Abstract

Large-scale variability of moisture in the upper troposphere is examined using TIROS (Television Infrared Observation Satellite) Operational Vertical Sounder (TOYS) satellite observations and ECMWF model analyses from 1989 in the latitude band from 40° to 40°S. To compare these dissimilar datasets, upwelling radiances were computed for the 6-7-μm water vapor band from the ECMWF temperature and moisture analyses, and these computed radiances were compared to the corresponding TOVS satellite observations. The ECMWF-based radiances reproduce the general locations and seasonal cycle of the TOVS-observed moisture features, particularly after an improved convective parameterization scheme was adopted by ECMWF in May 1989. However, the ECMWF analysis scheme still results in much milder lateral moisture gradients and seasonal contrasts than indicated by the TOYS observations. Seasonally, the upper troposphere in each hemisphere dries in winter and moistens in summer, but there are regions in each hemisphere that run counter to this seasonal trend, apparently depending on continental- and monsoon-scale dynamics. Dynamically, the TOVS-observed regions of significant subtropical dryness are correlated with persistent subsidence indicated by ECMWF 300-mb vertical velocity analyses. The TOVS radiance observations indicate large variations in space and time of the upper-tropospheric moisture field, which are not fully captured by the ECMWF analyses.

Abstract

It is shown that the distribution of upper-tropospheric humidity (UTH) in the cloud-free Tropics can be simulated with a simple model in which air expelled from moist convective regions is dried by subsidence along its trajectory. The distribution of UTH is analyzed in the tropical eastern Pacific using moisture data retrieved from GOES 6.7-μm observations during September 1992. The analysis examines the variation in moisture along horizontal trajectories derived from European Centre for Medium-Range Weather Forecasts wind analyses. Trajectory analysis is used to trace the convective sources of subtropical air. For the eastern subtropical Pacific, convective sources lie entirely outside the dry region, and are predominately in the ITCZ and over South America, with some air tracing to midlatitudes. The analysis also shows that, over large parts of the eastern subtropical Pacific, air has advected horizontally for five or more days since exiting convection. Composites of many trajectories from specific source regions show that radiatively driven subsidence appears to control the decrease in relative humidity away from convection. The observed UTH distribution along trajectories is then simulated with a simple model of horizontal advection and subsidence of an initial convective moisture profile. Finally, the monthly mean horizontal distribution of water vapor is simulated using this model of moisture transport and the computed distribution of the mean time since air at any location was in a convectively active region.

Abstract

A trajectory analysis of the Community Climate Model version 3 (CCM3) moisture simulation is used to show that the model simulates upper-tropospheric moisture observations better than would be inferred from a traditional geographical comparison. The upper-tropospheric moisture simulation is compared to upper-tropospheric moisture derived from Geostationary Operational Environmental Satellite 6.7-μm observations for September 1992. Trajectories start in convective regions of the Tropics and are followed into nonconvective subsidence regions. Moisture and pressure along the trajectories are determined for both the model and observations. Humidity values as a function of subsidence agree much better between observations and model than do geographical grid box comparisons, because the model does not simulate details in the large-scale flow pattern precisely. The relative humidity decreases slightly more slowly with subsidence along trajectories in the CCM3 simulation than in observations.

Abstract

Trends in extreme temperature and precipitation in two regional climate model simulations forced by two global climate models are compared with observed trends over the western United States. The observed temperature extremes show substantial and statistically significant trends across the western United States during the late twentieth century, with consistent results among individual stations. The two regional climate models simulate temporal trends that are consistent with the observed trends and reflect the anthropogenic warming signal. In contrast, no such clear trends or correspondence between the observations and simulations is found for extreme precipitation, likely resulting from the dominance of the natural variability over systematic climate change during the period. However, further analysis of the variability of precipitation extremes shows strong correspondence between the observed precipitation indices and increasing oceanic Niño index (ONI), with regionally coherent patterns found for the U.S. Northwest and Southwest. Both regional climate simulations reproduce the observed relationship with ONI, indicating that the models can represent the large-scale climatic links with extreme precipitation. The regional climate model simulations use the Weather Research and Forecasting (WRF) Model and Hadley Centre Regional Model (HadRM) forced by the ECHAM5 and the Hadley Centre Climate Model (HadCM) global models for the 1970–2007 time period. Comparisons are made to station observations from the Historical Climatology Network (HCN) locations over the western United States. This study focused on temperature and precipitation extreme indices recommended by the Expert Team on Climate Change Detection Monitoring and Indices (ETCCDMI).

Abstract

Extreme precipitation and temperature indices in reanalysis data and regional climate models are compared to station observations. The regional models represent most indices of extreme temperature well. For extreme precipitation, finer grid spacing considerably improves the match to observations. Three regional models, the Weather Research and Forecasting (WRF) at 12- and 36-km grid spacing and the Hadley Centre Regional Model (HadRM) at 25-km grid spacing, are forced with global reanalysis fields over the U.S. Pacific Northwest during 2003–07. The reanalysis data represent the timing of rain-bearing storms over the Pacific Northwest well; however, the reanalysis has the worst performance at simulating both extreme precipitation indices and extreme temperature indices when compared to the WRF and HadRM simulations. These results suggest that the reanalysis data and, by extension, global climate model simulations are not sufficient for examining local extreme precipitations and temperatures owing to their coarse resolutions. Nevertheless, the large-scale forcing is adequately represented by the reanalysis so that regional models may simulate the terrain interactions and mesoscale processes that generate the observed local extremes and frequencies of extreme temperature and precipitation.

Abstract

In this paper, the small-scale (<1 km) structure of temperature near the tropopause, as indicated by ozone concentration, is examined using data recorded during GALE from the NCAR Sabreliner. A systematic difference is observed in the temperature microstructure of the troposphere and stratosphere in qualitative agreement with evidence from VHF radar observations. Spectral distribution of the temperature variations also differs across the tropopause.

Abstract

Extreme precipitation events impact the Pacific Northwest during winter months, causing flooding, landslides, extensive property damage, and loss of life. Outstanding questions about such events include whether there are a range of associated synoptic evolutions, whether such evolutions vary along the coast, and the associated rainfall duration and variability. To answer these questions, this study uses 60 years of National Climatic Data Center (NCDC) daily precipitation observations to identify the top 50 events in two-day precipitation at six coastal stations from northern California to northwest Washington. NCEP–NCAR reanalysis data were used to construct synoptic composite evolutions of these events for each coastal location. Most regional flooding events are associated with precipitation periods of 24 h or less, and two-day precipitation totals identify nearly all major events. Precipitation areas of major events are generally narrow, roughly 200 km in width, and most are associated with atmospheric rivers. Composite evolutions indicate negative anomalies in sea level pressure and upper-level height in the central Pacific, high pressure anomalies over the southwest United States, large positive 850-hPa temperature anomalies along the coast and offshore, and enhanced precipitable water and integrated water vapor fluxes over southwest to northeast swaths. A small subset of extreme precipitation events over the southern portion of the domain is associated with a very different synoptic evolution: a sharp trough in northwesterly flow and post-cold-frontal convection. High precipitable water values are more frequent during the summer, but are not associated with heavy precipitation due to upper-level ridging over the eastern Pacific and weak onshore flow that limit upward vertical velocities.

Abstract

This study investigates whether GCM-simulated precipitation is a good predictor for regional precipitation over Washington and Oregon. In order to allow for a detailed comparison of the estimated precipitation with observations, the simulated precipitation is taken from the NCEP–NCAR reanalysis, which nearly perfectly represents the historic pressure, temperature, and humidity, but calculates precipitation according to the model physics and parameterizations.

Three statistical downscaling methods are investigated: (i) local rescaling of the simulated precipitation, and two newly developed methods, namely, (ii) downscaling using singular value decomposition (SVD) with simulated precipitation as the predictor, and (iii) local rescaling with a dynamical correction. Both local scaling methods are straightforward to apply to GCMs that are used for climate change experiments and seasonal forecasts, since they only need control runs for model fitting. The SVD method requires for model fitting special reanalysis-type GCM runs nudged toward observations from a historical period (selection of analogs from the GCM chosen to optimally match the historical weather states might achieve similar results). The precipitation-based methods are compared with conventional statistical downscaling using SVD with various large-scale predictors such as geopotential height, temperature, and humidity.

The skill of the different methods for reconstructing historical wintertime precipitation (1958–94) over Oregon and Washington is tested on various spatial scales as small as 50 km and on temporal scales from months to decades. All methods using precipitation as a predictor perform considerably better than the conventional downscaling. The best results using conventional methods are obtained with geopotential height at 1000 hPa or humidity at 850 hPa as predictors. In these cases correlations of monthly observed and reconstructed precipitation on the 50-km scale range from 0.43 to 0.65. The inclusion of several predictor fields does not improve the reconstructions, since they are all highly correlated. Local rescaling of simulated precipitation yields much higher correlations between 0.7 and 0.9, with the exception of the rain shadow of the Cascade Mountains in the Columbia Basin (eastern Washington). When the simulated precipitation is used as a predictor in SVD-based downscaling correlations also reach 0.7 in eastern Washington. Dynamical correction improves the local scaling considerably in the rain shadow and yields correlations almost as high as with the SVD method. Its combination of high skill and ease to use make it particularly attractive for GCM precipitation downscaling.

Abstract

This work compares the Weather Research and Forecasting (WRF) and Hadley Centre Regional Model (HadRM) simulations with the observed daily maximum and minimum temperature (Tmax and Tmin) and precipitation at Historical Climatology Network (HCN) stations over the U.S. Pacific Northwest for 2003–07. The WRF and HadRM runs were driven by the NCEP/Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP)-II Reanalysis (R-2) data. The simulated Tmax in WRF and HadRM as well as in R-2 compares well with the observations. Predominantly cold biases of Tmax are noted in WRF and HadRM in spring and summer, while in winter and fall more stations show warm biases, especially in HadRM. Large cold biases of Tmax are noted in R-2 at all times. The simulated Tmin compares reasonably well with the observations, although not as well as Tmax in both models and in the reanalysis R-2. Warm biases of Tmin prevail in both model simulations, while R-2 shows mainly cold biases. The R-2 data play a role in the model biases of Tmax, although there are also clear indications of resolution dependency. The model biases of Tmin originate mainly from the regional models. The temporal correlation between the simulated and observed daily precipitation is relatively low in both models and in the reanalysis; however, the correlation increases steadily for longer averaging times. The high-resolution models perform better than R-2, although the nested WRF domains do have the largest biases in precipitation during the winter and spring seasons.

Abstract

This paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century.