Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field

The effect of climate change on crop production and nitrate-nitrogen (NO3-N) pollution from subsurface drained fields is of a great concern. Using the calibrated and validated RZWQM2 (coupled with CERES-Maize and CROPGRO in DSSAT), the potential effects of climate change and elevated atmospheric CO2 concentrations (CO2) on tile drainage volume, NO3-N losses, and crop production were assessed integrally for the first time for a corn-soybean rotation cropping system near Gilmore City, Iowa. RZWQM2 simulated results under 20-year observed historical weather data (1990–2009) and ambient CO2 were compared to those under 20-year projected future meteorological data (2045–2064) and elevated CO2, with all management practices unchanged. The results showed that, under the future climate, tile drainage, NO3-N loss and flow-weighted average NO3-N concentration (FWANC) increased by 4.2 cm year−1 (+14.5 %), 11.6 kg N ha−1 year−1 (+33.7 %) and 2.0 mg L−1 (+16.4 %), respectively. Yields increased by 875 kg ha−1 (+28.0 %) for soybean [Glycine max (L.) Merr.] but decreased by 1380 kg ha−1(−14.7 %) for corn (Zea mays L.). The yield of the C3 soybean increased mostly due to CO2enrichment but increased temperature had negligible effect. However, the yield of C4 corn decreased largely because of fewer days to physiological maturity due to increased temperature and limited benefit of elevated CO2 to corn yield under subhumid climate. Relative humidity, short wave radiation and wind speed had small or negligible impacts on FWANC or grain yields. With the predicted trend, this study suggests that to mitigate NO3-N pollution from subsurface drained corn-soybean field in Iowa is a more challenging task in the future without changing current management practices. This study also demonstrates the advantage of an agricultural system model in assessing climate change impacts on water quality and crop production. Further investigation on management practice adaptation is needed

Dynamics of Cloud-Top Generating Cells in Winter Cyclones. Part III: Shear and Convective Organization

Cloud-top generating cells (GCs) are a common feature atop stratiform clouds within the comma head of winter cyclones. The dynamics of cloud-top GCs are investigated using very high-resolution idealized WRF Model simulations to examine the role of shear in modulating the structure and intensity of GCs. Simulations were run for the same combinations of radiative forcing and instability as in Part II of this series, but with six different shear profiles ranging from 0 to 10ms21 km21 within the layer encompassing the GCs. The primary role of shear was to modulate the organization of GCs, which organized as closed convective cells in simulations with radiative forcing and no shear. In simulations with shear and radiative forcing, GCs organized in linear streets parallel to the wind. No GCs developed in the initially stable simulations with no radiative forcing. In the initially unstable and neutral simulations with no radiative forcing or shear, GCs were exceptionally weak, with no clear organization. In moderate-shear (Du/Dz 5 2, 4ms21 km21) simulations with no radiative forcing, linear organization of the weak cells was apparent, but this organization was less coherent in simulations with high shear (Du/Dz 5 6, 8, 10ms21 km21). The intensity of the updrafts was primarily related to the mode of radiative forcing but was modulated by shear. The more intense GCs in nighttime simulations were either associated with no shear (closed convective cells) or strong shear (linear streets). Updrafts within GCs under conditions with radiative forcing were typically ;1–2 ms21 with maximum values , 4ms21

Data support for "Impact of hygroscopic CCN and turbulence on cloud droplet growth: A parcel-DNS approach"

This dataset provide the DNS model output for studying aerosol-cloud interaction and impact of aerosols in cloud development and rain initiation. The relevant manuscript is under preparation

A Trial to Improve Surface Heat Exchange Simulation through Sensitivity Experiments over a Desert Steppe Site

It is still a daunting challenge for land surface models (LSMs) to correctly represent surface heat exchange for water-limited desert steppe ecosystems. This study aims to improve the ability of the Noah LSM to simulate surface heat fluxes through addressing uncertainties in precipitation forcing conditions, rapidly evolving vegetation properties, soil hydraulic properties (SHPs), and key parameterization schemes. Three years (2008-10) of observed surface heat fluxes and soil temperature over a desert steppe site in Inner Mongolia, China, are used to verify model simulations. The proper seasonal distribution of precipitation, along with more realistic vegetation parameters, can improve the simulation of sensible heat flux (SH) and the seasonal variability of latent heat flux. Correctly representing the low-surface exchange coefficient is crucial for improving SH for short vegetation like this desert steppe site. Relating C-zil, the coefficient in the Noah surface exchange coefficient calculation, with canopy height h improves the simulated SH and the diurnal range of soil temperature over the simulation compared with using the default constant C-zil. The exponential water stress formulation proposed here for the Jarvis scheme improves the partitioning between soil evaporation and transpiration. It is found that the surface energy fluxes are very sensitive to SHPs. This study highlights the important role of the proper parameter values and appropriate parameterizations for the surface exchange coefficient and water stress function in canopy resistance in capturing the observed surface energy fluxes and soil temperature variations for this desert steppe site