The use of satellite information for precomputing the snowmelt runoff hydrograph

A technique is proposed of precomputing the snowmelt runoff hydrograph on the basis of physical and mathematical models of river runoff formation, available standard data of surface hydrometeorological measurements, and satellite measurements of Earth’s surface conditions. The computations were carried out for two regions including the basins of the Vyatka and Don rivers. It is demonstrated that, in spite of the possible errors and gaps depending on meteorological conditions, the satellite snow cover measurements can be an important addition to the surface measurements for simulating a spatial picture of the runoff formation. The use of physical and mathematical models of the runoff formation enables to reduce the errors of satellite snow cover data and to ensure the spatiotemporal continuity of its monitoring.     

Treatment of frozen soil and snow cover in the land surface model SEWAB

Summary  The land surface model SEWAB (Surface Energy and Water Balance) is designed to be coupled to both, atmospheric and hydrological models. Its application in mid and high latitudes requires the inclusion of freezing and thawing processes within the soil and the accumulation and ablation of a snow cover. These winter processes are parameterised with a minimum number of empirical formulations in order to assure reasonable computation times for an application in climate and sensitivity studies yet accounting for all important processes. Meteorological forcing data and measurements of snow depth, soil temperature and liquid soil water content at two locations in the mid-west of North America are used to test the model. Generally the simulated snow depth matches the measurements, remaining differences in snow depth can be explained by uncertainties in snow density, blowing snow and errors in precipitation measurements. The simulated soil temperature and liquid soil water content compare well with the measurements, showing the isolating effect of the snow cover. Received August 25, 2000 Revised January 19, 2001     

Hydrologic Sensitivity of Global Rivers to Climate Change

Climate predictions from four state-of-the-art general circulation models (GCMs) were used to assess the hydrologic sensitivity to climate change of nine large, continental river basins (Amazon, Amur, Mackenzie, Mekong, Mississippi, Severnaya Dvina, Xi, Yellow, Yenisei). The four climate models (HCCPR-CM2, HCCPR-CM3, MPI-ECHAM4, and DOE-PCM3) all predicted transient climate response to changing greenhouse gas concentrations, and incorporated modern land surface parameterizations. Model-predicted monthly average precipitation and temperature changes were downscaled to the river basin level using model increments (transient minus control) to adjust for GCM bias. The variable infiltration capacity (VIC) macroscale hydrological model (MHM) was used to calculate the corresponding changes in hydrologic fluxes (especially streamflow and evapotranspiration) and moisture storages. Hydrologic model simulations were performed for decades centered on 2025 and 2045. In addition, a sensitivity study was performed in which temperature and precipitation were increased independently by 2 °C and 10%, respectively, during each of four seasons. All GCMs predict a warming for all nine basins, with the greatest warming predicted to occur during the winter months in the highest latitudes. Precipitation generally increases, but the monthly precipitation signal varies more between the models than does temperature. The largest changes in the hydrological cycle are predicted for the snow-dominated basins of mid to higher latitudes. This results in part from the greater amount of warming predicted for these regions, but more importantly, because of the important role of snow in the water balance. Because the snow pack integrates the effects of climate change over a period of months, the largest changes occur in early to mid spring when snow melt occurs. The climate change responses are somewhat different for the coldest snow dominated basins than for those with more transitional snow regimes. In the coldest basins, the response to warming is an increase of the spring streamflow peak, whereas for the transitional basins spring runoff decreases. Instead, the transitional basins have large increases in winter streamflows. The hydrological response of most tropical and mid-latitude basins to the warmer and somewhat wetter conditions predicted by the GCMs is a reduction in annual streamflow, although again, considerable disagreement exists among the different GCMs. In contrast, for the high-latitude basins increases in annual flow volume are predicted in most cases.     

The surface energy balance of a snow cover: comparing measurements to two differentsimulation models

Summary  We compared two one-dimensional simulation models for heat and water fluxes in the soil-snow-atmosphere system with respect to their mathematical formulations of the surface heat exchange and the snow pack evolution. They were chosen as examples of a simple one-layer snow model and a more detailed multiple-layer snow model (SNTHERM). The snow models were combined with the same one-dimensional model for the heat and water balance of the underlying soil (CoupModel). Data from an arable field in central Sweden (Marsta), covering two years (1997–1999) of soil temperature, snow depth and eddy-correlation measurements were successfully compared with the models. Conditions with a snow pack deeper or shallower than 10 cm and bare soil resulted in similar discrepancies. The simulated net radiation and sensible heat flux were in good agreement with that measured during snow-covered periods, except for situations with snowmelt when the downward sensible heat flux was overestimated by 10–20 Wm⁻². The results showed that the uncertainties in parameter values were more important than the model formulation and that both models were useful in evaluating the limitations and uncertainties of the measurements. Received November 1, 1999 Revised April 20, 2000     

High latitude river runoff in a doubled CO2 climate

A global atmospheric model is used to calculate the monthly river flow for nine of the world's major high latitude rivers for the present climate and for a doubled CO₂ climate. The model has a horizontal resolution of 4° × 5°, but the model's runoff from each grid box is quartered and added to the appropriate river drainage basin on a 2° × 2.5° resolution. A routing scheme is used to move runoff from a grid box to its neighboring downstream grid box and ultimately to the mouth of the river. In a model simulation in which atmospheric carbon dioxide is doubled, mean annual precipitation and river flow increase for all of these rivers, increased outflow at the river mouths begins earlier in the spring, and the maximum outflow occurs approximately one month sooner due to an earlier snow melt season. In the doubled CO₂ climate, snow mass decreases for the Yukon and Mackenzie rivers in North America and for rivers in northwestern Asia, but snow mass increases for rivers in northeastern Asia.     

Characterizing the distribution of observed precipitation and runoff over the continental United States

This paper describes the development of a comprehensive geographic database of historical precipitation and runoff measurements for the conterminous U.S. The database is used in a spatial analysis to characterize large scale precipitation and runoff patterns and to assess the utility and limitations of using historical hydro-meteorological data for providing spatially distributed precipitation estimates at regional and continental scales. Long-term annual average precipitation (P) and runoff (Q) surfaces (geographically referenced, digital representations of a continuous spatial distribution) generated from interpolation of point measurements are used in a distributed water balance calculation to check the reliability of precipitation estimates. The resulting input-output values (P- Q) illustrate the deficiency (sparse distribution and low elevation bias) of historical precipitation measurements in the mountainous western U.S. where snowmelt is an important component of the annual runoff. The incorporation of high elevation snow measurements into the precipitation record significantly improves the water balance estimates in some areas and enhances the utility of historical data for providing spatially distributed precipitation estimates in topographically diverse regions. Regions where the use of historical precipitation data may be most limited for precipitation estimation are identified and alternatives to the use of interpolated historical data for precipitation estimation across large heterogenous regions are suggested. The research establishes a database for continental scale studies and provides direction for the successful development of spatially distributed regional scale water balance models.     

On improving cold region hydrological processes in the Canadian Land Surface Scheme

Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990–2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.     

A new snow parameterization for the Météo-France climate model

Both observational and numerical studies demonstrate the sensitivity of the atmosphere to variations in the extent and mass of snow cover. There is therefore a need for simple but realistic snow parameterizations in forecast and climate models. A new snow hydrology scheme has recently been developed at Météo-France for use in the ARPEGE climate model and has been successfully tested against local field measurements in stand-alone experiments. This study describes the global validation of the parameterization in a 3-year integration for the present-day climate within the T42L30 version of ARPEGE. Results are compared with those from a control simulation and with available observed climatologies, in order to assess the impact of the new snow parameterization on the simulated surface climate. The seasonal cycle of the Northern Hemisphere snow cover is clearly improved when using the new scheme. The snow pack is still slightly overestimated in winter, but its poleward retreat is better reproduced during the melting season. As a consequence, the modified GCM performs well in simulating the springtime continental heating, which may play a strong role in the simulation of the Asian summer monsoon.     

Implications of 21st century climate change for the hydrology of Washington State

Pacific Northwest (PNW) hydrology is particularly sensitive to changes in climate because snowmelt dominates seasonal runoff, and temperature changes impact the rain/snow balance. Based on results from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), we updated previous studies of implications of climate change on PNW hydrology. PNW 21st century hydrology was simulated using 20 Global Climate Models (GCMs) and 2 greenhouse gas emissions scenarios over Washington and the greater Columbia River watershed, with additional focus on the Yakima River watershed and the Puget Sound which are particularly sensitive to climate change. We evaluated projected changes in snow water equivalent (SWE), soil moisture, runoff, and streamflow for A1B and B1 emissions scenarios for the 2020s, 2040s, and 2080s. April 1 SWE is projected to decrease by approximately 38–46% by the 2040s (compared with the mean over water years 1917–2006), based on composite scenarios of B1 and A1B, respectively, which represent average effects of all climate models. In three relatively warm transient watersheds west of the Cascade crest, April 1 SWE is projected to almost completely disappear by the 2080s. By the 2080s, seasonal streamflow timing will shift significantly in both snowmelt dominant and rain–snow mixed watersheds. Annual runoff across the State is projected to increase by 2–3% by the 2040s; these changes are mainly driven by projected increases in winter precipitation.     

Improvement of a Snow Albedo Parameterization in the Snow–Atmosphere–Soil Transfer Model:Evaluation of Impacts of Aerosol on Seasonal Snow Cover

The presence of light-absorbing aerosols(LAA) in snow profoundly influence the surface energy balance and water budget.However,most snow-process schemes in land-surface and climate models currently do not take this into consideration.To better represent the snow process and to evaluate the impacts of LAA on snow,this study presents an improved snow albedo parameterization in the Snow–Atmosphere–Soil Transfer(SAST) model,which includes the impacts of LAA on snow.Specifically,the Snow,Ice and Aerosol Radiation(SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme.The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot(SASP),Colorado,USA.Results show that the snow albedo and snow depth are better reproduced than those in the original SAST,particularly during the period of snow ablation.Furthermore,the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack,with or without LAA.The LAA particles directly absorb extra solar radiation,which accelerates the growth rate of the snow grain size.Meanwhile,these larger snow particles favor more radiative absorption.The average total radiative forcing of the LAA at the SASP is 47.5Wm~(-2).This extra radiative absorption enhances the snowmelt rate.As a result,the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier,respectively,which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.     

Hydrologic effects of climate change in the Yukon River Basin

A monthly water balance (WB) model was developed for the Yukon River Basin (YRB). The WB model was calibrated using mean monthly values of precipitation and temperature derived from the Precipitation-elevation Regression on Independent Slopes Model (PRISM) data set and by comparing estimated mean monthly runoff with runoff measured at Pilot Station, Alaska. The calibration procedure used the Shuffled Complex Evolution global search. Potential hydrologic effects of climate change were assessed for the YRB by imposing changes in precipitation and temperature derived from selected Inter-governmental Panel for Climate Change (IPCC) climate simulations. Scenarios from five general circulation model (GCM) simulations were used to provide a range of potential changes. Results from the scenarios indicate an increase in annual runoff in the twenty-first century for the YRB with simulated increases in precipitation having the greatest effect on increases in runoff. Simulated increases in temperature were found to alter the timing of snow accumulation and melt.     

Energy and water balance studies of a snow cover during snowmelt period at a high arctic site

Summary  The predicted global warming is supposed to have an enhanced effect on the arctic regions. How this will influence the water, carbon dioxide and methane balances in the European arctic tundra is the objective of the EU-funded project “Understanding Land Surface Physical Processes in the Arctic” (LAPP), to which where SINTEF is one of several contributors. The snow cover is one of the limiting factors for these exchange processes and knowledge of how it behaves and will behave under a different climate is important. Data collected for water and energy balance studies in an area close to Ny-?lesund at 79°N at Svalbard are the basis of this study. Measurements during the ablation periods since 1992 show an average air temperature for the periods of 2.1 °C, an average incoming shorwave radiation of 230 W/m² and an average measured runoff intensity of 14 mm/day with a maximum of 68 mm/day. Three models of different complexity are tested in order to simulate the water and energy balance of a snow cover on the arctic tundra. The three models are: a complex numerical model (CROCUS), a simple energy balance model and a temperature index model. The simulations were carried out for the melt periods in 1992 and 1996 as these two periods represent very different meteorological conditions. The results of these simulations exposed weaknesses in all the models. The energy balance model lacks calculation of cold content in the snowpack. This influences both the outgoing longwave radiation and the timing of the melt. Due to the effect of compensating errors in the simulations, CROCUS performed better than the simple energy balance model but also this model has problems with the simulation of outgoing longwave radiation. The temperature index model does not perform well for snowmelt studies in regions were radiation is the main driving energy source for the melt. Received September 28, 1999 Revised September 18, 2000     

The potential impact of climate change on seasonal snow in New Zealand: part I—an analysis using 12 GCMs

Seasonal snow directly affects New Zealand??s economy through the energy, agriculture and tourism sectors. In New Zealand, little is known about the long-term variability of the snow cover and the expected impacts of climate change on snow cover. The lack of systematic historical snow observations in New Zealand means that information on interannual variability, trends and projections of future seasonal snow must be generated using simulation models. We use a temperature index snow model to calculate the accumulation and ablation of the current (1980?C1999) snowpack for more than 37,000 third-order river basins with 100?m contour intervals, resulting in over 200,000 individual model elements in New Zealand. Using this model, which captures the gross features of snow under the current climate, we assess the range of likely effects of climate change on seasonal snow in New Zealand using downscaled temperature and precipitation changes from the middle of the road (A1B) climate change projections from 12 general circulation models (GCMs). For each of the 12 GCMs, we consider two future time periods 2030?C2049 (mid-point reference 2040) and 2080?C2099 (mid-point reference 2090). These future time periods are compared to simulations of current, 1980?C1999 (mid-point reference 1990), seasonal snow. Our results show that on average at a national scale, at nearly all elevations, the 2040s and 2090s result in a decrease in snow as described by all of our summary statistics: snow duration, percentage of precipitation that is snow and peak snow accumulation in each year. This decrease in snow is more marked at elevations below 1,000?m but is evident at all but the very highest elevations. Relative to snow simulations for average peak snow accumulation for the present, we observe that by the 2040s, depending on the GCM used, there is a reduction of between 3 and 44?% at 1,000?m, and an increase of 8?% through to a reduction of 22?% at 2,000?m. By the 2090s, the average reduction is greater, with a decrease of between 32 and 79?% at 1,000?m and between 6 and 51?% at 2,000?m. More substantial reductions are observed below these elevations. When we consider the elevation where snow duration exceeds 3?months, we see a rise in this elevation from 1,550?m in the 1990s to between 1,550 and 1,750?m by the 2040s and 1,700 and 2,000?m by the 2090s, depending on the GCM used. The results of this work are consistent with our understanding of snow processes in general and with work from other similar mid-latitude locations.     

Parametrization schemes of incident radiation in the North Water polynya

Abstract

An evaluation of the Canadian Land Surface Scheme (CLASS) 3.1 snow cover simulations at four sites included in the Snow Model Intercomparison Project (SnowMIP) revealed that CLASS was able to provide realistic representations of snow cover accumulation, melt and physical properties over a range of snow cover climates. The modified snow aging parametrization in CLASS 3.1 provided improved simulations of snowpack density which resulted in a marked reduction in the root‐mean‐square (rms) error for daily snow depth, and slight improvements in snow surface temperature. CLASS 3.1 still exhibited a tendency to overestimate snow cover duration which is attributed to the way shallow snow ablation is treated. CLASS provided generally realistic simulations of daily and seasonal variation in snow albedo although cold snow albedo was underpredicted by 0.10 to 0.15 at a site with a deep (> 2 m) cold snowpack. CLASS also exhibited a tendency to overpredict late spring snow albedo which was reduced by the addition of a snow layer subroutine that kept track of snow albedo by precipitation event. CLASS had a noticeable cold bias averaging 3°–4°C at two mountain sites included in the comparison. The bias was closely linked to atmospheric stability and could exceed 10°C under conditions of strong radiative cooling and low wind speeds. The CLASS energy deficit under these conditions was determined to be ～20–40 W m^?2 and was mostly accounted for by introducing a windless exchange coefficient into the calculation of sensible heat fluxes following the approach used in a number of other physical snowpack models. CLASS provided realistic simulations of daily snowmelt runoff with the exception of the Weissfluhjoch site which was characterized by a deep cold snowpack. A preliminary assessment of snow water equivalent (SWE) rms error for the 23 models participating in SnowMIP showed that CLASS was one of the better single layer snow models included in the comparison. CLASS performance was comparable to the multi‐layer CROCUS snowpack model in the evaluations carried out in this study.     

Great Lakes Hydrology Under Transposed Climates

Historical climates, based on 43 years of daily data from areas south and southwest of the Great Lakes, were used to examine the hydrological response of the Great Lakes to warmer climates. The Great Lakes Environmental Research Laboratory used their conceptual models for simulating moisture storages in, and runoff from, the 121 watersheds draining into the Great Lakes, over-lake precipitation into each lake, and the heat storages in, and evaporation from, each lake. This transposition of actual climates incorporates natural changes in variability and timing within the existing climate; this is not true for General Circulation Model-generated corrections applied to existing historical data in many other impact studies. The transposed climates lead to higher and more variable over-land evapotranspiration and lower soil moisture and runoff with earlier runoff peaks since the snow pack is reduced up to 100%. Water temperatures increase and peak earlier. Heat resident in the deep lakes increases throughout the year. Buoyancy-driven water column turnover frequency drops and lake evaporation increases and spreads more throughout the annual cycle. The response of runoff to temperature and precipitation changes is coherent among the lakes and varies quasi-linearly over a wide range of temperature changes, some well beyond the range of current GCM predictions for doubled CO₂ conditions.     

Validation and sensitivity of the global hydrologic budget in stand-alone simulations with the ISBA land-surface scheme

 Global soil moisture data of high quality and resolution are not available by direct observation, but are useful as boundary and initial conditions in comprehensive climate models. In the framework of the GSWP (Global Soil Wetness Project), the ISBA land-surface scheme of Météo-France has been forced with meteorological observations and analyses in order to study the feasibility of producing a global soil wetness climatology at a 1°×1° horizontal resolution. A control experiment has been performed from January 1987 to December 1988, using the ISLSCP Initiative I boundary conditions. The annual mean, the standard deviation and the normalised annual harmonic of the hydrologic fields have been computed from the 1987 monthly results. The global maps which are presented summarise the surface hydrologic budget and its annual cycle. The soil wetness index and snow cover distributions have been compared respectively to the results of the ECMWF reanalysis and to satellite and in situ observations. The simulated runoff has been validated against a river flow climatology, suggesting a possible underestimation over some large river basins. Besides the control run, other simulations have been performed in order to study the sensitivity of the hydrologic budget to changes in the surface parameters, the precipitation forcing and the runoff scheme. Such modifications have a significant impact on the partition of total precipitation into evaporation and runoff. The sensitivity of the results suggests that soil moisture remains one of the most difficult climatological parameters to model and that any computed soil wetness climatology must be considered with great caution. Received: 3 January 1997 / Accepted: 19 August 1987     

Use of atmospheric radiation measurement program data from Barrow, Alaska, for evaluation and development of snow-albedo parameterizations

Summary Snow albedo is determined from the ratio of out-going to incoming solar radiation using three years of broadband shortwave radiometer data obtained from the Barrow, Alaska, Atmospheric Radiation Measurement (ARM) site. These data are used for the evaluation of various types of snow-albedo parameterizations applied in numerical weather prediction or climate models. These snow-albedo parameterizations are based on environmental conditions (e.g., air or snow temperature), snow related characteristics (e.g., snow depth, snow age), or combinations of both. The ARM data proved to be well suited for snow-albedo evaluation purposes for a low-precipitation tundra environment. The evaluation confirms that snow-age dependent parameterizations of snow albedo work well during snowmelt, while parameterizations considering meteorological conditions often perform better during snow accumulation. Current difficulties in parameterizing snow albedo occur for long episodes of snow-event free conditions and episodes with a high frequency of snow events or strong snowfall. In a further step, the first two years of the ARM albedo dataset is used to develop a snow-albedo parameterization, and the third year’s data serves for its evaluation. This parameterization considers snow depth, wind speed, and air temperature which are found to be significant parameters for snow-albedo modeling under various conditions. Comparison of all evaluated snow-albedo parameterizations with this new parameterization shows improved snow-albedo prediction. Correspondence: Nicole M?lders, Geophysical Institute and College of Natural Science and Mathematics, University of Alaska Fairbanks, 903 Koyukuk Drive, P.O. Box 757320, Fairbanks, AK 99775-7320, USA     

气侯变化背景下黑河上游春季融雪洪水预估研究

气候变暖将导致高山区冰冻圈加剧融化,一方面融水资源时空分布的不确定性增大;另一方面,融水洪水灾害发生的频度和强度也将发生改变。基于气象、水文数据和MODIS积雪覆盖数据,利用融雪径流模型(SRM),对1990—2012年共23年祁连山黑河札马什克控制区融雪期径流进行模拟与验证。结果表明：SRM在该流域具有较高的模拟精度（纳什系数为0.91),可用于分析和预估控制区径流强度变化。为此,采用黑河流域气温、降水降尺度数据,预估了未来气候变化背景下积雪范围变化及不同重现期洪水变化趋势。结果显示,与基准期相比,在RCP2.6、RCP4.5和RCP8.5情景下,最大积雪范围可减小3%~7%,且随着海拔升高,变化愈剧烈。RCP2.6情景下因气温和降水变化幅度较小,到21世纪末各重现期洪水强度保持在10%以内波动;RCP4.5情景下,各重现期洪水强度最高增大约20%;在RCP8.5情景下,各重现期洪水强度最高可增大超30%。相关分析结果显示,不同重现期洪水径流与气温和降水均具有较强相关性：重现期越长,洪峰与气温的相关性越大;重现期越短,洪峰与降水的相关性越大。通过预估气候变化背景下的融雪性洪水事件强度及重现期变化,有助于有效开展区域洪水风险管理、提高洪水资源的利用价值。     

Snow-albedo feedback and Swiss spring temperature trends

We quantify the effect of the snow-albedo feedback on Swiss spring temperature trends using daily temperature and snow depth measurements from six station pairs for the period 1961?C2011. We show that the daily mean 2-m temperature of a spring day without snow cover is on average 0.4?°C warmer than one with snow cover at the same location. This estimate is comparable with estimates from climate modelling studies. Caused by the decreases in snow pack, the snow-albedo feedback amplifies observed temperature trends in spring. The influence is small and confined to areas around the upward-moving snow line in spring and early summer. For the 1961?C2011 period, the related temperature trend increases are in the order of 3?C7?% of the total observed trend.     

Sensitivity of evapotranspiration in a wheat field,a forest,and a grassland to changes in climate and direct effects of carbon dioxide

Micrometeorological and physiological measurements were used to develop Penman-Monteith models of evapotranspiration for a wheat field in eastern Nebraska, a forest in Tennessee, and a grassland in east-central Kansas. The model fit the measurements well over the periods of observation. Model sensitivities to changes in climatic and physiological parameters were then analyzed. The range of changes considered was established from recent general circulation model output and from review of recent plant physiological research. Finally, climate change scenarios produced by general circulation models for the locations and seasons matching the observed data were applied to the micrometeorological models. Simulation studies show that when all climatic and plant factors are considered, evapotranspiration estimates can differ greatly from those that consider only temperature. Depending on ecosystem and on climate and plant input used, evapotranspiration can differ from the control (no climate or plant change) by about -20 to +40%.