Eugene S. Takle

The North American Regional Climate Change Assessment Program: Overview of Phase I Results

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 i...

Hydrological responses to dynamically and statistically downscaled climate model output

Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/ National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic simulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

Project to Intercompare Regional Climate Simulations (PIRCS): Description and initial results

The first simulation experiment and output archives of the Project to Intercompare Regional Climate Simulations (PIRCS) is described. Initial results from simulations of the summer 1988 drought over the central United States indicate that limited-area models forced by large-scale information at the lateral boundaries reproduce bulk temporal and spatial characteristics of meteorological fields. In particular, the 500 hPa height field time average and temporal variability are generally well simulated by all participating models. Model simulations of precipitation episodes vary depending on the scale of the dynamical forcing. Organized synoptic-scale precipitation systems are simulated deterministically in that precipitation occurs at close to the same time and location as observed (although amounts may vary from observations). Episodes of mesoscale and convective precipitation are represented in a more stochastic sense, with less precise agreement in temporal and spatial patterns. Simulated surface energy fluxes show broad similarity with the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) observations in their temporal evolution and time average diurnal cycle. Intermodel differences in midday Bowen ratio tend to be closely associated with precipitation differences. Differences in daily maximum temperatures also are linked to Bowen ratio differences, indicating strong local, surface influence on this field. Although some models have bias with respect to FIFE observations, all tend to reproduce the synoptic variability of observed daily maximum and minimum temperatures. Results also reveal the advantage of an intercomparison in exposing common tendencies of models despite their differences in convective and surface parameterizations and different methods of assimilating lateral boundary conditions.

Altered hydrologic feedback in a warming climate introduces a ''warming hole''

[2] Changes in forcing of the climate system can trigger new or altered feedback processes. We have found evidence of such a feedback in the hydrological cycle of the central U.S. that creates a regional minimum within the continentalscale pattern of warming in an enhanced greenhouse-gas climate. The effect of this particular feedback is amplified because a change is introduced into a slowly varying component of the hydrologic cycle (soil moisture) thereby extending the impact of increased summer precipitation to later months in the annual cycle. We investigated these processes using a regional climate model (RCM) to downscale contemporary and future scenario climates from a global climate model (GCM) [Johns et al., 1997] in order to project resolution-enhanced patterns of climate change for the continental U.S. Previous work has shown that the downscaled climate from this approach provides a reasonable representation of the atmosphere-hydrology linkage in this region [Pan et al., 2001a; Gutowski et al., 2003]. [3] The most notable feature in the projected climate is a local minimum of warming (hereinafter called a ‘‘warming hole’’) in the central U.S. during summer (June, July and August) (Figure 1a). The increase in daily maximum surface air temperature (dTmax) in summer at the center of the warming hole is less than 0.5 K, which is substantially less than the mean increase of about 3 K over the continental U.S. The ground temperature has an even stronger warming hole with 0.5 K cooling, rather than warming, in the center. The warming hole starts to develop in June, reaches its maximum value in September, and gradually diminishes through October and November (Figure 1b). The purpose of this paper is to analyze the processes underlying the reduced warming and to show the hole’s links to observed climate trends. 2. Methods

Use of regional climate model output for hydrologic simulations

Abstract Daily precipitation and maximum and minimum temperature time series from a regional climate model (RegCM2) configured using the continental United States as a domain and run on a 52-km (approximately) spatial resolution were used as input to a distributed hydrologic model for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado; east fork of the Carson River near Gardnerville, Nevada; and Cle Elum River near Roslyn, Washington). For comparison purposes, spatially averaged daily datasets of precipitation and maximum and minimum temperature were developed from measured data for each basin. These datasets included precipitation and temperature data for all stations (hereafter, All-Sta) located within the area of the RegCM2 output used for each basin, but excluded station data used to calibrate the hydrologic model. Both the RegCM2 output and All-Sta data capture the gross aspects of the seasonal cycles of precipit...

Impacts of climate change on streamflow in the Upper Mississippi River Basin: A regional climate model perspective

[1] 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.’’ INDEX TERMS: 1655 Global Change: Water cycles (1836); 1860 Hydrology: Runoff and streamflow; 1866 Hydrology: Soil moisture; KEYWORDS: climate change, streamflow, SWAT Citation: Jha, M., Z. Pan, E. S. Takle, and R. Gu (2004), Impacts of climate change on streamflow in the Upper Mississippi River Basin: A regional climate model perspective, J. Geophys. Res., 109, D09105, doi:10.1029/2003JD003686.

Note on the Use of Weibull Statistics to Characterize Wind-Speed Data

Abstract A hybrid density function is given for describing wind-speed distributions having nonzero probability of “calm.” A Weibull probability graph paper designed specifically for plotting wind-speed distributions is used to determine distribution parameters to within a few percent of values obtained by the maximum likelihood technique. Data from the National Weather Service are used to demonstrate the use of the hybrid density function and the Weibull graph paper.

Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)

We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.

Evaluation of uncertainties in regional climate change simulations

We have run two regional climate models (RCMs) forced by three sets of initial and boundary conditions to form a 2×3 suite of 10-year climate simulations for the continental United States at approximately 50 km horizontal resolution. The three sets of driving boundary conditions are a reanalysis, an atmosphere-ocean coupled general circulation model (GCM) current climate, and a future scenario of transient climate change. Common precipitation climatology features simulated by both models included realistic orographic precipitation, east-west transcontinental gradients, and reasonable annual cycles over different geographic locations. However, both models missed heavy cool-season precipitation in the lower Mississippi River basin, a seemingly common model defect. Various simulation biases (differences) produced by the RCMs are evaluated based on the 2×3 experiment set in addition to comparisons with the GCM simulation. The RCM performance bias is smallest, whereas the GCM-RCM downscaling bias (difference between GCM and RCM) is largest. The boundary forcing bias (difference between GCM current climate driven run and reanalysis-driven run) and intermodel bias are both largest in summer, possibly due to different subgrid scale processes in individual models. The ratio of climate change to biases, which we use as one measure of confidence in projected climate changes, is substantially larger than 1 in several seasons and regions while the ratios are always less than 1 in summer. The largest ratios among all regions are in California. Spatial correlation coefficients of precipitation were computed between simulation pairs in the 2×3 set. The climate change correlation is highest and the RCM performance correlation is lowest while boundary forcing and intermodel correlations are intermediate. The high spatial correlation for climate change suggests that even though future precipitation is projected to increase, its overall continental-scale spatial pattern is expected to remain relatively constant. The low RCM performance correlation shows a modeling challenge to reproduce observed spatial precipitation patterns.

A numerical simulation of boundary-layer flows near shelterbelts

We have developed a shelterbelt boundary-layer numerical model to study the patterns and dynamic processes relating to flow interaction with shelterbelts. The model simulates characteristics of all three zones of airflow passing over and through shelterbelts: the windward windspeed-reduction zone, the overspeeding zone above the shelterbelt, and the leeward windspeed-reduction zone. Locations of the maximum windspeed reduction and recirculation zone, as well as the leeward windspeed-recovery rate are well simulated by the model. Where comparisons with field measurements and wind-tunnel experiments were possible, the model demonstrated good performance for flows over and through shelters ranging from almost completely open to almost solid.The dynamic pressure resulting from the convergence and divergence of the flow field alters the perturbation pressure field. The disturbed pressure controls not only the formation of the separated flow but also the location of maximum windspeed reduction, streamline curvature, speed-up over the shelterbelt, and leeward windspeed recovery rate. The interaction of pressure with the flow produces complex flow patterns, the characteristics of which are determined, to a great extent, by shelterbelt structure.