Community Land Model Version Research Articles

Water storage effect of soil freeze-thaw process and its impacts on soil hydro-thermal regime variations

In the soil freeze/thaw phenomenon, the soil water phase and energy budget change, which can affect the soil-vegetation-atmosphere system. Herein, the basic role of freeze–thaw–process (FTP) in soil water and heat transport and its impact on soil moisture and temperature variation were investigated using the observations and numerical experiments with and without FTP in Community Land Model version 4.5 (CLM4.5) on the Tibetan Plateau (TP). The results averaged over the whole TP revealed that no soil FTP (i.e., no water phase change occurred) resulted in lower surface soil temperature by about -1.02 ℃ in freeze-thaw (FT) period, while surface soil temperature is higher by about 0.91 ℃ and surface soil moisture is drier by about -0.02 mm3/mm3 in after-thaw (AT) period. Soil FTP has a water storage effect, the storage index (SI) can reach 0.95 at surface layer. Without soil FTP, the surface soil water content at the AT period can be reduced by ∼10% (SI is decreased by about -0.05) as a result of enhanced evaporation; the soil moisture memory was shortened by about -20 days in March. Accordingly, surface latent heat decreased by -1.07 W/m2, while the surface sensible heat increased by 4.72 W/m2. The effects of FTP on soil water and heat transport at deep layer are distinguished from that at the surface layer. These imply that the biases of soil temperature and moisture simulation in models during FT period could lead to large uncertainties in estimating climate effects of TP. Under climate warming background in recent decades, with the delaying of soil freeze-beginning date and advancing of soil thaw-end date, changes of soil FTP regime would lead to loss of spring soil moisture.

Changes in Wood Biomass and Crop Yields in Response to Projected CO2, O3, Nitrogen Deposition, and Climate

AbstractAs the world's population increases, so will the demand for food and timber resources. Though carbon dioxide (CO2) fertilization and, to a lesser extent, nitrogen (N) deposition are expected to increase future resource production, changes in ozone (O3) and climate have the potential to decrease production due to increased phytotoxic damage, drought, and heat stress. To determine how crop and timber production may change in the future, we use the Community Land Model version 4.5 with prognostic crops to simulate responses of wood biomass and crop yields to CO2, O3, N deposition, and climate under Representative Concentration Pathway 8.5 forcings. Generally, rising CO2 increases wood biomass and crop yields, while projected climate change causes decreases. Small projected changes in O3 and N deposition do not strongly affect yields, though additional research is needed on future O3 and N deposition trends and impacts. By the end of the 21st century, global wood biomass increases by ~16% due to the dominating impact of CO2. The positive effect of CO2 on future crop yields is muted by the negative impacts of climate, with a ~5% net global increase. Future projections suggest that rice and wheat yields typically increase under the combination of future forcings, whereas soy and corn yields are regionally variable. While short‐term resource management strategies can benefit from planting heat‐tolerant species and cultivars, technological advances and intensification, among other management strategies not included here, must be employed to meet the future demand for these resources.

Influence of winter precipitation on spring phenology in boreal forests.

Understanding the variations in spring vegetation phenology associated with preseason climate conditions can significantly improve our knowledge on ecosystem dynamics and biosphere-atmosphere interactions. Recent studies have shown that wet winters can delay the start date of the vegetation growing season (SOS) in the high latitudes. However, associated underlying mechanisms remain unclear due to the lack of observation sites as well as complex interactions between various climate and ecosystem variables. In this study, the impact of winter precipitation on year-to-year variations of the SOS in boreal forests from 1982 to 2005 was investigated. Two experiments were performed using the Community Land Model version 4.5. In the control experiment, observed precipitation was used; in the sensitivity experiment, precipitation in the year 1982 was repeated throughout the period. The SOS in the control experiment shows high temporal correlations with the SOS estimated from the satellite-retrieved leaf area index, indicating that the land model is capable of simulating realistic response of vegetation to interannual climate variability. The effects of winter precipitation on the SOS are examined by comparing the two model experiments for wet- and dry winters. After wet winters, the SOS was delayed by 2.7days over 70.1% of the boreal forests than after dry winters; this accounts for 42.5% of the interannual variation in the SOS. The SOS delay is related to the decrease in the growing degree-days (GDD) based on soil temperatures, suggesting that the effects of heat exposure on vegetation growth is strongly modulated by winter precipitation. The GDD decrease is related to both the increase in snowmelt heat flux and reduced absorption of solar radiation, which are proportional to the amount of winter precipitation and the ratio of short plants to tall trees, respectively. Our results provide a physical basis for the winter precipitation-SOS relationship, suggesting that an increase in winter precipitation can alleviate strong advancing trends in spring vegetation growth in conjunction with global warming even for temperature-limited ecosystems.

Interactive effects of seasonal drought and nitrogen deposition on carbon fluxes in a subtropical evergreen coniferous forest in the East Asian monsoon region

Subtropical forests in the East Asian monsoon region function as considerable carbon sinks in the Northern Hemisphere. Forest ecosystems in this region have experienced intensified seasonal drought that has limited their carbon sequestration capacity, but increasing atmospheric nitrogen deposition has contrarily enhanced their capacity to act as carbon sinks. Understanding and quantifying the interactive effects of seasonal drought and nitrogen deposition on the carbon sequestration of subtropical forests is of great significance for accurately predicting future changes to the terrestrial carbon cycle. In this study, we used the Community Land Model Version 4.5 (CLM4.5) to investigate how carbon fluxes, i.e. gross primary productivity (GPP), ecosystem respiration (Re), and net ecosystem productivity (NEP), respond to seasonal drought and nitrogen deposition in an evergreen coniferous forest in southern China. Our results showed that reduced GPP during the drought in the summers of 2003 and 2007 weakened the forest’s carbon sequestration capacity. The reduction in GPP mainly occurred at the sunlit canopy due to its higher sensitivity to soil water stress, and non-stomatal limitations played an important role in limiting leaf photosynthesis. The enhanced NEP by nitrogen deposition was attributed to increased plant growth, which could, in turn, be attributed to increases in leaf area. Interactions of seasonal drought and nitrogen deposition varied with drought severity. Interactive effects of the two drivers on GPP, Re, and NEP were additive under mild and moderate drought conditions but non-additive under severe drought. Their net effects on NEP shifted from +29% under mild and moderate drought conditions to -56% under severe drought. Our study highlights the importance of accounting for the interactive effects of seasonal drought and nitrogen deposition in assessing the carbon sequestration of subtropical forest ecosystems in the East Asian monsoon region.

Evaluating and improving the Community Land Model's sensitivity to land cover

Abstract. Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate.

Impacts of hydraulic redistribution on eco-hydrological cycles: A case study over the Amazon basin

Hydraulic redistribution (HR) refers to the process of soil water transport through the low-resistance pathway provided by plant roots. It has been observed in field studies and proposed to be one of the processes that enable plants to resist water limitations. However, most land-surface models (LSMs) currently do not include this underground root process. In this study, a HR scheme was incorporated into the Community Land Model version 4.5 (CLM4.5) to investigate the effect of HR on the eco-hydrological cycle. Two paired numerical simulations (with and without the new HR scheme) were conducted for the Tapajos National Forest km83 (BRSa3) site and the Amazon. Simulations for the BRSa3 site in the Amazon showed that HR during the wet season was small, 0.1 mm day–1, transferring water from shallow wet layers to deep dry layers at night; however, HR in the dry season was more obvious, up to 0.3 mm day–1, transferring water from deep wet layers to shallow dry layers at night. By incorporating HR into CLM4.5, the new model increased gross primary production (GPP) and evapotranspiration (ET) by 10% and 15%, respectively, at the BRSa3 site, partly overcoming the underestimation. For the Amazon, regional analysis also revealed that vegetation responses (including GPP and ET) to seasonal drought and the severe drought of 2005 were better captured with the HR scheme incorporated.

Triose phosphate limitation in photosynthesis models reduces leaf photosynthesis and global terrestrial carbon storage

Triose phosphate utilization (TPU)-limited photosynthesis occurs when carbon export from the Calvin-Benson cycle cannot keep pace with carbon inputs and processing. This condition is poorly constrained by observations but may become an increasingly important driver of global carbon cycling under future climate scenarios. However, the consequences of including or omitting TPU limitation in models have seldom been quantified. Here, we assess the impact of changing the representation of TPU limitation on leaf- and global-scale processes. At the leaf scale, TPU limits photosynthesis at cold temperatures, high CO2 concentrations, and high light levels. Consistent with leaf-scale results, global simulations using the Community Land Model version 4.5 illustrate that the standard representation of TPU limits carbon gain under present day and future conditions, most consistently at high latitudes. If the assumed TPU limitation is doubled, further restricting photosynthesis, terrestrial ecosystem carbon pools are reduced by 9 Pg by 2100 under a business-as-usual scenario. The impact of TPU limitation on global terrestrial carbon gain suggests that CO2 concentrations may increase more than expected if models omit TPU limitation, and highlights the need to better understand when TPU limitation is important, including variation among different plant types and acclimation to temperature and CO2.

Multi-sensor land data assimilation: Toward a robust global soil moisture and snow estimation

Global monitoring of soil moisture and snow is now available through various satellite observations from optical, microwave, and gravitational sensors. However, very few modeling frameworks exist that conjointly use the above sensors to produce mutually and physically consistent earth system records. To this goal, a prototype of multi-sensor land data assimilation system is developed by linking the Community Land Model version 4 (CLM4) and a series of forward models with the Data Assimilation Research Testbed (DART). The deterministic Ensemble Adjustment Kalman Filter (EAKF) within the DART is utilized to estimate global soil moisture and snow by assimilating brightness temperature, snow cover fraction, and daily total water storage observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), Moderate Resolution Imaging Spectroradiometer (MODIS), and Gravity Recovery and Climate Experiment (GRACE), respectively. A 40-member of Community Atmosphere Model version 4 (CAM4) reanalysis is adopted to introduce ensemble spread in CLM4 land states and some methods are used to reduce the computational load. Data assimilation with different combinations of sensors is implemented for 2003–2009 to investigate individual contributions from different satellite observations. Evaluation results and cross-comparison of open-loop and data assimilation cases suggest that 1) assimilation of MODIS snow cover fraction slightly improves snow estimation in mid and high latitudes; 2) lower and higher frequencies of AMSR-E brightness temperature play complementary roles in improving global soil moisture and snow estimation; 3) assimilation of GRACE tends to degrade soil moisture estimation but poses potential in improving snow depth estimation in most high-latitude regions. Generally, the combination of MODIS, GRACE, and AMSR-E observations with regard to spatial locations holds promise to provide a robust global soil moisture and snow estimation through the multi-sensor land data assimilation system.

The importance of carbon-nitrogen biogeochemistry on water vapor and carbon fluxes as elucidated by a multiple canopy layer higher order closure land surface model

The carbon-nitrogen (CN) biogeochemistry and the prognostic canopy structure scheme used in the Community Land Model version 4.5 (CLM4.5) are integrated into the multiple canopy layer higher order closure Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). The ACASA-CN model inherits the advantages from ACASA and CLM4.5, and it is the first model that represents fully prognostic terrestrial feedbacks with a higher order closure turbulence scheme and vertically resolved canopy structure. The simulations are evaluated in terms of ecological, biogeophysical and biogeochemical aspects at six AmeriFlux eddy covariance sites encompassing a variety of vegetation types and microclimatic conditions across the continental United States. Our model evaluation shows that ACASA-CN reasonably simulates surface layer properties, such as vegetation structure and plant phenology. Our results indicate that the use of a higher order closure turbulence scheme with multiple canopy layer representation is critical to land carbon cycle simulation. Based on our simulations, water vapor exchange between the land surface and the atmosphere is primarily through plant transpiration (78–88%), and canopy evapotranspiration is enhanced with the use of CN biogeochemistry. Our results indicate that the ratio of transpiration to evapotranspiration exhibits a two-stage variation pattern, and the transpiration fraction decreases in dense canopies.

A New Scheme for Considering Soil Water‐Heat Transport Coupling Based on Community Land Model: Model Description and Preliminary Validation

AbstractLand surface models (LSMs) have developed significantly over the past few decades, with the result that most LSMs can generally reproduce the characteristics of the land surface. However, LSMs fail to reproduce some details of soil water and heat transport during seasonal transition periods because they neglect the effects of interactions between water movement and heat transfer in the soil. Such effects are critical for a complete understanding of water‐heat transport within a soil thermohydraulic regime. In this study, a fully coupled water‐heat transport scheme (FCS) is incorporated into the Community Land Model (version 4.5) to replaces its original isothermal scheme, which is more complete in theory. Observational data from five sites are used to validate the performance of the FCS. The simulation results at both single‐point and global scale show that the FCS improved the simulation of soil moisture and temperature. FCS better reproduced the characteristics of drier and colder surface layers in arid regions by considering the diffusion of soil water vapor, which is a nonnegligible process in soil, especially for soil surface layers, while its effects in cold regions are generally inverse. It also accounted for the sensible heat fluxes caused by liquid water flow, which can contribute to heat transfer in both surface and deep layers. The FCS affects the estimation of surface sensible heat (SH) and latent heat (LH) and provides the details of soil heat and water transportation, which benefits to understand the inner physical process of soil water‐heat migration.

Simulation of Changes in the Near‐Surface Soil Freeze/Thaw Cycle Using CLM4.5 With Four Atmospheric Forcing Data Sets

AbstractChange in the near‐surface soil freeze/thaw cycle is critical for assessments of hydrological activity, ecosystems, and climate change. Previous studies investigated the near‐surface soil freeze/thaw cycle change mostly based on in situ observations and satellite monitoring. Here numerical simulation method is tested to estimate the long‐term change in the near‐surface soil freeze/thaw cycle in response to recent climate warming for its application to predictions. Four simulations are performed at 0.5° × 0.5° resolution from 1979 to 2009 using the Community Land Model version 4.5, each driven by one of the four atmospheric forcing data sets (i.e., one default Climate Research Unit‐National Centers for Environmental Prediction [CRUNCEP] and three newly developed Modern Era Retrospective‐Analysis for Research and Applications, Climate Forecast System Reanalysis, and European Centre for Medium‐Range Weather Forecasts Reanalysis Interim). The observations from 299 weather stations in both Russia and China are employed to validate the simulated results. The results show that all simulations reasonably reproduce the observed variations in the ground temperature, the freeze start and end dates, and the freeze duration (the correlation coefficients range from 0.47 to 0.99, and the Nash‐Sutcliffe efficiencies range from 0.19 to 0.98). Part of the simulations also exactly simulate the trends of the ground temperature, the freeze start and end dates, and the freeze duration. Of the four simulations, the results from the simulation using the CRUNCEP data set show the best overall agreement with the in situ observations, indicating that the CRUNCEP data set could be preferentially considered as the basic atmospheric forcing data set for future prediction. The simulated area‐averaged annual freeze duration shortened by 8.03 days on average from 1979 to 2009, with an uncertainty (one standard deviation) of 0.67 days caused by the different atmospheric forcing data sets. These results address the performance of numerical model in simulating the long‐term changes in the near‐surface soil freeze/thaw cycle and the role of different atmospheric forcing data sets in the simulation, which are useful for the prediction of future freeze/thaw dynamics.

Detecting the permafrost carbon feedback: talik formation and increased cold-season respiration as precursors to sink-to-source transitions

Abstract. Thaw and release of permafrost carbon (C) due to climate change is likely to offset increased vegetation C uptake in northern high-latitude (NHL) terrestrial ecosystems. Models project that this permafrost C feedback may act as a slow leak, in which case detection and attribution of the feedback may be difficult. The formation of talik, a subsurface layer of perennially thawed soil, can accelerate permafrost degradation and soil respiration, ultimately shifting the C balance of permafrost-affected ecosystems from long-term C sinks to long-term C sources. It is imperative to understand and characterize mechanistic links between talik, permafrost thaw, and respiration of deep soil C to detect and quantify the permafrost C feedback. Here, we use the Community Land Model (CLM) version 4.5, a permafrost and biogeochemistry model, in comparison to long-term deep borehole data along North American and Siberian transects, to investigate thaw-driven C sources in NHL (> 55∘ N) from 2000 to 2300. Widespread talik at depth is projected across most of the NHL permafrost region (14 million km2) by 2300, 6.2 million km2 of which is projected to become a long-term C source, emitting 10 Pg C by 2100, 50 Pg C by 2200, and 120 Pg C by 2300, with few signs of slowing. Roughly half of the projected C source region is in predominantly warm sub-Arctic permafrost following talik onset. This region emits only 20 Pg C by 2300, but the CLM4.5 estimate may be biased low by not accounting for deep C in yedoma. Accelerated decomposition of deep soil C following talik onset shifts the ecosystem C balance away from surface dominant processes (photosynthesis and litter respiration), but sink-to-source transition dates are delayed by 20–200 years by high ecosystem productivity, such that talik peaks early (∼ 2050s, although borehole data suggest sooner) and C source transition peaks late (∼ 2150–2200). The remaining C source region in cold northern Arctic permafrost, which shifts to a net source early (late 21st century), emits 5 times more C (95 Pg C) by 2300, and prior to talik formation due to the high decomposition rates of shallow, young C in organic-rich soils coupled with low productivity. Our results provide important clues signaling imminent talik onset and C source transition, including (1) late cold-season (January–February) soil warming at depth (∼ 2 m), (2) increasing cold-season emissions (November–April), and (3) enhanced respiration of deep, old C in warm permafrost and young, shallow C in organic-rich cold permafrost soils. Our results suggest a mosaic of processes that govern carbon source-to-sink transitions at high latitudes and emphasize the urgency of monitoring soil thermal profiles, organic C age and content, cold-season CO2 emissions, and atmospheric 14CO2 as key indicators of the permafrost C feedback.

Human impacts on 20th century fire dynamics and implications for global carbon and water trajectories

Abstract Fire is a fundamental Earth system process and the primary ecosystem disturbance on the global scale. It affects carbon and water cycles through changing terrestrial ecosystems, and at the same time, is regulated by weather and climate, vegetation characteristics, and, importantly, human ignitions and suppression (i.e., the direct human effect on fire). Here, we utilize the Community Land Model version 4.5 (CLM4.5) to quantify the impacts of changes in human ignition and suppression on fire dynamics and associated carbon and water cycles. We find that the impact is to significantly reduce the 20th century global burned area by a century average of 38 Mha/yr and by 103 Mha/yr at the end of the century. Land carbon gain is weakened by 17% over the 20th century, mainly due to increased human deforestation fires and associated escape fires (i.e., degradation fires) in the tropical humid forests, even though the decrease in burned area in many other regions due to human fire suppression acts to increase land carbon gain. The direct human effect on fire weakens the upward trend in global runoff throughout the century by 6% and enhances the upward trend in global evapotranspiration since ~ 1945 by 7%. In addition, the above impacts in densely populated, highly developed (if population density > 0.1 person/km2), or moderately populated and developed regions are of opposite sign to those in other regions. Our study suggests that particular attention should be paid to human deforestation and degradation fires in the tropical humid forests when reconstructing and projecting fire carbon emissions and net atmosphere-land carbon exchange and estimating resultant impacts of direct human effect on fire.

Utilizing a new soil effective temperature scheme and archived satellite microwave brightness temperature data to estimate surface soil moisture in the Nagqu region, Tibetan Plateau of China

Since the early 2000s, many satellite passive microwave brightness temperature (BT) archives, such as the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) BTs, have become the useful resources for assessing the changes in the surface and deep soil moistures over both arid and semi-arid regions. In this study, we used a new soil effective temperature (Teff) scheme and the archived AMSR-E BTs to estimate surface soil moisture (SM) over the Nagqu region in the central Tibetan Plateau, China. The surface and deep soil temperatures required for the calculation of regional-scale Teff were obtained from outputs of the Community Land Model version 4.5 (CLM4.5). In situ SM measurements at the CEOP-CAMP/Tibet (Coordinated Enhanced Observing Period Asia-Australia Monsoon Project on the Tibetan Plateau) experimental sites were used to validate the AMSR-E-based SM estimations at regional and single-site scales. Furthermore, the spatial distribution of monthly mean surface SM over the Nagqu region was obtained from 16 daytime AMSR-E BT observations in July 2004 over the Nagqu region. Results revealed that the AMSR-E-based surface SM estimations agreed well with the in situ-based surface SM measurements, with the root mean square error (RMSE) ranging from 0.042 to 0.066 m3/m3 and the coefficient of determination (R2) ranging from 0.71 to 0.92 during the nighttime and daytime. The regional surface soil water state map showed a clear spatial pattern related to the terrain. It indicated that the lower surface SM values occurred in the mountainous areas of the northern, mid-western and southeastern parts of Nagqu region, while the higher surface SM values appeared in the low elevation areas such as the Tongtian River Basin, Namco Lake and bog meadows in the central part of Nagqu region. Our analysis also showed that the new Teff scheme does not require special fitting parameters or additional assumptions, which simplifies the data requirements for regional-scale applications. This scheme combined with the archived satellite passive microwave BT observations can be used to estimate the historical surface SM for hydrological process studies over the Tibetan Plateau regions.

Regional climate model simulation for temperature and precipitation over South Asia using different physical parameterisation schemes

The ability of ICTP regional climate model version 4 (RegCM4.3) is investigated by using two land surface schemes: the biosphere-atmosphere transfer scheme (BATS) and the community land model version 3.5 (CLM3.5). To attain the best model configuration over the South Asia region, six sensitivity experiments are conducted with three different cumulus convection schemes. RegCM4.3 coupled with CLM3.5 and mixed convection scheme option (MIX-CLM), produced better simulation than BATS. The cold winter bias and the intensities of wet-dry biases over the foothills of Hindukush-Karakorum-Himalaya (HKH) and Central India are substantially reduced with MIX-CLM. In terms of seasonal variability, results suggest that different convection schemes behaved differently over sub-regions of the domain. The annual cycles of precipitation and temperature are better captured over the Bay of Bengal and Western Ghats by MIX-CLM. In spite of some deficiencies, the MIX-CLM scheme improves the model performance over the various parts of the domain.

Regional climate model simulation for temperature and precipitation over South Asia using different physical parameterisation schemes

The ability of ICTP regional climate model version 4 (RegCM4.3) is investigated by using two land surface schemes: the biosphere-atmosphere transfer scheme (BATS) and the community land model version 3.5 (CLM3.5). To attain the best model configuration over the South Asia region, six sensitivity experiments are conducted with three different cumulus convection schemes. RegCM4.3 coupled with CLM3.5 and mixed convection scheme option (MIX-CLM), produced better simulation than BATS. The cold winter bias and the intensities of wet-dry biases over the foothills of Hindukush-Karakorum-Himalaya (HKH) and Central India are substantially reduced with MIX-CLM. In terms of seasonal variability, results suggest that different convection schemes behaved differently over sub-regions of the domain. The annual cycles of precipitation and temperature are better captured over the Bay of Bengal and Western Ghats by MIX-CLM. In spite of some deficiencies, the MIX-CLM scheme improves the model performance over the various parts of the domain.

Extreme Precipitation Years and Their Occurrence Frequency Regulate Long‐Term Groundwater Recharge and Transit Time

Core Ideas Long‐term groundwater recharge in semiarid regions was investigated. New deep drainage and water table schemes were added to Community Land Model. Most groundwater recharge at depth occurs in wet years. Frequency of wet years in a period controls the groundwater recharge in that period. Deep drainage, defined as the water flux below the plant root zone, is potential groundwater recharge in arid and semiarid regions but remains poorly understood. This study aims to explore long‐term (1901–2015) deep drainage (at the 75‐m depth) in a semiarid region with deep unsaturated zone (>90‐m depth). For this purpose, a winter wheat (Triticum aestivum L.) field on the Loess Plateau of China was investigated using the Community Land Model (CLM) version 4.0. A new water table scheme was added to CLM version 4.0 to better simulate the water table depth. We found that wet years (with precipitation >650 mm yr−1) are the main source of recharge to the deep soil (e.g., >75‐m depth). The average response time of recharge to a wet year was 8.3 yr to 75‐m depth, which is only 9% of the response time averaged across all non‐wet years in the period. Our results also indicate that the frequency of wet years rather than the average annual precipitation amount plays a more important role in generating deep drainage and groundwater recharge. The results of this study provide new insight into the long‐term groundwater recharge in regions with a deep unsaturated zone.

Improving maize growth processes in the community land model: Implementation and evaluation

Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Several current ESMs have the capabilities to simulate crop growth. However, some critical crop growth processes (e.g. flowering and other reproductive processes) and their responses to environmental extremes (e.g. heat stress) are not yet represented in most of these models. In this paper, an improved maize growth model was implemented in the Community Land Model version 4.5 (CLM4.5) by modifying the maize planting scheme, incorporating the phenology scheme adopted from the APSIM model (Agricultural Production Systems sIMulator), adding a new carbon allocation scheme into CLM4.5, and improving the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number. Evaluation of results at 7 AmeriFlux sites located in the US Corn Belt show that the CLM-APSIM model performs better than the original CLM4.5 in simulating phenology (LAI and canopy height), surface fluxes including gross primary production (GPP), net ecosystem exchange (NEE), latent heat (LH), and sensible heat (SH), and especially in simulating the biomass partition and maize yield. The CLM-APSIM model corrects a serious deficiency in CLM4.5-related to CLM4.5’s underestimation of aboveground biomass (i.e. overestimation of belowground biomass) and overestimation of Harvest Index, which lead to a reasonable yield estimation with wrong mechanisms. Moreover, 13-year simulation results from 2001 to 2013 at the three Mead sites (US-Ne1, Ne2 and Ne3) show that the CLM-APSIM model can more accurately reproduce maize yield responses to growing season climate (temperature and precipitation) than the original CLM4.5 when benchmarked with the site-based observations and USDA county-level survey statistics. The CLM-APSIM model is thus more suitable than its predecessor models in terms of simulating abiotic environmental stresses on maize yield. This new model provides an improved tool to attribute maize yield change to various processes under historical and future climate, as well as to assess and design effective climate adaptation strategies for sustainable agricultural production.

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

Abstract. A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.

Multiple timescale analysis of the urban heat island effect based on the Community Land Model: a case study of the city of Xi'an, China.

Urban heat islands (UHIs) are the phenomenon of urban regions usually being warmer than rural regions, which significantly impacts both the regional ecosystem and societal activities. Numerical simulation can provide spatially and temporally continuous datasets for UHI analysis. In this study, a spatially and temporally continuous ground temperature dataset of Xi'an, China was obtained through numerical simulation based on the Community Land Model version 4.5 (CLM4.5), at a temporal resolution of 30 min and a spatial resolution of 0.05∘× 0.05∘. Based on the ground temperature, the seasonal average UHI intensity (UHII) was calculated and the seasonal variation of the UHI effect was analyzed. The monthly variation tendency of the urban heat stress was also investigated. Based on the diurnal cycle of ground temperature and the UHI effect in each season, the variation tendencies of the maximum, minimum, and average UHII were analyzed. The results show that the urban heat stress in summer is the strongest among all four seasons. The heat stress in urban areas is very significant in July, and the UHII is the weakest in January. Regarding the diurnal cycle of UHII, the maximum always appears at 06:30 UTC to 07:30 UTC, while the minimum intensity of the UHI effect occurs at different times in the different seasons. The results of this study could provide a reference for policymakers about how to reduce the damage caused by heat stress.