperature change, +1.8°C ± 0.3°C with P-value of 0.01. This reduction is a decadal non-stationary component of the Arctic land-surface temperature changes. The reduction is greatest, -1.3°C ± 0.2°C with P-value of 0.01 in the Eastern Russia— Western North American sector of the Arctic during the July 2002 through 2012.

Arctic Diurnal Land-Surface Temperature Range Changes Derived by NASA MODIS-Terra and -Aqua 2000 through 2012

The diurnal variation of surface temperature is a fundamental parameter as it is a driver of physical processes of atmosphere-land and -ocean energy and mass cycles playing a key role in meteorology and climatology. Our investigation focus is on the diurnal variation of land-surface temperature derived by the Moderate Resolution Imaging Spectroradiometer (MODIS) deployed on the NASA Terra and Aqua satellites. We key our investigation on the ascending and descending mode equator crossing times for daytime and nighttime land-surface temperature variations from March 2000 through 2010 (MODIS-Terra) and July 2002 through 2012 (MODIS-Aqua) and assess the diurnal land-surface temperature range changes at those sampling times. Our investigation shows non-stationary changes in the trends of land-surface temperature diurnal range. We identify changes in the diurnal range trends linked to increase of daytime and nighttime land-surface temperatures from March 2000 through 2010 and decrease in daytime and nighttime land-surface temperatures from July 2002 through 2012. The most recent decrease in daytime and nighttime land-surface temperatures and diurnal range will affect Arctic and other associated energy and mass cycles.

MODIS-Derived Arctic Land-Surface Temperature Trends

Across the Arctic changes in active layer, melting of glaciers and ground ice, thawing of permafrost and sequestration changes of carbon storage are driven in part by variations of land surface heat absorption, conduction and re-radiation relative to solar irradiance. We investigate Arctic land-surface temperature changes and regional variations derived by the MODIS sensors on NASA Aqua and Terra from March 2000 through July 2012. Over this decadal period we detect increase in the number of days with daytime land-surface temperature above 0℃. There are indications of increasing trends of land-surface temperature change. Regional variations of the changes in land-surface temperature likely arise due to surface material types and topography relative to the daytime variation of solar irradiance.

AN IMPROVED LAND-SURFACE PROCESS MODEL AND ITS SIMULATION EXPERIMENT——PART I:LAND-SURFACE PROCESS MODEL AND ITS“OFF-LINE”TESTS AND PERFORMANCE ANALYSES

Based on the existing land-surface schemes and models,an improved Land-surface Process Model(LPM-ZD)has been developed.It has the following major characteristics:(1)The combination of physical equations and empirical analytical formulae are used to construct the governing equations of soil temperature and moisture.Higher resolution of model level and physical equations are adopted for the upper soil layers,and for the lower soil layers,lower resolution of model level is adopted and empirical analytical formulae are used.(2)In land surface hydrological process,the sub-grid distribution of rainfall and its effects are taken into account. (3)A simple snow cover submodel has been used,which includes effects of snow cover on soil thermodynamics and hydrology,as well as albedo. By use of this model and three groups of point observation data,a series of“off-line”tests have been carried out.The simulation results indicate that land-surface process model has good performance and can well simulate diurnal and seasonal variation of land surface processes for many kinds of land surface covers(forest,grass,crops and desert)in different climate zone.The results simulated by the model are consistent with the observations.Later,by use of one group of observation data and the model,a series of sensitivity experiments have been done.It is shown that the model is much sensitive to some parameters,such as initial soil moisture,vegetation physical parameters as well as the proportion of the grid covered with rain.Therefore it is much important for land-surface process model to define these parameters as accurately as possible.

Land-surface temperature retrieval at high spatial and temporal resolutions based on multi-sensor fusion

Land-surface temperature(LST)is of great significance for the estimation of radiation and energy budgets associated with land-surface processes.However,the available satellite LST products have either low spatial resolution or low temporal resolution,which constrains their potential applications.This paper proposes a spatiotemporal fusion method for retrieving LST at high spatial and temporal resolutions.One important characteristic of the proposed method is the consideration of the sensor observation differences between different land-cover types.The other main contribution is that the spatial correlations between different pixels are effectively considered by the use of a variation-based model.The method was tested and assessed quantitatively using the different sensors of Landsat TM/ETM,moderate resolution imaging spectroradiometer and the geostationary operational environmental satellite imager.The validation results indicate that the proposed multisensor fusion method is accurate to about 2.5 K.

SOME NEW UNDERSTANDINGS OF LAND-SURFACE PROCESSES IN ARID AREA FROM THE HEIFE

The survey for the HEIFE(Atmosphere-Land Surface Processes Experiment at Heihe River Basin,Western China)is given in the paper.The following basic subjects for land-surface process- es in arid areas are studied:(1)the general characteristics of the energy budget on ground surface in arid areas;(2)the parameterization of the land surface processes;(3)the interaction between oasis and its desert circumstances,a special phenomenon in arid areas.The analysis shows that the sensible heat flux in the surface energy budget is in the majority,and the latent heat flux may be neglected.The influence of atmospheric stratification stability on the turbulent transfer of energy and substance must be considered in parameterization of land surface processes in arid areas.The “cold island effect”phenomenon in oasis and the“humidity inversion”phenomenon in desert near oasis are the result of the interaction between them.The results would improve the understanding of land surface processes in arid areas.

AN IMPROVED LAND-SURFACE PROCESS MODEL AND ITS SIMULATION EXPERIMENT—PART II:COUPLING SIMULATION EXPERIMENT OF LAND-SURFACE PROCESS MODEL WITH REGIONAL CLIMATE MODEL

The Land-surface Process Model(LPM-ZD)has been successfully coupled with the regional climate model RegCM2 of NCAR.Then thus-obtained coupled model(CRegCM)has been applied to simulate the climate characteristics of heavy rain in middle and East China for three months from May to July 1991.and compared with model output of NCAR-RegCM2 using BATS as land- surface process scheme,abbreviated as NRegCM.The results show that CRegCM has good ability and performance.CRegCM successfully simulates the extreme precipitation event and the simulations of CRegCM for surface temperature and some physical variables related to land surface process are more reasonable than those of NRegCM.

A New Sensitivity Analysis Approach Using Conditional Nonlinear Optimal Perturbations and Its Preliminary Application

Simulations and predictions using numerical models show considerable uncertainties,and parameter uncertainty is one of the most important sources.It is impractical to improve the simulation and prediction abilities by reducing the uncertainties of all parameters.Therefore,identifying the sensitive parameters or parameter combinations is crucial.This study proposes a novel approach:conditional nonlinear optimal perturbations sensitivity analysis(CNOPSA)method.The CNOPSA method fully considers the nonlinear synergistic effects of parameters in the whole parameter space and quantitatively estimates the maximum effects of parameter uncertainties,prone to extreme events.Results of the analytical g-function test indicate that the CNOPSA method can effectively identify the sensitivity of variables.Numerical results of the theoretical five-variable grassland ecosystem model show that the maximum influence of the simulated wilted biomass caused by parameter uncertainty can be estimated and computed by employing the CNOPSA method.The identified sensitive parameters can easily change the simulation or prediction of the wilted biomass,which affects the transformation of the grassland state in the grassland ecosystem.The variance-based approach may underestimate the parameter sensitivity because it only considers the influence of limited parameter samples from a statistical view.This study verifies that the CNOPSA method is effective and feasible for exploring the important and sensitive physical parameters or parameter combinations in numerical models.

Changes in extreme temperature events over the Hindu Kush Himalaya during 1961e2015

This study uses the CMA (China Meteorological Administration) global land-surface daily air temperature dataset V1.0 (GLSATD V1.0) to analyze long-term changes in extreme temperature events over the Hindu Kush Himalaya (HKH) during 1961e2015. Results show there was a significant decrease in the number of extreme cold events (cold nights, cold days, and frost days) but a significant increase in the number of extreme warm events (warm nights, warm days, and summer days) over the entire HKH during 1961e2015. For percentile-based indices, trends of extreme events related to minimum temperature (Tmin) were greater in magnitude than those related to maximum temperature (Tmax). For absolute-value based indices, maximum Tmax, minimum Tmin, and summer days all show increasing trends, while frost days and the diurnal temperature range (DTR) show significant decreasing trends. In addition, there was a decrease in extreme cold events in most parts of east HKH, particularly in Southwest China and the Tibetan Plateau, while there was a general increase in extreme warm events over the entire HKH. Finally, the change in extreme cold events in the HKH appears to be more sensitive to elevation (with cold nights and cold days decreasing with elevation), whereas the change in warm extremes (warm nights, warm days, and maximum Tmax) shows no detectable relationship with elevation. Frost days and minimum Tmin also have a good relationship with elevation, and the trend in frost days decreases with an increase in elevation while the trend in minimum Tmin increases with an increase in elevation.

Trait-based representation of hydrological functional properties of plants in weather and ecosystem models

Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types(PFTs)and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

PMODTRAN:a parallel implementation based on MODTRAN for massive remote sensing data processing

MODerate resolution atmospheric TRANsmission(MODTRAN)is a commercial remote sensing(RS)software package that has been widely used to simulate radiative transfer of electromagnetic radiation through the Earth’s atmosphere and the radiation observed by a remote sensor.However,when very large RS datasets must be processed in simulation applications at a global scale,it is extremely time-consuming to operate MODTRAN on a modern workstation.Under this circumstance,the use of parallel cluster computing to speed up the process becomes vital to this time-consuming task.This paper presents PMODTRAN,an implementation of a parallel task-scheduling algorithm based on MODTRAN.PMODTRAN was able to reduce the processing time of the test cases used here from over 4.4 months on a workstation to less than a week on a local computer cluster.In addition,PMODTRAN can distribute tasks with different levels of granularity and has some extra features,such as dynamic load balancing and parameter checking.

Integrating space and time: a case for phenological context in grazing studies and management

In water-limited landscapes, patterns in primary production are highly variable across space and time.Livestock grazing is a common agricultural practice worldwide and a concern is localized overuse of specific pasture resources that can exacerbate grass losses and soil erosion. On a research ranch in New Mexico with average annual rainfall of 217 mm, we demonstrate with a quantitative approach that annual seasons vary greatly and examine foraging patterns in Angus-Hereford(Bos taurus) cows. We define five seasonal stages based on MODIS NDVI: pre-greenup, greenup, peak green, drydown and dormant, and examine livestock movements in 2008. Daily distance traveled by cows was greater and foraging area expanded during periods with higher precipitation. A regression model including minimum NDVI, rainfall and their interaction explained 81% of the seasonal variation in distance traveled by cows(P < 0.01).Cows explored about 81 ha·d^(–1) while foraging, but tended to explore smaller areas as the pasture became greener(greenup and peak green stages). Cows foraged an average of 9.7 h daily and spent more time foraging with more concentrated search patterns as pastures became greener.Our findings suggest that phenological context can expand the capacity to compare and integrate findings, and facilitate meta-analyses of grazing studies conducted at different locations and times of year.