Aihui Wang

Soil Moisture Drought in China, 1950–2006

AbstractFour physically based land surface hydrology models driven by a common observation-based 3-hourly meteorological dataset were used to simulate soil moisture over China for the period 1950–2006. Monthly values of total column soil moisture from the simulations were converted to percentiles and an ensemble method was applied to combine all model simulations into a multimodel ensemble from which agricultural drought severities and durations were estimated. A cluster analysis method and severity–area–duration (SAD) algorithm were applied to the soil moisture data to characterize drought spatial and temporal variability. For drought areas greater than 150 000 km2 and durations longer than 3 months, a total of 76 droughts were identified during the 1950–2006 period. The duration of 50 of these droughts was less than 6 months. The five most prominent droughts, in terms of spatial extent and then duration, were identified. Of these, the drought of 1997–2003 was the most severe, accounting for the majority...

Multimodel Ensemble Reconstruction of Drought over the Continental United States

Abstract Retrospectively simulated soil moisture from an ensemble of six land surface/hydrological models was used to reconstruct drought events over the continental United States for the period 1920–2003. The simulations were performed at one-half-degree spatial resolution, using a common set of atmospheric forcing data and model-specific soil and vegetation parameters. Monthly simulated soil moisture was converted to percentiles using Weibull plotting position statistics, and the percentiles were then used to represent drought severities and durations. An ensemble method, based on an inverse mapping of the average of the individual model’s soil moisture percentiles, was also used to combine all models’ simulations. Major results are 1) all models and the ensemble reconstruct the known severe drought events during the last century. The spatial extents and severities of drought are plausible for the individual models although substantial among-model disparities exist. 2) The simulations are in more agreem...

Evaluating runoff simulations from the Community Land Model 4.0 using observations from flux towers and a mountainous watershed

[1] Previous studies using the Community Land Model (CLM) focused on simulating land-atmosphere interactions and water balance on continental to global scales, with limited attention paid to its capability for hydrologic simulations at watershed or regional scales. This study evaluates the performance of CLM 4.0 (CLM4) for hydrologic simulations and explores possible directions of improvement. Specifically, it is found that CLM4 tends to produce unrealistically large temporal variations of runoff for applications at a mountainous catchment in the northwest United States, where subsurface runoff is dominant, as well as at a few flux tower sites spanning a wide range of climate and site conditions in the United States. Runoff simulations from CLM4 can be improved by (1) increasing spatial resolution of the land surface representations and (2) calibrating model parameter values. We also demonstrate that runoff simulations may be improved by implementing alternative runoff generation schemes such as those from the variable infiltration capacity (VIC) model or the TOPMODEL formulations with a more general power law-based transmissivity profile, which will be explored in future studies. This study also highlights the importance of evaluating both energy and water fluxes in the application of land surface models across multiple scales.

Surface Skin Temperature and the Interplay between Sensible and Ground Heat Fluxes over Arid Regions

AbstractOver arid regions, two community land models [Noah and Community Land Model (CLM)] still have difficulty in realistically simulating the diurnal cycle of surface skin temperature. Based on theoretical arguments and synthesis of previous observational and modeling efforts, three revisions are developed here to address this issue. The revision of the coefficients in computing roughness length for heat significantly reduces the underestimate of daytime skin temperature but has a negligible effect on nighttime skin temperature. The constraints of the minimum friction velocity and soil thermal conductivity help improve nighttime skin temperature under weak wind and dry soil conditions. These results are robust in both Noah and CLM, as well as in Noah, with 4 versus 10 soil layers based on in situ data at the Desert Rock site in Nevada with a monthly averaged diurnal amplitude of 31.7 K and the Gaize site over Tibet, China, with an amplitude of 44.6 K. While these revisions can be directly applied to CL...

Time Scales of Land Surface Hydrology

Abstract This paper intends to investigate the time scales of land surface hydrology and enhance the understanding of the hydrological cycle between the atmosphere, vegetation, and soil. A three-layer model for land surface hydrology is developed to study the temporal variation and vertical structure of water reservoirs in the vegetation–soil system in response to precipitation forcing. The model is an extension of the existing one-layer bucket model. A new time scale is derived, and it better represents the response time scale of soil moisture in the root zone than the previously derived inherent time scale (i.e., the ratio of the field capacity to the potential evaporation). It is found that different water reservoirs of the vegetation–soil system have different time scales. Precipitation forcing is mainly concentrated on short time scales with small low-frequency components, but it can cause long time-scale disturbances in the soil moisture of root zone. This time scale increases with soil depth, but i...

Seasonal evapotranspiration changes (1983–2006) of four large basins on the Tibetan Plateau

Lack of reliable historical basin-scale evapotranspiration (ET) estimates is a bottleneck for water balance analyses and model evaluation on the Tibetan Plateau (TP). This study looks at four large basins on the TP to develop a general approach suitable for large river basins to estimate historical monthly ET. Five existing global ET products are evaluated against monthly ET estimated by the water balance method as a residual from precipitation (P), terrestrial water storage change (Delta S), and discharge (R). The five ET products exhibit similar seasonal variability, despite of the different amounts among them. A bias correction method, based on the probability distribution mapping between the reference ET and the five products during 2003-2012, effectively removes nearly all biases and significantly increases the reliability of the products. Then, the surface water balance changes for the four basins are analyzed based on the corrected ET products as well as observed P and R during 1983-2006. A trend analysis shows an upward trend for ET in the four basins for all seasons during the past three decades, along with the regional warming, as well as a dominating increasing trend in P and negative trend in R. (Less)

Consistent Parameterization of Roughness Length and Displacement Height for Sparse and Dense Canopies in Land Models

Abstract While progress has been made in the treatment of turbulence below, within, and above canopy in land models, not much attention has been paid to the convergence of canopy roughness length and displacement height to bare soil values as the above-ground biomass, or the sum of leaf and stem area indices, becomes zero. Preliminary formulations have been developed to ensure this convergence for the Community Land Model version 3 (CLM3) and are found to significantly improve the wintertime simulation of sensible heat flux (SH) compared with observational data over the Cabauw site in the Netherlands. The simulation of latent heat flux (LH) is also moderately improved. For global offline CLM3 simulations, the new formulations change SH by more than 5 W m−2 over many regions, while the change of LH is less than 1 W m−2 over most of the regions.

Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model version 4.0, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, and in situ observations from the Coordinated Energy and Water Cycle Observation Project in 2003 were compared. Both modeled and MODIS Ts were interpolated to the 12 station locations, and comparisons were performed under MODIS clear-sky condition. Over four semiarid stations, both MODIS and modeled Ts show negative biases compared to in situ data, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS-observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. (2012) bring the modeled Ts closer to MODIS during the day and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

What is monthly mean land surface air temperature

Land surface air temperature is one of the fundamental variables in weather and climate observations, modeling, and applications. Its monthly mean has been computed as the average of daily maximum and minimum temperatures [Jones et al., 1999]. This is different from the true monthly mean temperature, which is defined as the integral of the continuous temperature measurements in a month divided by the integration period and can be very accurately represented using hourly data, as has long been recognized [e.g., Brooks, 1921]. We argue, from scientific, technological, and historical perspectives, that it is time to compute the true monthly mean using hourly data for the national and international climate data record

Range of monthly mean hourly land surface air temperature diurnal cycle over high northern latitudes

Daily maximum and minimum temperatures over global land are fundamental climate variables, and their difference represents the diurnal temperature range (DTR). While the differences between the monthly averaged DTR (MDTR) and the range of monthly averaged hourly temperature diurnal cycle (RMDT) are easy to understand qualitatively, their differences have not been quantified over global land areas. Based on our newly developed in situ data (Climatic Research Unit) reanalysis (Modern-Era Retrospective analysis for Research and Applications) merged hourly temperature data from 1979 to 2009, RMDT in January is found to be much smaller than that in July over high northern latitudes, as it is much more affected by the diurnal radiative forcing than by the horizontal advection of temperature. In contrast, MDTR in January is comparable to that in July over high northern latitudes, but it is much larger than January RMDT, as it primarily reflects the movement of lower frequency synoptic weather systems. The area-averaged RMDT trends north of 40°N are near zero in November, December, and January, while the trends of MDTR are negative. These results suggest the need to use both the traditional MDTR and RMDT suggested here in future observational and modeling studies. Furthermore, MDTR and its trend are more sensitive to the starting hour of a 24 h day used in the calculations than those for RMDT, and this factor also needs to be considered in model evaluations using observational data.