Evaluation of the Community Microwave Emission Model Coupled with the Community Land Model over East Asia

The Community Microwave Emission Model (CMEM) developed by the European Centre for Me-dium-Range Weather Forecasts (ECMWF) can provide a link between surface states and satellite observations and simulate the passive microwave brightness temperature of the surface at low frequencies (from 1 GHz to 20 GHz).This study evaluated the performance of the CMEM cou-pled with the Community Land Model (CLM) (CMEM-CLM) using C-band (6.9 GHz) microwave brightness temperatures from the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E) over East Asia.Preliminary results support the argument that the simulated brightness temperatures of CMEM-CLM from July 2005 to June 2010 are comparable to AMSR-E observational data.CMEM-CLM performed better for vertical polarization,for which the root mean square error was approximately 15 K,compared to over 30 K for horizontal polarization.An evaluation performed over seven sub-regions in China indicated that CMEM-CLM was able to capture the temporal evolution of C-band brightness temperatures well,and the best correlation with AMSR-E appeared over western Northwest China (over 0.9 for vertical polarization).However,larger biases were found over southern North China and the middle and lower reaches of the Yangtze River.

Estimates of net primary productivity and actual evapotranspiration over the Tibetan Plateau from the Community Land Model version 4.5 with four atmospheric forcing datasets

The accuracy of the simulation of carbon and water processes largely relies on the selection of atmospheric forcing datasets when driving land surface models(LSM).Particularly in high-altitude regions,choosing appropriate atmospheric forcing datasets can effectively reduce uncertainties in the LSM simulations.Therefore,this study conducted four offline LSM simulations over the Tibetan Plateau(TP)using the Community Land Model version 4.5(CLM4.5)driven by four state-of-the-art atmospheric forcing datasets.The performances of CRUNCEP(CLM4.5 model default)and three other reanalysis-based atmospheric forcing datasets(i.e.ITPCAS,GSWP3 and WFDEI)in simulating the net primary productivity(NPP)and actual evapotranspiration(ET)were evaluated based on in situ and gridded reference datasets.Compared with in situ observations,simulated results exhibited determination coefficients(R2)ranging from 0.58 to 0.84 and 0.59 to 0.87 for observed NPP and ET,respectively,among which GSWP3 and ITPCAS showed superior performance.At the plateau level,CRUNCEP-based simulations displayed the largest bias compared with the reference NPP and ET.GSWP3-based simulations demonstrated the best performance when comprehensively considering both the magnitudes and change trends of TP-averaged NPP and ET.The simulated ET increase over the TP during 1982-2010 based on ITPCAS was significantly greater than in the other three simulations and reference ET,suggesting that ITPCAS may not be appropriate for studying long-term ET changes over the TP.These results suggest that GSWP3 is recommended for driving CLM4.5 in conducting long-term carbon and water processes simulations over the TP.This study contributes to enhancing the accuracy of LSM in water-carbon simulations over alpine regions.

Parameter Sensitivities of the Community Land Model at Two Alpine Sites in the Three-River Source Region

The three-river source region plays an important role on China’s ecological security and Asia’s water supply. Historically, the region has experienced severe ecological degradation due to climate change and human activities. Reasonable simulations of the energy and water cycles are essential to predict the responses of land surface processes to future climate change. Current land surface models involve empirical functions that are associated with many parameters. These parameter uncertainties will largely affect the simulation when applied to a new domain. The Community Land Model(CLM) is a widely used land surface model, and version 5.0 is the newest version. Compared to the prior version CLM4.5, CLM5.0 has largely updated plant hydraulic and stomatal conductance schemes. How these changes affect parameter sensitivities is unknown. In our work, we tested 17 key parameters in CLM4.5 and 19 parameters in CLM5.0 at two eddy flux sites in the three-river source region: the Maqu and Maduo sites. We adopted the simplest one-at-a-time changes on each parameter and quantified their sensitivities by the parameter effect(PE).We found that the Maqu site was more sensitive to vegetation parameters, while the Maduo site was more sensitive to the initial soil water content in both CLM4.5 and CLM5.0. This is because Maduo grid cell has wetland that does not respond to vegetation parameters in CLM, which may not reflect the reality. Further model development on wetland vegetation parameterization is important. Our validation on the default simulation showed CLM5.0 did not always improve the simulations. The largest difference between CLM5.0 and CLM4.5 was that soil moisture(SM) showed a much stronger decrease in response to a higher leaf area index(LAI) in CLM5.0 than in CLM4.5, suggesting that SM is more sensitive to vegetation changes in CLM5.0.

Evaluating the Dependence of Vegetation on Climate in an Improved Dynamic Global Vegetation Model

The capability of an improved Dynamic Global Vegetation Model （DGVM） in reproducing the impact of climate on the terrestrial ecosystem is evaluated. The new model incorporates the Community Land Model- DGVM （CLM3.0-DGVM） with a submodel for temperate and boreal shrubs, as well as other revisions such as the ＂two-leaf＂ scheme for photosynthesis and the definition of fractional coverage of plant functional types （PFTs）. Results show that the revised model may correctly reproduce the global distribution of temperate and boreal shrubs, and improves the model performance with more realistic distribution of di？erent vege- tation types. The revised model also correctly reproduces the zonal distributions of vegetation types. In reproducing the dependence of the vegetation distribution on climate conditions, the model shows that the dominant regions for trees, grasses, shrubs, and bare soil are clearly separated by a climate index derived from mean annual precipitation and temperature, in good agreement with the CLM4 surface data. The dominant plant functional type mapping to a two dimensional parameter space of mean annual temperature and precipitation also qualitatively agrees with the results from observations and theoretical ecology studies.

Improving microwave brightness temperature predictions based on Bayesian model averaging ensemble approach

The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simulation is investigated by adopting a statistical post-processing procedure with the Bayesian model averaging （BMA） ensemble approach. The simulations by the community microwave emission model （CMEM） cou- pled with the community land model version 4.5 （CLM4.5） over China's Mainland are con- ducted by the 24 configurations from four vegetation opacity parameterizations （VOPs）, three soil dielectric constant parameterizations （SDCPs）, and two soil roughness param- eterizations （SRPs）. Compared with the simple arithmetical averaging （SAA） method, the BMA reconstructions have a higher spatial correlation coefficient （larger than 0.99） than the C-band satellite observations of the advanced microwave scanning radiometer on the Earth observing system （AMSR-E） at the vertical polarization. Moreover, the BMA product performs the best among the ensemble members for all vegetation classes, with a mean root-mean-square difference （RMSD） of 4 K and a temporal correlation coefficient of 0.64.

Use of the RegCM System over East Asia： Review and Perspectives

The Abdus Salam International Center for Theoretical Physics （ICTP） RegCM system is one of the most commonly used regional climate models （RCMs） over the East Asia region, In this paper, we present a brief review of the RegCM system and its applications to the East Asia region. The model history and plans for future development are described, Previous and ongoing applications, as well as the advantages and biases found in the model system over the East Asia region, are summarized, The model biases that exist are mainly found in the cold seasons, and are characterized by a warm bias at high latitudes and underestimation of precipitation in the south. These biases are similar to those of most global climate models （GCMs）, Finally, future plans on the application and development of the model, and specifically on those within the context of the Coordinated Regional Climate Downscaling Experiment （CORDEX）, are introduced. This paper is intended to serve as a reference for future users of the RegCM system within the East Asia region.

Runoff of arid and semi-arid regions simulated and projected by CLM-DTVGM and its multi-scale fluctuations as revealed by EEMD analysis

Runoff is a major component of the water cycle, and its multi-scale fluctuations are important to water resources management across arid and semi-arid regions. This paper coupled the Distributed Time Variant Gain Model （DTVGM） into the Community Land Model （CLM 3.5）, replacing the TOPMODEL-based method to simulate runoff in the arid and semi-arid regions of China. The coupled model was calibrated at five gauging stations for the period 1980-2005 and validated for the period 2006-2010. Then, future runoff （2010-2100） was simulated for different Representative Concentration Pathways （RCP） emission scenarios. After that, the spatial distributions of the future runoff for these scenarios were discussed, and the multi-scale fluctuation characteristics of the future annual runoff for the RCP scenarios were explored using the Ensemble Empirical Mode Decomposition （EEMD） analysis method. Finally, the decadal variabilities of the future annual runoff for the entire study area and the five catchments in it were investigated. The results showed that the future annual runoff had slowly decreasing trends for scenarios RCP 2.6 and RCP 8.5 during the period 2010-2100, whereas it had a non-monotonic trend for the RCP 4.5 scenario, with a slow increase after the 2050s. Additionally, the future annual runoff clearly varied over a decadal time scale, indicating that it had clear divisions between dry and wet periods. The longest dry period was approximately 15 years （2040-2055） for the RCP 2.6 scenario and 25 years （2045-2070） for the RCP 4.5 scenario. However, the RCP 8.5 scenario was predicted to have a long dry period starting from 2045. Under these scenarios, the water resources situation of the study area will be extremely severe. Therefore, adaptive water management measures addressing climate change should be adopted to proactively confront the risks of water resources.

Understanding and simulating of three-dimensional subsurface hydrological partitioning in an alpine mountainous area, China

Critical zone(CZ)plays a vital role in sustaining biodiversity and humanity.However,flux quantification within CZ,particularly in terms of subsurface hydrological partitioning,remains a significant challenge.This study focused on quantifying subsurface hydrological partitioning,specifically in an alpine mountainous area,and highlighted the important role of lateral flow during this process.Precipitation was usually classified as two parts into the soil:increased soil water content(SWC)and lateral flow out of the soil pit.It was found that 65%–88%precipitation contributed to lateral flow.The second common partitioning class showed an increase in SWC caused by both precipitation and lateral flow into the soil pit.In this case,lateral flow contributed to the SWC increase ranging from 43%to 74%,which was notably larger than the SWC increase caused by precipitation.On alpine meadows,lateral flow from the soil pit occurred when the shallow soil was wetter than the field capacity.This result highlighted the need for three-dimensional simulation between soil layers in Earth system models(ESMs).During evapotranspiration process,significant differences were observed in the classification of subsurface hydrological partitioning among different vegetation types.Due to tangled and aggregated fine roots in the surface soil on alpine meadows,the majority of subsurface responses involved lateral flow,which provided 98%–100%of evapotranspiration(ET).On grassland,there was a high probability(0.87),which ET was entirely provided by lateral flow.The main reason for underestimating transpiration through soil water dynamics in previous research was the neglect of lateral root water uptake.Furthermore,there was a probability of 0.12,which ET was entirely provided by SWC decrease on grassland.In this case,there was a high probability(0.98)that soil water responses only occurred at layer 2(10–20 cm),because grass roots mainly distributed in this soil layer,and grasses often used their deep roots for water uptake during ET.To improve the estimation of soil water dynamics and ET,we established a random forest(RF)model to simulate lateral flow and then corrected the community land model(CLM).RF model demonstrated good performance and led to significant improvements in CLM simulation.These findings enhance our understanding of subsurface hydrological partitioning and emphasize the importance of considering lateral flow in ESMs and hydrological research.