Community Land Model Version Research Articles

How can biosphere models simulate enough vegetation biomass in the mountains of the western United States? Implications of meteorological forcing

Most carbon stocks and fluxes in the western United States are found in mountainous terrain, where observations and modeling are difficult. Terrestrial biosphere models generally underestimate above-ground biomass (AGB) over this region. Here, we identify methods to reduce this underestimation by focusing upon 1) biases in meteorological datasets, 2) model representation of water stress, and 3) spatial resolution. We adopted the widely-used Community Land Model version 4.5 (CLM 4.5) with six different meteorological datasets and found a 6-fold variation in simulated AGB across Utah/Colorado. Simulations underestimated AGB because of warm and dry biases within the meteorological datasets that reduced water availability and restricted plant growth. To eliminate the AGB underestimation we adopted a meteorological dataset designed for complex terrain (gridMET), combined with a representation of plant hydraulic stress (CLM 5.0). Conversely, changes in spatial resolution (meteorological variables and land surface description) had negligible impact on simulated AGB.

Simulation of Northeast Monsoon in a coupled regional model framework

The rainfall during Northeast Monsoon (NEM) meets most of the water demand and influences the socioeconomic condition of the population in the southern part of India. The present study focuses to identify a better, coupled land-atmosphere combination using regional downscaling experiments with RegCM4 for representing the mean characteristics of the NEM rainfall. Three suites of model integrations are made using three different land-surface schemes such as Biosphere-Atmosphere Transfer Scheme (BATS), Subgrid-BATS (SUB), and Community Land Model version 4.5 (CLM). The CLM experiment shows a better spatial representation of the rainfall due to the better representation of the moisture flux and convection, whereas the BATS and SUB experiments show strong wet bias (1–6 mm/yr) over Tamilnadu and Kerala. The spatial correlation of the climatological rainfall with respect to observation is maximum (0.5–0.6) for the CLM. However, the model experiments fail to reproduce the interannual variability of rainfall. The better representation of climatological rainfall, evaporation and turbulent fluxes (sensible and latent heat flux) leads to an improved temperature climatology in the CLM experiment. The study illustrates that the CLM land-surface scheme performs better in representing the northeast monsoon as compared to others however there is a need to explore avenues for further improvements in the performance of the coupled model framework.

The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0

Terrestrial evapotranspiration (ET) is a critical component of water and energy cycles, and improving global land evapotranspiration is one of the challenging works in the development of land surface models (LSMs). In this study, we apply a bias correction approach into the Community Land Model version 5.0 (CLM5) globally by utilizing the remote sensing-based ET dataset. Results reveal that the correction approach can alleviate both overestimation and underestimation of ET by CLM5 over the globe. The adjustment to overestimation is generally effective, whereas the effectiveness for underestimation is determined by the ET regime, namely water-limited or energy-limited. In the areas with abundant precipitation, the underestimation is effectively corrected by increasing ET without the water supply limit. In areas with rare precipitation, however, increasing ET is limited by water supply, which leads to an undesirable correction effect. Compared with the ET simulated by CLM5, the bias correction approach can reduce the global-averaged relative bias (RB) and the root mean square error (RMSE) by 51.8% and 65.9% against Global Land Evaporation Amsterdam Model (GLEAM) ET data, respectively. Meanwhile, the correlation coefficient (CC) can also be improved from 0.93 to 0.98. Continentally, the most substantial ET improvement occurs in Asia, with the RB and RMSE decreased by 69.7% (from 7.04% to 2.14%) and 70.2% (from 0.312 mm day−1 to 0.093 mm day−1, equivalent to from 114 mm year−1 to 34 mm year−1), and the CC increased from 0.92 to 0.99, respectively. Consequently, benefiting from the improvement of ET, the simulations of runoff and soil moisture are also improved over the globe and each of the six continents, and the improvement varies with region. This study demonstrates that the use of satellite-based ET products is beneficial to hydrological simulations in land surface models over the globe.

Global warming induces significant changes in the fraction of stored precipitation in the surface soil

The fraction of stored precipitation (FSP) in surface soil is a new metric to characterize the synoptic-scale dynamics of wet soil moisture anomaly, the impact of which on the atmosphere differs from that of dry anomaly. Investigating the response of FSP to global warming is essential for understanding the land-atmosphere coupling and hydroclimate predictability in a changing climate. Here we use the Coupled Model Intercomparison Project phase 6 (CMIP6) models to project future changes in global FSP under two shared socioeconomic pathway (SSP) scenarios. The historical simulation based on Community Land Model version 5 (CLM5) during 1951–2014 suggests that 14.4% of the global land precipitation is remained in the surface soil within 3 days. The CLM5 simulated FSP applies to validate CMIP6 historical simulations in terms of global mean, spatial correlation and variability, and 5 among 12 CMIP6 models are finally selected to estimate FSP changes in a warming future. Compared with the FSP during the end of 20th century, it increases (decreases) significantly over 29% (16%) of the global land areas after 100 years in the business-as-usual scenario (SSP245). Global warming will increase FSP significantly over Amazon, most of Europe, western USA and Tibet Plateau, while the FSP decreases significantly over India and West Africa due to the increase of precipitation and soil moisture. The changes are more significant in the non-mitigation scenario (SSP585). The projected changes in FSP imply changes in regional flood risk and predictability in a warming future.

Mycorrhizal Distributions Impact Global Patterns of Carbon and Nutrient Cycling

AbstractMost tree species predominantly associate with a single type of mycorrhizal fungi, which can differentially affect plant nutrient acquisition and biogeochemical cycling. Uncertainties in mycorrhizal distributions are non‐trivial, and current estimates disagree in up to 50% over 40% of the land area, including tropical forests. Remote sensing capabilities for mycorrhizal detection show promise for refining these estimates further. Here, we address for the first time the impact of mycorrhizal distributions on global carbon and nutrient cycling. Using the state‐of‐the‐art carbon‐nitrogen economics within the Community Land Model version 5, we found Net Primary Productivity (NPP) increased throughout the 21st century by 20%; however, as soil nitrogen has progressively become limiting, the costs to NPP for nitrogen acquisition—that is, to mycorrhizae—have increased at a faster rate by 60%. This suggests that nutrient acquisition will increasingly demand a higher portion of assimilated carbon to support the same productivity.

On the Influence of Vegetation Cover Changes and Vegetation-Runoff Systems on the Simulated Summer Potential Evapotranspiration of Tropical Africa Using RegCM4

The community land model version 4.5 provides two ways for treating the vegetation cover changes (a static versus an interactive) and two runoff schemes for tracking the soil moisture changes. In this study, we examined the sensitivity of the simulated boreal summer potential evapotranspiration (PET) to the aforementioned options using a regional climate model. Three different experiments with each one covering 16 years have been performed. The two runoff schemes were designated as SIMTOP (TOP) and variable infiltration capacity (VIC). Both runoff schemes were coupled to the carbon–nitrogen (CN) module, thus the vegetation status can be influenced by soil moisture changes. Results show that vegetation cover changes alone affect considerably the simulated 2-m mean air temperature (T2M). However, they do not affect the global incident solar radiation (RSDS) and PET. Conversely to the vegetation cover changes alone, the vegetation-runoff systems affect both the T2M and RSDS. Therefore, they considerably affect the simulated PET. Also, the CN-VIC overestimates the PET more than the CN-TOP compared to the Climatic Research Unit observational dataset. In comparison with the static vegetation case and CN-VIC, the CN-TOP shows the least bias of the simulated PET. Overall, our results show that the vegetation-runoff system is relevant in constraining the PET, though the CN-TOP can be recommended for future studies concerning the PET of tropical Africa.

On the sensitivity of the Amazon surface climate to two land‐surface hydrology schemes using a high‐resolution regional climate model (RegCM4)

AbstractTwo 11‐year simulations were conducted to investigate the influence of two runoff schemes in the community land model version 4.5 (CLM45) on the Amazon surface energy balance and surface climate using a high‐resolution regional climate model (RegCM4‐CLM45). The default scheme is TOPMODEL (TOP), while the alternative is Variable Infiltration Capacity (VIC). In the two simulations, the vegetation status is prescribed (satellite phenology; SP). The first simulation was designated as SP‐TOP, while the second simulation was referred to as SP‐VIC, and both of them were evaluated using reanalysis products (e.g., ERA5) and micrometeorology data measurements. Results show that the SP‐VIC severely underestimates latent heat and overestimates sensible heat fluxes, more than SP‐TOP in comparison with the ERA5. This explains the large warm bias observed in the winter season. On the other hand, the SP‐VIC shows a slightly smaller dry bias than SP‐TOP against the Climate Research Unit (CRU) data. Our results show that SP‐VIC does not improve the quality of the simulation compared to SP‐TOP, which suggests the necessity of additional calibration of the VIC surface parameters using in situ observations of the Amazon and revising the VIC runoff scheme to perform new sensitivity experiments. The same needs to be done with SP‐TOP.

Improved Runoff Simulations for a Highly Varying Soil Depth and Complex Terrain Watershed in the Loess Plateau with the Community Land Model Version 5

Improved Runoff Simulations for a Highly Varying Soil Depth and Complex Terrain Watershed in the Loess Plateau with the Community Land Model Version 5

The Importance of Subsurface Processes in Land Surface Modeling over a Temperate Region: An Analysis with SMAP, Cosmic Ray Neutron Sensing and Triple Collocation Analysis

Land surface models (LSMs) simulate water and energy cycles at the atmosphere–soil interface, however, the physical processes in the subsurface are typically oversimplified and lateral water movement is neglected. Here, a cross-evaluation of land surface model results (with and without lateral flow processes), the National Aeronautics and Space Administration (NASA) Soil Moisture Active/Passive (SMAP) mission soil moisture product, and cosmic-ray neutron sensor (CRNS) measurements is carried out over a temperate climate region with cropland and forests over western Germany. Besides a traditional land surface model (the Community Land Model (CLM) version 3.5), a coupled land surface-subsurface model (CLM-ParFlow) is applied. Compared to CLM stand-alone simulations, the coupled CLM-ParFlow model considered both vertical and lateral water movement. In addition to standard validation metrics, a triple collocation (TC) analysis has been performed to help understanding the random error variances of different soil moisture datasets. In this study, it is found that the three soil moisture datasets are consistent. The coupled and uncoupled model simulations were evaluated at CRNS sites and the coupled model simulations showed less bias than the CLM-standalone model (−0.02 cm3 cm−3 vs. 0.07 cm3 cm−3), similar random errors, but a slightly smaller correlation with the measurements (0.67 vs. 0.71). The TC-analysis showed that CLM-ParFlow reproduced better soil moisture dynamics than CLM stand alone and with a higher signal-to-noise ratio. This suggests that the representation of subsurface physics is of major importance in land surface modeling and that coupled land surface-subsurface modeling is of high interest.

Global Freshwater Storage Capability across Time Scales in the GRACE Satellite Era

Freshwater is recharged mainly by rainfall and stored inland for a period of time, which is directly affected by its storage capability. The storage capability of river basins has different spatiotemporal features that are important for the predictability of freshwater resources. However, the estimation of freshwater storage capability (FSC) remains a challenge due to the lack of observations and quantification indices. Here, we use a metric that characterizes hydrological “inertia” after rainfalls to analyze FSC over the 194 largest global major river basins based on satellite observations from the Gravity Recovery and Climate Experiment (GRACE) and simulations from the Community Land Model version 5 (CLM5). During 2003–16, the global land was observed to retain 28% of precipitation after one month based on GRACE observations, and the simulation depicts that the retained proportions decrease from 42% after one day to 26% after one month, with smaller FSC partly attributed to wetter conditions and higher vegetation densities. The root zone contributes about 40% to the global land FSC on daily to monthly time scales. As the time scale increases, the contribution from the surface soil decreases from 26% to 14%, while the contribution from the deep soil increases from 4% to 10%. Snow contributes over 20% of land FSC, especially over high latitudes. With six decades of CLM5 long-term simulations, it is revealed that the change of FSC in most basins is related to internal climate variability. The FSC of river basins which displays the proportion of precipitation retained on land is worthy of further attention regarding the predictability of water resources.

On the role of a coupled vegetation-runoff system in simulating the tropical African climate: a regional climate model sensitivity study

The role of vegetation-runoff system—in simulating the tropical African climate—was examined by analysing two 13-year simulations with two runoff schemes of the community land model version 4.5 (CLM45): the default one is TOPMODEL (TOP) and the other one is the Variable Infiltration Capacity (VIC) using a regional climate model (RegCM4-CLM45). In both simulations, the carbon-nitrogen (CN) module was activated. The first simulation was referred to as CN-TOP, while the second one was designated as CN-VIC. Overall, the results showed that the CN-VIC severely decreases the leaf area index (LAI), vegetation transpiration and soil evaporation relative to the CN-TOP. Eventually, it severely underestimates the total evapotranspiration but overestimates the sensible heat flux in comparison with the reanalysis product; meanwhile the CN-TOP opposes this effect. As a result, the CN-TOP shows a strong cold bias, and the CN-VIC shows a slightly warm bias in comparison with the observation. Moreover, enabling the interactive vegetation module leads to intensifying the dry bias of the total surface precipitation in both simulations with respect to the static vegetation case against the reanalysis product; however the CN-VIC still outperforms the CN-TOP in comparison with the observations. In conclusion, the coupled vegetation-runoff system has a strong influence on the tropical African climate relative to the static case, and calibrating the four parameters of the VIC surface dataset ensures a better and more reliable performance of the coupled RegCM4-CLM45-CN-VIC model for simulating the tropical African climate.

Modulated Responses of East Asian Winter Climate to Anthropogenic Aerosols by Urban Cover in Eastern China

The increasing anthropogenic aerosols (AAs) over East Asia have caused significant regional climate responses, but the role of urban land-use changes which occur simultaneously, in altering these AA-induced changes, is not well understood. Here, the modulation of the AAs’ effect on the East Asian winter (November–January) climate by the urban cover in eastern China was investigated using the Community Atmosphere Model version 5.1 coupled with the Community Land Model version 4. Results show that the winter sulfate aerosol burden is higher from central eastern China to southern Japan in the case with the presence of urban cover than in the case without it, resulting from urban-induced circulation changes. Such aerosol changes markedly increase the cloud fraction and precipitation over northern China and the adjacent ocean to the east, especially convection activities around southern Japan. This leads to a cooling effect near the surface over northern China and in the mid-upper troposphere to the east due to aerosol direct and indirect effects. The resulting circulation responses act to shift the mid-tropospheric East Asian trough southward and the upper-level East Asian westerly jet-stream as well, further supporting the surface changes. These winter climate responses to the urban-modulated aerosols can largely offset or even reverse those to the AAs forcing without the urban cover in the model, especially in northern East Asia. This study highlights the need to consider the modulating role of urban land-use changes in assessing the AAs’ climatic effect over East Asia and other regions.

Can Land Surface Models Capture the Observed Soil Moisture Control of Water and Carbon Fluxes in Temperate‐To‐Boreal Forests?

AbstractThe reservoir of soil water is exchanged with the atmosphere through evaporative processes, which are mediated via vegetation through transpiration. Carbon uptake is closely coupled to transpiration, and most process‐based models link transpiration and photosynthesis explicitly. Here, we evaluate the simulation of water and carbon fluxes in forested areas of North America using point‐based simulations of the Community Land Model version 5 (CLM5) with Soil Moisture Active/Passive (SMAP) satellite derived soil moisture measurements and in situ measurements at eight Fluxnet and two United States Climate Research Network (CRN) sites. Compared to observations, there is a broad site‐to‐site variability in simulated soil moisture, with some sites exhibiting wet biases and others dry biases. The bias sign does not depend on ecosystem or other environmental drivers such as radiation and temperature. Compared to Fluxnet latent heat (LH) and gross primary production (GPP) flux tower observations, simulated LH flux biases at deciduous broadleaf forests are linked with soil moisture biases, and the model captures the observed seasonal cycle and parabolic seasonal relationship with soil moisture. The parabolic shape is driven by high soil moisture and low LH fluxes in June, peak LH and drier soil conditions in July, followed by further soil moisture drawdown in August. GPP is underestimated at most sites, and the model exhibits a linear relationship between soil moisture and GPP. Because the photosynthesis parameterizations are similar in most Earth system models, further model development that incorporates observations and observed relationships is needed to accurately capture the GPP‐soil moisture relationship.

Evaluating and improving simulations of diurnal variation in land surface temperature with the Community Land Model for the Tibetan Plateau.

This study evaluated and improved the ability of the Community Land Model version 5.0 (CLM5.0) in simulating the diurnal land surface temperature (LST) cycle for the whole Tibetan Plateau (TP) by comparing it with Moderate Resolution Imaging Spectroradiometer satellite observations. During daytime, the model underestimated the LST on sparsely vegetated areas in summer, whereas cold biases occurred over the whole TP in winter. The lower simulated daytime LST resulted from weaker heat transfer resistances and greater soil thermal conductivity in the model, which generated a stronger heat flux transferred to the deep soil. During nighttime, CLM5.0 overestimated LST for the whole TP in both two seasons. These warm biases were mainly due to the greater soil thermal inertia, which is also related to greater soil thermal conductivity and wetter surface soil layer in the model. We employed the sensible heat roughness length scheme from Zeng, Wang & Wang (2012), the recommended soil thermal conductivity scheme from Dai et al. (2019), and the modified soil evaporation resistance parameterization, which was appropriate for the TP soil texture, to improve simulated daytime and nighttime LST, evapotranspiration, and surface (0–10 cm) soil moisture. In addition, the model produced lower daytime LST in winter because of overestimation of the snow cover fraction and an inaccurate atmospheric forcing dataset in the northwestern TP. In summary, this study reveals the reasons for biases when simulating LST variation, improves the simulations of turbulent fluxes and LST, and further shows that satellite-based observations can help enhance the land surface model parameterization and unobservable land surface processes on the TP.

Validation of the Community Land Model Version 5 Over the Contiguous United States (CONUS) Using In Situ and Remote Sensing Data Sets

AbstractThe Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125° during 1979–2018 over the CONUS using different configurations of CLM, namely CLM5‐biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5‐satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote‐sensed and in situ data sets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC‐simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM‐simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation data sets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially distributed plant phenology and physiology parameters and regional‐specific agricultural management practices (e.g., planting and harvest).

Assessments of Weather Research and Forecasting Land Surface Models in Precipitation Simulation Over the Tibetan Plateau

AbstractPrecipitation is a key hydrometeorological variable for understanding surface energy partitioning and water budget over the Tibetan Plateau (TP). A substantial proportion of summer precipitation falls as rain. The effects of different land surface models (LSMs) on the TP’s precipitation and their inner mechanisms remain unclear. Therefore, the assessments of different LSMs coupled with the Weather Research and Forecasting model in precipitation simulation were investigated over the TP during June 28–29 of 2008. The simulated results were evaluated with the merged Climate Prediction Center (CPC) MORPHing technique (CMORPH) precipitation data set developed by the China Meteorological Administration. The assessment demonstrated that precipitation simulated by the Community Land Model Version 4 (CLM4), Noah‐Multiparameterization (Noah‐MP), and Pleim‐Xiu LSM schemes was wider and stronger compared with the merged CMORPH over the central and western TP but was underestimated over the eastern and southern regions. Generally, both CLM4 and Noah‐MP schemes exhibited higher forecasting quality and accuracy in simulating precipitation over the TP. The optimal precipitation simulation was achieved by applying the Noah‐MP scheme, with a lowest root mean square error of 9.53 mm/day, mainly attributed to its corrections of overforecasting for precipitation that did not occur. Further mechanism analysis indicated that soil moisture‐energy flux‐precipitation feedback play an important role in different LSM schemes.

Impact of Vegetation Physiology and Phenology on Watershed Hydrology in a Semiarid Watershed in the Pacific Northwest in a Changing Climate

AbstractChanges in carbon dioxide (CO2) concentration and nitrogen (N) availability can affect land surface processes by regulating physiological (e.g., stomatal opening and closure) and phenological (e.g., leaf area index) responses, which in turn influence terrestrial water cycle dynamics. In this study, we apply the Community Land Model version 5 to investigate how projected environment changes in the 21st century can affect the hydrologic budget in the Upper Columbia‐Priest Rapids watershed, a typical semiarid watershed located in the Pacific Northwest of the United States. Nine numerical experiments were performed to quantifying contributions of climate change, CO2 concentration, and N availability to the watershed hydrologic budget under two Representative Concentration Pathways (RCPs) (i.e., RCP4.5 and RCP8.5). Our results show that compared to its historical value, evapotranspiration (ET) over the watershed increases by 15% and 12% by the end of the century under RCP4.5 and RCP8.5 in responses to changes in meteorological forcing, and further increases by 16% and 11% when elevated CO2 concentrations are accounted for. The effect of N availability on the water balance is insignificant. Such an increase in ET is contributed by the overall increase in leaf area index of vegetation in response to increases in precipitation and CO2 concentration. However, corn‐dominated regions can respond to these changes differently, caused by its increased stomatal resistance under an elevated CO2 concentration with limited N. Our results demonstrate physiological and phenological responses can modulate watershed hydrologic budgets under projected future changes.

Numerical modeling of the responses of soil temperature and soil moisture to climate change over the Tibetan Plateau, 1961–2010

AbstractChanges in soil temperature (ST) and soil moisture (SM) are essential for climate change and ecosystem assessments. Previous investigations on the ST and SM on the Tibetan Plateau (TP) are mainly based on the situ observation and the satellite products. In this study, the improved Community Land Model version 4.5 (CLM4.5), with proper parameter optimization and surface datasets update, is used to estimate the response of ST and SM in the TP to climate change in the long‐term time series from 1961 to 2010. After validating the reasonability of the simulated results using the observations, the spatial distribution of changes in ST and SM in annual and seasonal time series since 1960s, 1980s, 1990s, are investigated respectively and the changes of precipitation (Pr) and surface evaporation (Ev) are also analysed to understand the cause of changes objectively. As a whole, the soil was warming and wetting at the maximum value of 0.31°C/decade and 0.77%/decade since the 1960s. However, the warming process in soil mainly occurred in the 1980s while the wetting tendency is detected since the 1990s extensively. Except for the influence of air warming, the enhanced Pr and Ev might also be indispensable factors that caused the intensive wetting process but damped warming process in soil. Summer is the favourable season for the thermal and hydraulic variation since the 1980s. There exists the striking warmer and drier trend in the eastern TP since 1980s while the colder and wetter condition in the western TP since the 1990s. The magnitude of variation in soil is magnified from 1990s under the continuing impact of climate change.

Climate response to introduction of the ESA CCI land cover data to the NCAR CESM

The European Space Agency Climate Change Initiative Land Cover data (ESA CCI-LC, from 1992 to 2015) is introduced to the National Center for Atmospheric Research Community Earth System Model version 1.2.1 (NCAR CESM1.2.1). In comparison with the original land surface data in the Community Land Model version 4 (ORG), the new data features notable land use and land cover change (LULCC) with increased forests over northeastern Asia and Alaska by decreasing shrublands and grasslands. Overestimated bare land cover over the Tibetan Plateau (TP) and the Rocky Mountains in the ORG are corrected with the replacements by grasslands and shrublands respectively in the new data. The model simulation results show that with the introduction of the ESA CCI-LC, the simulated surface albedo, surface net radiation flux, sensible and latent heat fluxes are relatively improved over the regions where significant LULCC exists, such as northeastern Asia, Alaska, the TP, and Australia. Surface air temperature, precipitation, and atmospheric circulation are improved in boreal winter but degraded in summer. The winter warming over northeastern Asia results from increased longwave downwelling flux and adiabatic heating while the notable winter cooling over Alaska is attributed to strong cold advection followed by reduced longwave downwelling flux. LULCC alters precipitation by influencing water vapor content. In winter, LULCC affects atmospheric circulation via modulating baroclinicity while in summer, it influences land-sea thermal contrast, thus affecting the intensity of East Asian summer monsoon. LULCC also alters the simulated dust burden.

Water use efficiency in terrestrial ecosystem over East Asia: Effects of climate regimes and land cover types

Water use efficiency (WUE) is an environmental factor to account for the metabolism of terrestrial ecosystems using various climate systems and vegetation types. It is estimated by the ratio of gross primary productivity (GPP) to evapotranspiration (ET), the largest carbon and water fluxes with respect to plant respiration. In this study, the WUE was calculated using GPP and ET from the community land model version 4.0 (CLM4.0), inclusive of the prognostic carbon-nitrogen model in the community earth system model (CESM). The estimated WUE in East Asia was analyzed for climate zones, land cover types, and water- and energy-limited zones, with aridity index (AI). Spatial variations from 2001 to 2015 in annual WUE gradually increased as latitude decreased, though small year-to-year differences appeared between monthly GPP and ET. Monthly WUE was lower in summer than fall because the water loss rate in summer was higher than the carbon assimilation increase. The WUE under arid conditions (AI<0.5) was lower than under humid conditions. The GPP, ET, and WUE were higher in the forest, savannas, cropland, and permanent wetland with dense vegetation or abundant water resources than in other land cover types. The WUE was lower in water-limited zones than in energy-limited zones due to the low amount of water to use for the physical processes of GPP and ET. Based on this study, we identified general spatial and temporal variations of carbon fluxes in East Asia with various climate zones and land cover types.