The 132-year historical rainfall record reveals that severe droughts in India have always been accompanied by El Niño events. Yet El Niño events have not always produced severe droughts. We show that El Niño events with the warmest sea surface temperature (SST) anomalies in the central equatorial Pacific are more effective in focusing drought-producing subsidence over India than events with the warmest SSTs in the eastern equatorial Pacific. The physical basis for such different impacts is established using atmospheric general circulation model experiments forced with idealized tropical Pacific warmings. These findings have important implications for Indian monsoon forecasting.
A mesoscale model has been used to simulate an observed trough system which crossed the Rocky Mountains between 24 and 27 March 1983. Numerical simulations have been conducted with and without topography to isolate the effects that the mountains have on the cyclone and the subsequent lee cyclogenesis that occurs in eastern Colorado. The applicability of two theories to describe processes occurring in the cyclone as it crosses the mountains have been investigated: 1) superposition or masking of the cyclone by a topographically induced anticyclone, and 2) upper-level forcing coupled with low-level blocking. In this case study, the low-level absolute vorticity of the cyclone over the region of the Rocky Mountains is less in the simulations with topography than in the simulations without. However, later in the simulations as the cyclone moves away from the mountains, vorticity differences between the simulations decrease markedly. In association with decreased vorticity, higher geopotential heights are found at all tropospheric levels over the mountains in the runs with topography. These height differences are similar in magnitude and character to the anticyclone that develops when the zonally averaged mean flow is allowed to impinge on the topography until a quasi-equilibrium is reached. An upper-tropospheric jet streak and associated indirect circulation are present in this March 1983 case and are simulated by the model. However, comparison of the mountain and no-mountain simulations indicates the presence of topography does not result in significant blocking of the low-level flow or alter the magnitude of the indirect circulation in the lee region. This lack of sensitivity may be a function of the relatively smooth topography employed in the model.
As part of an ongoing study of the regional climate and hydrology of the southwestern United States, in this paper we investigate the systematic biases of two versions of the PSU/NCAR mesoscale model (MM4). These are a standard version and one that includes a more detailed treatment of radiative transfer, surface physics, and soil hydrology. We simulated the period 1–30 January 1979, in which nine Pacific storms moved across the western United States. Results from both model versions are compared to the large scale analysis used to provide initial and lateral boundary conditions. Both models show a lower tropospheric cold bias of 1–3 K near the surface over land and an upper tropospheric warm bias of less than 1 K, which suggest high model stability and reduced vertical mixing. The model atmospheres are wetter than that of the analysis, particularly in the lower troposphere and over the ocean. The wind magnitude bias is positive near the surface (∼1.5–3 m s−1), negative in the upper troposphere (∼−1.5 m s−1) and positive above the jet-level (∼3 m s−1). The wind direction bias is small throughout the model atmospheres except at the top model layer near 10 mb. These results indicate that the model evaporation and nighttime land surface sensible heat fluxes are larger compared to the analysis, while the daytime sensible heat fluxes and surface wind drag are smaller. The biases are generally smaller in the midtroposphere than in the lower troposphere and in the stratosphere. In general, both models capture most regional features of the orographic forcing of precipitation by the western United States topography quite well. Compared to station data, precipitation amounts tend to be overpredicted. Daily precipitation threat scores for various precipitation thresholds vary between 0.315 and 0.385. The threat scores for the 30-day precipitation, more indicative of the model's ability to simulate climatological precipitation averages, are higher, ⩾0.8 for light precipitation to ∼0.5 for moderate to heavy precipitation. Snow depths predicted by the augmented model also show realistic regional features. In general, the inclusion of the new physics package did not strongly affect precipitation prediction or the temperature, moisture, and wind midtropospheric biases. In the boundary layer over land, however, the augmented model was significantly colder and drier than the standard model due to larger nighttime surface sensible heat fluxes and lower evaporation rates. The regional hydrologic budgets simulated by the soil hydrology package of the augmented MM4 appear realistic in many respects, although verification is difficult at the present model resolution.
As part of the development effort of a regional climate model (RCM) for the southern Great Basin, this paper presents a validation analysis of the climatology generated by a high-resolution RCM driven by observations. The RCM is a version of the National Center for Atmospheric Research/Pennsylvania State University mesoscale model, version 4 (MM4), modified for application to regional climate simulation. Two multiyear simulations, for the periods 1 January 1982 to 31 December 1983 and 1 January 1988 to 25 April 1989, were performed over the western United States with the RCM driven by European Centre for Medium-Range Weather Forecasts analyses of observations. The model resolution is 60 km. This validation analysis is the first phase of a project to produce simulations of future climate scenarios over a region surrounding Yucca Mountain, Nevada, the only location currently being considered as a potential high-level nuclear-waste repository site. Model-produced surface air temperatures and precipitation were compared with observations from five southern Nevada stations located in the vicinity of Yucca Mountain. The seasonal cycles of temperature and precipitation were simulated well. Monthly and seasonal temperature biases were generally negative and largely explained by differences in elevation between the observing stations and the model topography. The model-simulated precipitation captured the extreme dryness of the Great Basin. Average yearly precipitation was generally within 30% of observed and the range of monthly precipitation amounts was the same as in the observations. Precipitation biases were mostly negative in the summer and positive in the winter. The number of simulated daily precipitation events for various precipitation intervals was within factors of 1.5–3.5 of observed. Overall, the model tended to overestimate the number of light precipitation events and underestimate the number of heavy precipitation events. At Yucca Mountain, simulated precipitation, soil moisture content, and water infiltration below the root zone (top 1 m) were maximized in the winter. Evaporation peaked in the spring after temperatures began to increase. The conclusion drawn from this validation analysis is that this high-resolution RCM simulates the regional surface climatology of the southern Great Basin reasonably well when driven by meteorological fields derived from observations.
The effect of a doubling of atmospheric CO2 on the characteristics of the 500 mb height field and persistent height anomalies associated with blocking phenomena are investigated in two experiments with the NCAR Community Climate Model (CCM) coupled to a simple ocean mixed layer. This version of the CCM with a seasonal cycle, computed hydrology and the simple mixed layer ocean produces a somewhat improved simulation compared with earlier model versions in spite of a lack of ocean heat transport and overextensive sea ice. In a control experiment with present amounts of CO2, 500 mb height statistics compared best with observations during winter while summer is not simulated as well. In a second experiment, where CO2 is doubled, the troposphere experiences warming most everywhere and 500 mb heights increase, especially near areas where sea ice has retreated and surface air temperature warming is greatest. In most regions of significant blocking activity, standard deviations of 500 mb height and blocking activity are decreased in all seasons. In the Northern Hemisphere, there are also increases in 500 mb standard deviations and blocking activity in the North Pacific during winter, and an increase in standard deviations at high latitudes over Asia and Alaska during summer. There also is a coincident increase of blocking over Asia at those latitudes, but a decrease of blocking over Alaska in summer, partially due to increased variability on shorter time scales there. Thus, in this hemisphere the incidence of blocking does not seem to change significantly with increased CO2, but the centers of action move geographically. On the other hand, in the Southern Hemisphere, blocking activity is generally reduced.
Abstract Analog postprocessing methods have previously been applied using precipitation reforecasts and analyses to improve probabilistic forecast skill and reliability. A modification to a previously documented analog procedure is described here that produces highly skillful, statistically reliable precipitation forecast guidance at ° grid spacing. These experimental probabilistic forecast products are available via the web in near–real time. The main changes to the previously documented analog algorithm were as follows: (i) use of a shorter duration (2002–13), but smaller grid spacing, higher-quality time series of precipitation analyses for training and forecast verification (i.e., the Climatology-Calibrated Precipitation Analysis); (ii) increased training sample size using data from 19 supplemental locations, chosen for their similar precipitation analysis climatologies and terrain characteristics; (iii) selection of analog dates for a particular grid point based on the similarity of forecast characteristics at that grid point rather than similarity in a neighborhood around that grid point; (iv) using an analog rather than a rank-analog approach; (v) varying the number of analogs used to estimate probabilities from a smaller number (50) for shorter-lead forecasts to a larger number (200) for longer-lead events; and (vi) spatial Savitzky–Golay smoothing of the probability fields. Special procedures were also applied near coasts and country boundaries to deal with data unavailability outside of the United States while smoothing. The resulting forecasts are much more skillful and reliable than raw ensemble guidance across a range of event thresholds. The forecasts are not nearly as sharp, however. The use of the supplemental locations is shown to especially improve the skill of short-term forecasts during the winter.
Dynamical methods are used to investigate atmospheric teleconnections associated with extreme seasonal precipitation anomalies over the central United States during April–June. The importance of sea surface temperature (SST) anomalies in forcing atmospheric teleconnections is specifically addressed through analyses of atmospheric general circulation model (GCM) simulations forced with the monthly varying SSTs of the years 1950–98. The results from three different models, each run in ensemble mode, are compared with observations of extreme April–June precipitation events in the central United States during the last half of the twentieth century. Analysis of GCM simulations of April–June 1988 indicates that the atmospheric circulation anomalies associated with the 1988 drought were not forced by SST anomalies and that the coexistence of central U.S. drought and La Niña during that spring was coincidental. Likewise, composite analysis reveals no SST forcing for the teleconnections associated with extreme dry spring seasons over the central United States during the last half of the twentieth century in either observations or GCMs. Nonetheless, this characteristic teleconnection pattern of the composite analysis resembles the circulation anomalies of 1988. The results imply that such drought events and the teleconnections related with them have little SST-based predictability. A somewhat different conclusion is drawn regarding the role of tropical SSTs in the occurrence of extreme wet spring seasons over the central United States. Simulations of the 1993 flood period exhibit skill in reproducing the seasonal circulation anomalies over the Pacific–North American region, and the ensemble mean precipitation anomalies in one GCM nearly replicate the observed strength and distribution of positive rainfall anomalies over the United States. Further composite analysis of extreme wet spring seasons over the last half of the twentieth century confirms the impression gathered from the 1993 case study, with observations and all three GCMs possessing positive tropical east Pacific SST anomalies in conjunction with extreme wet spring seasons over the central United States. Some SST-based potential predictability of extreme wet springs over the central United States consequently exists.
Abstract In this study the authors diagnose the sources for the contiguous U.S. seasonal forecast skill that are related to sea surface temperature (SST) variations using a combination of dynamical and empirical methods. The dynamical methods include ensemble simulations with four atmospheric general circulation models (AGCMs) forced by observed monthly global SSTs from 1950 to 1999, and ensemble AGCM experiments forced by idealized SST anomalies. The empirical methods involve a suite of reductions of the AGCM simulations. These include uni- and multivariate regression models that encapsulate the simultaneous and one-season lag linear connections between seasonal mean tropical SST anomalies and U.S. precipitation and surface air temperature. Nearly all of the AGCM skill in U.S. precipitation and surface air temperature, arising from global SST influences, can be explained by a single degree of freedom in the tropical SST field—that associated with the linear atmospheric signal of El Niño–Southern Oscillation (ENSO). The results support previous findings regarding the preeminence of ENSO as a U.S. skill source. The diagnostic methods used here exposed another skill source that appeared to be of non-ENSO origins. In late autumn, when the AGCM simulation skill of U.S. temperatures peaked in absolute value and in spatial coverage, the majority of that originated from SST variability in the subtropical west Pacific Ocean and the South China Sea. Hindcast experiments were performed for 1950–99 that revealed most of the simulation skill of the U.S. seasonal climate to be recoverable at one-season lag. The skill attributable to the AGCMs was shown to achieve parity with that attributable to empirical models derived purely from observational data. The diagnostics promote the interpretation that only limited advances in U.S. seasonal prediction skill should be expected from methods seeking to capitalize on sea surface predictors alone, and that advances that may occur in future decades could be readily masked by inherent multidecadal fluctuations in skill of coupled ocean–atmosphere systems.
Abstract For the newly implemented Global Ensemble Forecast System, version 12 (GEFSv12), a 31-yr (1989–2019) ensemble reforecast dataset has been generated at the National Centers for Environmental Prediction (NCEP). The reforecast system is based on NCEP’s Global Forecast System, version 15.1, and GEFSv12, which uses the Finite Volume 3 dynamical core. The resolution of the forecast system is ∼25 km with 64 vertical hybrid levels. The Climate Forecast System (CFS) reanalysis and GEFSv12 reanalysis serve as initial conditions for the Phase 1 (1989–99) and Phase 2 (2000–19) reforecasts, respectively. The perturbations were produced using breeding vectors and ensemble transforms with a rescaling technique for Phase 1 and ensemble Kalman filter 6-h forecasts for Phase 2. The reforecasts were initialized at 0000 (0300) UTC once per day out to 16 days with 5 ensemble members for Phase 1 (Phase 2), except on Wednesdays when the integrations were extended to 35 days with 11 members. The reforecast dataset was produced on NOAA’s Weather and Climate Operational Supercomputing System at NCEP. This study summarizes the configuration and dataset of the GEFSv12 reforecast and presents some preliminary evaluations of 500-hPa geopotential height, tropical storm track, precipitation, 2-m temperature, and MJO forecasts. The results were also compared with GEFSv10 or GEFS Subseasonal Experiment reforecasts. In addition to supporting calibration and validation for the National Water Center, NCEP Climate Prediction Center, and other National Weather Service stakeholders, this high-resolution subseasonal dataset also serves as a useful tool for the broader research community in different applications.
