Land-Cover Change and the ‘‘Dust Bowl’’ Drought in the U.S. Great Plains

The North American Dust Bowl drought during the 1930s had devastating environmental and societal impacts. Comprehending the causes of the drought has been an ongoing effort in order to better predict similar droughts and mitigate their impacts. Among the potential causes of the drought are sea surface temperature (SST) anomalies in the tropical Pacific Ocean and strengthened local sinking motion as a feedback to degradation of the land surface condition leading up to and during the drought. Limitations on these causes are the lack of a strong tropical SST anomaly during the drought and lack of local anomaly in moisture supply to undercut the precipitation in the U.S. Great Plains. This study uses high-resolution modeling experiments and quantifies an effect of the particular Great Plains land cover in the 1930s that weakens the southerly moisture flux to the region. This effect lowers the average precipitation, making the Great Plains more susceptible to drought. When drought occurs, the land-cover effect enhances its intensity and prolongs its duration. Results also show that this land-cover effect is comparable in magnitude to the effect of the 1930s large-scale circulation anomaly. Finally, analysis of the relationship of these two effects suggests that while lowering the precipitation must have contributed to the Dust Bowl drought via the 1930s land-cover effect, the initiation of and recovery from that drought would likely result from large-scale circulation changes, either of chaotic origin or resulting from combinations of weak SST anomalies and other forcing

Land-Cover Change and the ‘‘Dust Bowl’’ Drought in the U.S. Great Plains

The North American Dust Bowl drought during the 1930s had devastating environmental and societal impacts. Comprehending the causes of the drought has been an ongoing effort in order to better predict similar droughts and mitigate their impacts. Among the potential causes of the drought are sea surface temperature (SST) anomalies in the tropical Pacific Ocean and strengthened local sinking motion as a feedback to degradation of the land surface condition leading up to and during the drought. Limitations on these causes are the lack of a strong tropical SST anomaly during the drought and lack of local anomaly in moisture supply to undercut the precipitation in the U.S. Great Plains. This study uses high-resolution modeling experiments and quantifies an effect of the particular Great Plains land cover in the 1930s that weakens the southerly moisture flux to the region. This effect lowers the average precipitation, making the Great Plains more susceptible to drought. When drought occurs, the land-cover effect enhances its intensity and prolongs its duration. Results also show that this land-cover effect is comparable in magnitude to the effect of the 1930s large-scale circulation anomaly. Finally, analysis of the relationship of these two effects suggests that while lowering the precipitation must have contributed to the Dust Bowl drought via the 1930s land-cover effect, the initiation of and recovery from that drought would likely result from large-scale circulation changes, either of chaotic origin or resulting from combinations of weak SST anomalies and other forcing

A warm-season comparison of WRF coupled to the CLM4.0, Noah-MP, and Bucket hydrology land surface schemes over the central USA

In climate modeling studies, there is a need to choose a suitable land surface model (LSM) while adhering to available resources. In this study, the viability of three LSM options (Community Land Model version 4.0 [CLM4.0], Noah-MP, and the five-layer thermal diffusion [Bucket] scheme) in the Weather Research and Forecasting model version 3.6 (WRF3.6) was examined for the warm season in a domain centered on the central USA. Model output was compared to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, a gridded observational dataset including mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, latent heat (LH) flux, sensible heat (SH) flux, and soil water content (SWC) were compared to observations from sites in the Central and Southern Great Plains region. An overall warm bias was found in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. These three LSMs produced similar patterns of wet and dry biases. Model output of SWC and LH/SH fluxes were compared to observations, and did not show a consistent bias. Both sophisticated LSMs appear to be viable options for simulating the effects of land use change in the central USA

Non-Hydrostatic Regcm4 (Regcm4-NH): Evaluation of Precipitation Statistics at the Convection-Permitting Scale over Different Domains

Recent studies over different geographical regions of the world have proven that regional climate models at the convection-permitting scale (CPMs) improve the simulation of precipitation in many aspects, such as the diurnal cycle, precipitation frequency, intensity, and extremes at daily-but even more at hourly-time scales. Here, we present an evaluation of climate simulations with the newly developed RegCM4-NH model run at the convection-permitting scale (CP-RegCM4-NH) for a decade-long period, over three domains covering a large European area. The simulations use a horizontal grid spacing of similar to 3 km and are driven by the ERA-Interim reanalysis through an intermediate driving RegCM4-NH simulation at similar to 12 km grid spacing with parameterized deep convection. The km-scale simulations are evaluated against a suite of hourly observation datasets with high spatial resolutions and are compared to the coarse-resolution driving simulation in order to assess improvements in precipitation from the seasonal to hourly scale. The results show that CP-RegCM4-NH produces a more realistic representation of precipitation than the coarse-resolution simulation over all domains. The most significant improvements were found for intensity, heavy precipitation, and precipitation frequency, both on daily and hourly time scales in all seasons. In general, CP-RegCM4-NH tends to correctly produce more intense precipitation and to reduce the frequency of events compared to the coarse-resolution one. On the daily scale, improvements in CP simulations are highly region dependent, with the best results over Italy, France, and Germany, and the largest biases over Switzerland, the Carpathians, and Greece, especially during the summer seasons. At the hourly scale, the improvement in CP simulations for precipitation intensity and spatial distribution is clearer than at the daily timescale. In addition, the representation of extreme events is clearly improved by CP-RegCM4-NH, particularly at the hourly time scale, although an overestimation over some subregions can be found. Although biases between the model simulations at the km-scale and observations still exist, this first application of CP-RegCM4-NH at high spatial resolution indicates a clear benefit of convection-permitting simulations and encourages further assessments of the added value of km-scale model configurations for regional climate change projections.ISSN:2073-443

Assessing mean climate change signals in the global CORDEX-CORE ensemble

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25[Formula: see text] (0.22[Formula: see text]) versus 50[Formula: see text] (0.44[Formula: see text])) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies