The North American Regional Climate Change Assessment Program (NARCCAP) is an international effort designed to investigate the uncertainties in regional-scale projections of future climate and ...produce highresolution climate change scenarios using multiple regional climate models (RCMs) nested within atmosphere–ocean general circulation models (AOGCMs) forced with the Special Report on Emission Scenarios (SRES) A2 scenario, with a common domain covering the conterminous United States, northern Mexico, and most of Canada. The program also includes an evaluation component (phase I) wherein the participating RCMs, with a grid spacing of 50 km, are nested within 25 years of National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis II.
This paper provides an overview of evaluations of the phase I domain-wide simulations focusing on monthly and seasonal temperature and precipitation, as well as more detailed investigation of four subregions. The overall quality of the simulations is determined, comparing the model performances with each other as well as with other regional model evaluations over North America. The metrics used herein do differentiate among the models but, as found in previous studies, it is not possible to determine a “best” model among them. The ensemble average of the six models does not perform best for all measures, as has been reported in a number of global climate model studies. The subset ensemble of the two models using spectral nudging is more often successful for domain-wide root-mean-square error (RMSE), especially for temperature. This evaluation phase of NARCCAP will inform later program elements concerning differentially weighting the models for use in producing robust regional probabilities of future climate change.
Physical processes represented by the Monin–Obukhov bulk formula for momentum are investigated with field observations. We discuss important differences between turbulent mixing by the most energetic ...non-local, large, coherent turbulence eddies and local turbulent mixing as traditionally represented by K-theory (analog to molecular diffusion), especially in consideration of developing surface-layer stratification. The study indicates that the neutral state in a horizontally homogeneous surface layer described in the Monin–Obukhov bulk formula represents a special neutrality regardless of wind speed, for example, the surface layer with no surface heating/cooling. Under this situation, the Monin–Obukhov bulk formula agrees well with observations for heights to at least 30 m. As the surface layer is stratified, stably or unstably, the neutral state is achieved by mechanically generated turbulent mixing through the most energetic non-local coherent eddies. The observed neutral relationship between
u
∗
(the square root of the momentum flux magnitude) and wind speed
V
at any height is different from that described by the Monin–Obukhov formula except within several metres of the surface. The deviation of the Monin–Obukhov neutral
u
∗
-
V
linear relation from the observed one increases with height and contributes to the deteriorating performance of the bulk formula with increasing height, which cannot be compensated by stability functions. Based on these analyses, estimation of drag coefficients is discussed as well.
ABSTRACT
Since late 1970s, climate warming has been widely recognized. In the Midwest, farmers cannot rely on the normal calendar anymore, and it has become critically necessary to evaluate the most ...recent climate trends relative to growing season in order to conduct adaptation efforts for agriculture. Based on the homogenized historical monthly temperature and precipitation records during the period of 1980–2013 from 302 observing stations in the 12 Midwestern US states, we investigate the climate trends on four timescales: monthly, early growing season, late growing season, and the entire growing season. The climate metrics include maximum temperature, minimum temperature, average temperature, diurnal temperature range, and precipitation. Nonparametric Sen's Slope together with the nonparametric Mann–Kendall test is used to estimate the decadal trend and to detect the statistical significance. The results show that growing season average temperature has increased at a rate of 0.15 °C decade−1 over the Midwest United States. Within the growing season, minimum temperature is increasing faster in the early growing season, especially in June, while maximum temperature is increasing faster in the late growing season, especially in September. Spatially, statistically significant (p ≤ 0.05) growing season warming is more focused in the southern part of the region in the early growing season but in the northern part of the region in the late growing season. Over the Midwest, dominant trends in diurnal temperature range are decreasing during most months, with the exception of September. The majority of the locations show increasing trends in growing season precipitation, yet few are statistically significant. Furthermore, precipitation has been increasing in the early growing season but decreasing in the late growing season. This within‐season reversing trend in precipitation is found in 8 of 12 Corn Belt states: Illinois, Iowa, Michigan, Minnesota, Missouri, Nebraska, North Dakota, and Wisconsin.
Impact of climate change on streamflow in the Upper Mississippi River Basin is evaluated by use of a regional climate model (RCM) coupled with a hydrologic model, Soil and Water Assessment Tool ...(SWAT). The RCM we used resolves, at least partially, some fine‐scale dynamical processes that are important contributors to precipitation in this region and that are not well simulated by global models. The SWAT model was calibrated and validated against measured streamflow data using observed weather data and inputs from the U.S. Environmental Protection Agency Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) geographic information systems/database system. Combined performance of SWAT and RCM was examined using observed weather data as lateral boundary conditions in the RCM. The SWAT and RCM performed well, especially on an annual basis. Potential impacts of climate change on water yield and other hydrologic budget components were then quantified by driving SWAT with current and future scenario climates. Twenty‐one percent increase in future precipitation simulated by the RCM produced 18% increase in snowfall, 51% increase in surface runoff, and 43% increase in groundwater recharge, resulting in 50% net increase in total water yield in the Upper Mississippi River Basin on an annual basis. Uncertainty analysis showed that the simulated change in streamflow substantially exceeded model biases of the combined modeling system (with largest bias of 18%). While this does not necessarily give us high confidence in the actual climate change that will occur, it does demonstrate that the climate change “signal” stands out from the climate modeling (global plus regional) and impact assessment modeling (SWAT) “noise.”
Abstract
The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements in wind speed forecasts at a typical wind turbine hub height (80 m). An ...ensemble consisting of WRF model simulations with different planetary boundary layer (PBL) schemes showed little spread among the individual ensemble members for forecasting wind speed. A second configuration using three random perturbations of the Global Forecast System model produced more spread in the wind speed forecasts, but the ensemble mean possessed a higher mean absolute error (MAE). A third ensemble of different initialization times showed larger model spread, but model MAE was not compromised. In addition, postprocessing techniques such as training of the model for the day 2 forecast based on day 1 results and bias correction based on observed wind direction are examined. Ramp event forecasting was also explored. An event was considered to be a ramp event if the change in wind power was 50% or more of total capacity in either 4 or 2 h or less. This was approximated using a typical wind turbine power curve such that any wind speed increase or decrease of more than 3 m s−1 within the 6–12 m s−1 window (where power production varies greatly) in 4 h or less would be considered a ramp. Model MAE, climatology of ramp events, and causes were examined. All PBL schemes examined predicted fewer ramp events compared to the observations, and model forecasts for ramps in general were poor.
•Heating energy demand is decreasing while cooling energy demand is increasing.•Peak heating load decreasing and the peak cooling load increasing.•Quick and full service restaurants account for the ...greatest energy demand per area.•2.5% design condition may not be able to handle the future climatic conditions.
Typical climate conditions for the 20th century do not adequately describe the potential extreme conditions that will be encountered over the lifetime of buildings constructed today. We develop future typical meteorological year datasets that describe ambient environmental conditions that we utilize in the design and modifications of buildings to maintain human thermal comfort. Our use of multiple climate model scenarios provides uncertainty of the calculations of future energy demand. Going beyond previous studies, our results show that future energy demand by current buildings in the U.S. will decline for heating, and will increase for cooling. The increased air temperature poses a new challenge of increased humidity that will cause uncomfortable interior conditions for occupants. We identify the building features required for maintaining current thermal comfort understanding in future U. S. climates.
► Travel time distribution (TTD) of an unconfined aquifer estimated by three models. ► Models in order of increasing complexity: analytic, GIS, MODFLOW. ► All three models indicated exponential TTDs. ...► Good agreement among three models suggests applicability of simpler approaches. ► Spatial TTD maps correlated well in uplands, but poorly in floodplains.
It is critical that stakeholders are aware of the lag time necessary for conservation practices to demonstrate a positive impact on surface water quality. For solutes like nitrate that are transported primarily by the groundwater pathway, the lag time is a function of the groundwater travel time distribution (TTD). We used three models of varying levels of complexity to estimate the steady-state TTD of a shallow, unconfined aquifer in a small Iowa watershed: (a) analytic model, (b) GIS approach, and (c) MODFLOW model. The analytic model was the least input-intensive, whereas the GIS and MODFLOW approach required detailed data for model development. The resulting TTDs displayed an exponential distribution with good agreement among all the three methods (mean travel times ranging from 16.2years in the analytic model, 19.6years in GIS model and 20.5years in MODFLOW model). The greater deviation in the analytic model was attributed to the difficulty in estimation of a representative saturated thickness in an unconfined aquifer. The correspondence between the spatial travel time distributions generated by GIS and MODFLOW was a function of the landscape position, with greater correspondence in uplands compared to floodplains. In the floodplains the land surface slope is a poor approximation of the water table gradient that is captured by the MODFLOW model but not the GIS that uses the land surface as a surrogate for the water table. Study results indicate that except for cases where there are marked differences between water table surface and land surface, simpler approaches (analytic and GIS) can be used to estimate TTDs required for the design and optimal placement of conservation practices and communicating lag times issues to the public.
Recent wind farm studies have revealed elevated nighttime surface temperatures but have not validated physical mechanisms that create the observed effects. We report measurements of concurrent ...differences in surface wind speed, temperature, fluxes, and turbulence upwind and downwind of two turbine lines at the windward edge of a utility‐scale wind farm. On the basis of these measurements, we offer a conceptual model based on physical mechanisms of how wind farms affect their own microclimate. Periods of documented curtailment and zero‐power production of the wind farm offer useful opportunities to rigorously evaluate the microclimate impact of both stationary and operating turbines. During an 80 min nighttime wind farm curtailment, we measured abrupt and large changes in turbulent fluxes of momentum and heat leeward of the turbines. At night, wind speed decreases in the near wake when turbines are off but abruptly increases when turbine operation is resumed. Our measurements are compared with Moderate Resolution Imaging Spectroradiometer Terra and Aqua satellite measurements reporting wind farms to have higher nighttime surface temperatures. We demonstrate that turbine wakes modify surface fluxes continuously through the night, with similar magnitudes during the Terra and Aqua transit periods. Cooling occurs in the near wake and warming in the far wake when turbines are on, but cooling is negligible when turbines are off. Wind speed and surface stratification have a regulating effect of enhancing or decreasing the impact on surface microclimate due to turbine wake effects.
Key Points
Nighttime fluxes and wind speed increase when turbines are on and wind speed decreases for turbines off
No distinction of stronger warming between nighttime Terra and Aqua satellite overpass periods
Nighttime fluxes simultaneously revert to ambient levels during an 80 min shutdown of the wind farm
CROP WIND ENERGY EXPERIMENT (CWEX) Rajewski, Daniel A.; Takle, Eugene S.; Lundquist, Julie K. ...
Bulletin of the American Meteorological Society,
05/2013, Letnik:
94, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Perturbations of mean and turbulent wind characteristics by large wind turbines modify fluxes between the vegetated surface and the lower boundary layer. While simulations have suggested that wind ...farms could significantly change surface fluxes of heat, momentum, momentum, moisture, and CO₂ over hundreds of square kilometers, little observational evidence exists to test these predictions. Quantifying the influences of the “turbine layer” is necessary to quantify how surface fluxes are modified and to better forecast energy production by a wind farm. Changes in fluxes are particularly important in regions of intensely managed agriculture where crop growth and yield are highly dependent on subtle changes in moisture, heat, and CO₂. Furthermore, speculations abound about the possible mesoscale consequences of boundary layer changes that are produced by wind farms. To address the lack of observations to answer these questions, we developed the Crop Wind Energy Experiment (CWEX) as a multiagency, multiuniversity field program in central Iowa. Throughout the summer of 2010, surface fluxes were documented within a wind farm test site and a 2-week deployment of a vertically pointing lidar quantified wind profiles. In 2011, we expanded measurements at the site by deploying six flux stations and two wind-profiling lidars to document turbine wakes. The results provide valuable insights into the exchanges over a surface that has been modified by wind turbines and a basis for a more comprehensive measurement program planned for the summer in 2014.
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