资源环境与城乡规划管理外文资料翻译.doc

毕业设计外文资料翻译题 目 陆面过程模式CLM的稳定同位素的季节变化仿真 学 院 资源与环境学院 专 业 资源环境与城乡规划管理 班 级 资源0702班 学 生 包芳 学 号 20072102002 指导教师 王永森 二一 一年 三月 二十五 日Simulations of seasonal variations of stable waterisotopes in land surface process model CLMZHANG XinPing1, WANG XiaoYun2, YANG ZongLiang3, NIU GuoYue3 & Xie ZiChu11 College of Resources and Environmental Sciences, Hunan Normal University, Changsha 410081, China;2 Qingdao Meteorological Bureau, Qingdao 266003, China;3 Department of Geological Sciences, the University of Texas at Austin, Texas 78721-0254, USAAbstract: In this study, we simulated and analyzed the monthly variations of stable water isotopes in different reservoirs at Manus, Brazil, using the Community Land Model (CLM) that incorporates stable isotopic effects as a diagnostic tool for understanding stable water isotopic processes, filling the observational data gaps and predicting hydro meteorological processes. The simulation results show that the 18O values in precipitation, vapor and surface runoff have distinct seasonality with the marked negative correlations with corresponding water amount. Compared with the survey results by the InternationalAtomic Energy Agency (IAEA) in co-operation with the World Meteorological Organization (WMO), the simulations by CLM reveal the similar temporal distributions of the18O in precipitation. Moreover, the simulated amount effect between monthly18O and monthly precipitation amount, and MWL (meteoric water line) are all close to the measured values. However, the simulated seasonal difference in the 18O in precipitation is distinctly smaller than observed one, and the simulated temporal distribution of the18O in precipitation displays the ideal bimodal seasonality rather than the observed single one. Thesemismatches are possibly related to the simulation capacity and the veracity in forcing data.Key word : stable water isotope, CLM, simulation, amount effect, seasonal variationThe modeling of the land surface and soil moisture is increasingly seen as an important component in understanding hydrological cycles. Stable water isotopes, for example18O and D, are superlative tracers for the hydrological cycles because their abundance in water reflects the accumulated record of physical phase change. Using the features of stable isotopes can accurately determine the partitioning of precipitation into transpiration, evaporation and runoff, which cannot be detected with mass balance alone. Recently, the conducting iPILPS (isotopes in the Project for Intercomparison of Land-surface Parameterization Schemes) incorporates stable water isotopes into land surface parameterization schemes. The iPILPS experiment aims to identify and test different land-surface schemes that incorporate stable water isotopes, appraise the applicability of stable isotopic data in hydro-climatic study and water resources survey, identify observational data gaps required for evaluating the land-surface schemes with isotopes and apply stable water isotopic data to specific prediction of hydro meteorological processes. This study, a part of iPILPS, incorporates stable water isotopes in CLM as a diagnostic tool, simulates and analyses variations of stable water isotopes in different reservoirs on monthly time scales at Manaus, Brazil. The simulated behaviors of stable isotopes in precipitation on monthly time scale have good consistency with actual survey result at Manaus station set up by IAEA/WMO, howing that the simulation by the CLM incorporating stable water isotopes is reasonable.1 Model description1.1 CLMEarths biosphere is an important part of the Earths climate system. Relatedly, the dynamic, thermodynamic and physiological processes of vegetation coverage are the key factors impacted climate change. These numerical models including physical process parameterizations are called as the land surface process model. Land surface model is composed of different physical processmodes including the parameterization of dynamics characteristics, the longwave and shortwave radiation transfer and rainfall interception, etc. in canopy associated with vegetation shape; photosynthesis, transpiration and evaporation related to plant physiology; and physical process of water-heat conduction, soil chemical processes, freezing and thawing of permafrost within soil, and so on. The Community Land Model (CLM) is currently one of well-developed and potential land surface models. CLM is developed from the Biosphere-AtmosphereTransfer Scheme (BATS), the Institute of Atmospheric Physics, Chinese Academy of Sciences land model (IAP94) and the NCAR land surface model (LSM). The model takes into account ecological differences among vegetation types, hydraulic and thermal differences among soil types, and allows for multiple land cover types within a grid cell. Strictly speaking, CLM is a single point model. According to different physical processes, the model structure can be separated into two parts, the biogeophysical processes relating to vegetation cover at surface and physical processes relating to hydraulic and thermal transfer in soil, mainly including radiation transfer, turbulence diffusion and thermal conduction in soil and so on. Detailed descriptions about CLM may refer to relational references and technical notes.1.2 Stable water isotope parameterizationThe stable isotopic ratio incorporated into CLM is noted as R= (1)The subscription w stands for reservoir water, for example precipitation, runoff or vapor, etc.There are two possible ways of mixing the reservoir water with input, “total mixing” scheme and “partial mixing” scheme:Rw(t) = N1Rw (t 1) + N2Rinputs (t) N (2)N = N1 + N2 (3)in a total mixing, Roverflow (t) = Rw (t) (4)and in a partial mixing, namely as max(N1)N (5) Roverflow (t) = Rinputs (t) (6)where Rinputs is the stable isotopic ratio of any inputs, Roverflow is the ratio of overflow that is the water of exceeding the maximum storage capacity of the reservoir, N1 is the mass of water in reservoir, N2 is the mass of input water, N is the total mass after mixing and t is thetime. As phase change is generated, there will appear fractionation effect of stable isotope. As water evaporating, the stable isotopic ratio in residual water is (7) where f = N1(t) / N1(0) is the fraction of residual water in the reservoir after evaporation event, and = Rw / Rv is the fractionation factor of stable isotopes between liquid and vapor, Rv is the ratio in evaporated vapor. As vapor condensing,Rd = Ra , (8)where Rd and Ra are stable isotopic ratios in dew and in atmospheric vapor, respectively, and is the stable isotopic fractionation factor calculated between liquid and vapor phase.As known, vegetation transpiration does not produce stable isotopic fractionation, thus, the stable isotopic ratio in transpiration equals to that in root region, namelyRtr = Rroot . (9)1.3 Experimental schemeThree sites with different geophysical and climatic conditions are selected for iPILPS Phase 1 experiment. They are Munich, Germany (48.08N, 11.34E), Tumbarumba, Australia (35.49S, 148.01E) located in middle latitudes and Manaus, Brazil (3.08S, 60.01W) in tropical rainforest of South America. Manaus, with an equatorial climate characterized by agreeable temperatures but plenty of rain and humidity, is situated in the heart of Amazons, north of Brazil more than 1450 km inland from the Atlantic. According to statistical data, the annual mean precipitation amountis about 2190 mm at Manaus, with the maximal monthly mean precipitation of 308 mm in April and the minimal mean precipitation of 52 mm in August; the annual mean temperature is 26.8, with the highest monthly mean temperature of 27.9 in October and the lowest monthly mean temperature of 26.0 in March. The survey of stable isotopes in precipitation shows that there is the marked negative correlation between monthly stable isotopic ratios in precipitation and precipitation amount at Manaus. In view of that some variation features of stable isotopes in precipitation at Manaus have comparability with that under monsoon climate in East Asia, the simulation experiment of stable water isotopes was carried out at Manaus.The CLM simulation requires forcing that contains isotopes in precipitation and atmospheric vapor etc. at high resolution (Table 2). These forcing data, commended in iPILPS Phase 1 exclusively, are derived from output of REMOiso (Regional Model with isotopes) at 15-min time step for one ideal year (360 days). For the details on the forcing data see ref. In this experiment, the model iterates a 1-year calculation until differences between the initial and final values decrease below 0.01 mm/a for water storage and 0.01 mm/a RV-SMOW for isotopic species. The simulation year is defined as equilibrium year.1.4 Stable isotopic balanceWater balance is the base of calculating water amount in land surface scheme. Similarly, stable isotopic balance is the base of stable isotopic simulation. The magnitude of stable isotopic ratio in water is related to that in initial origin, e.g. in atmospheric precipitation or in vapor. By averaging the 18O in reservoirs and the specific humidity as well as aggregating the water budgets at 15-min time step, the daily variations of the 18O in reservoirs and corresponding water budgets are obtained (Figure 1). ，Figure 1 The daily variations of the18O in precipitation (a), vapor (b), with the corresponding water budgets from REMOiso as inputs at Manaus, Brazil. In Figure 1, the18O in precipitation and in vapor show all obvious seasonality and the typical isotopic signature in evergreen tropic forest: the heavy rain or the moist atmosphere (great q) is usually depleted in stable isotopes, whereas the light rain or the dry atmosphere (small q) is usually enriched in stable isotopes. Compared with precipitation, vapor is isotopic ally depleted obviously.The soil column is discredited into ten layers with different depths from 0.0175 m to 1.437 m in vertical direction. In this study, the variations of stable water isotopes and water budgets are concerned in super-surface (00.0175 m, the first layer in CLM) and root-region (0.01753.433 m, the 2nd10th layer in CLM).2 Simulation results by CLM2.1 Seasonal variations of 18O and water budgetsin land surface reservoirsOn the monthly time scale, the simulated precipitation, specific humidity and surface runoff show all the obvious bimodal seasonality, which characterizes the climatic regime of equator zones (Figure 2). The primary maximal and minimal precipitation appear respectively in April and in July with their amount difference of 528 mm, and the second maximal and minimal precipitation respectively in December and in January with the amount difference of 170 mm, merely 1/3 of the former amount and only one month in time difference, which is possibly related to the fast moving of the ITCZ in sum mer. Correspondingly, the18O in reservoirs also shows the bimodal seasonality, in which the variations of the18O in precipitation and in surface runoff have similarity: their two maximums appear in January and July and two minimums in April and October, with the negative correlation of stable isotopic ratio with water budget; additionally, in vapor, two maximums of the18O appears in January and August and two minimums of the18O does in April and November. The second extremums are later than that in precipitation and in runoff. Such a result shows that, to a certain degree, the stable isotopes in reservoirs and vapor are impacted not only by large-scale climatic conditions, for example the solar radiation and atmospheric circulation, but also by the vapor origins.Figure 2 The monthly variations of the O in precipitation (a),vapor (b), surface runoff (c), surface dew (d) and surface evaporation (e), with the corresponding water budgets at Manaus, Brazil. The magnitude of surface evaporation is related to atmospheric humidity. Compared Figure 2(e) with 2(b), the evaporation is relatively small at two maximal specific humidity in April and in December, but relatively great at the minimal specific humidity in July. Unlike the behaviors of precipitation, specific humidity and condensation, evaporation shows the weak seasonality and indistinctive correlation with the18O in evaporation.2.2 Seasonal variations of the 18O and waterThe surface infiltration water, originated primarily from atmospheric precipitation, shows a very good consistency with precipitation . As a result, 18the monthly mean18O in infiltration water is positively correlated to that in precipitation, but negatively to infiltration water in accordance with the amount effect. Compared with precipitation, the infiltration water is isotopic ally enriched markedly due to evaporation action.The variation of super-surface soil water is influenced not only by infiltration water but also by mass exchange with root region water and surface evaporation action. Impacted by the storage regulation and peak attenuation actions of soil, the seasonality of super-surface soil water is weakened. Correspondingly, the18O in superurface reservoir displays unclear seasonality and un-marked correlation with super-surface water. However, the surface evaporation keeps isotopic consistency with super-surface reservoir because of drawing water from super-surface soil directly . Comparatively, the evaporated vapor is isotopic ally depleted. The root-region water and the subsurface runoff have all weak seasonality with slightly later time phase than precipitation. Usually, in the rainy season, bigger aquiclude and stronger sub-surface runoff corresponds to the higher water table; and in the dry season, smaller aquiclude and weaker subsurface runoff to the lower water table. Correspondingly, 18O in reservoirs shows that, in the rainy season, the heavy precipitation and the produced strong infiltration have the marked impact on 18O in root-region reservoir and in the decrease of the18Oin root-region reservoir and subsurface run- off is in apparent. Additionally, it can be found that the18Oin subsurface runoff is equal to that in root-region water because the mass complement mainly comes from root-region water.2.3 Seasonal variations of the O and water budgets in canopy reservoir The canopy storage water mainly comes from the precipitation interception by canopy, the replenishment from condensation is less. Therefore, the seasonal variation of the18O in canopy reservoir is consistent with that in precipitation. In accordance with18O in canopy reservoir is in-the amount effect, the versely proportional to the canopy storage water: in the rainy season, more canopy storage water corresponds to18O in reservoir, and in dry season, less canopy lower18O in reservoir. Compared with precipitation, canopy reservoir is isotopically enriched due to evaporation action. Because vegetation transpiration process is considered not to generate isotopic fractionation, the18O variation in canopy transpiration keeps consistent with that in root-region water that furnishes the most of the canopy transpiration. By comparing ,the canopy transpiration varies with contrary to canopy evaporation. In the dry season, the water furnishing to canopy evaporation is less for lighter precipitation, but canopy transpiration is more due to drier atmosphere; in the rainy season, the water furnishing to canopy evaporation is more for heavier precipitation, but canopy transpiration is less due to moister atmosphere.3 Comparison between CLM simulated and actual results Manaus is one of sampling stations attached to the global survey network set by the International Atomic Energy Agency (IAEA) in co-operation with the World Meteorological Organization (WMO). There have been 26-year stable isotopic survey records from 1965 to 1990 (absent from 1993 to 1995) at Manaus (http:/www grams/ri/gnip/gnipmain.htm). On the monthly timescale, there is the marked amount effect between the actual18O in precipitation and precipitation amount with the confidence level above 0.001,and the simulated amount effect has good consistency with the actual that.The relationship betweenD and18O in atmospheric precipitation is called as the meteoric water line (MWL). The actual global MWL by Craig is D = 8.018O +10.0. The slope item of 8.0 stands for comparative relationship of fractionation rates between deuterium and oxygen-18, and the constant item of 10.0 does the deviation degree of the deuterium from that in equilibrium state. They are controlled by all of these phase-change processes from vapor evaporating in its origins to raindrops falling onto surface land. Compared with the global MWL, the actual MWL at Manaus has the slightly great slope and constant items, but the simulated one has the slightly small slope and constant items. 4 Conclusions (1) Similar to the simulated variations of precipitation, specific humidity and surface runoff, the simulated18O in these reservoirs also shows the bimodal seasonality with the marked negative correlations with corresponding water amount. The variation of the18O in dew has very good consistency with that in vapor because dew is condensed from vapor directly. The surface evaporation amount is