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Michael A. Alexander and James D. Scott

Abstract

Daily fields obtained from a 17-yr atmospheric GCM simulation are used to study the surface sensible and latent heat flux variability and its relationship to the sea level pressure (SLP) field. The fluxes are analyzed over the North Pacific and Atlantic Oceans during winter. The leading mode of interannual SLP variability consists of a single center associated with the Aleutian low in the Pacific, and a dipole pattern associated with the Icelandic low and Azores high in the Atlantic. The surface flux anomalies are organized by the low-level atmospheric circulation associated with these modes in agreement with previous observational studies.

The surface flux variability on all of the timescales examined, including intraseasonal, interannual, 3–10 day, and 10–30 day, is maximized along the north and west edges of both oceans and between Japan and the date line at ∼35°N in the Pacific. The intraseasonal variability is approximately 3–5 times larger than the interannual variability, with more than half of the total surface flux variability occuring on timescales of less than 1 month. Surface flux variability in the 3–10-day band is clearly associated with midlatitude synoptic storms. Composites indicate upward (downward) flux anomalies that exceed |30 W m−2| occur to the west (east) of storms, which move eastward across the oceans at 10°–15° per day. The SLP and surface flux anomalies are also strong and coherent in the 10–30-day band but are located farther north, are broader in scale, and propagate ∼3–4 times more slowly eastward than the synoptic disturbances.

The sensible and latent heat flux are proportional to the wind speed multiplied by the air–sea temperature and humidity difference, respectively. The anomalous wind speed has the greatest influence on surface flux anomalies in the subtropics and western Pacific, while the air temperature and moisture anomalies have the greatest impact in the northeast Pacific and north of 40°N in the Atlantic. The covariance between the wind speed and the air temperature or humidity anomalies, while generally small, is nonnegligible on synoptic timescales.

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James D. Scott and Steven A. Rutledge

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A study of the 28 May 1985 “asymmetric” mesoscale convective system (MCS) observed during PRE-STORM is presented. Dual-Doppler analysis revealed a well-defined cyclonic mesovortex in the northern portion of the stratiform region, in accord with previous studies on this type of circulation. At maximum extent, the closed cyclonic circulation had a diameter of approximately 80 km and a depth of 7 km. A smaller anticyclonic circulation was present to the south of the cyclonic vortex. Counterrotating vortices in asymmetric MCSs have been identified in recent modeling studies; however, prior to this study, observational confirmation of the anticyclonic vortex has been elusive.

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Caren Marzban, Scott Sandgathe, and James D. Doyle

Abstract

Knowledge of the relationship between model parameters and forecast quantities is useful because it can aid in setting the values of the former for the purpose of having a desired effect on the latter. Here it is proposed that a well-established multivariate statistical method known as canonical correlation analysis can be formulated to gauge the strength of that relationship. The method is applied to several model parameters in the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) for the purpose of “controlling” three forecast quantities: 1) convective precipitation, 2) stable precipitation, and 3) snow. It is shown that the model parameters employed here can be set to affect the sum, and the difference between convective and stable precipitation, while keeping snow mostly constant; a different combination of model parameters is shown to mostly affect the difference between stable precipitation and snow, with minimal effect on convective precipitation. In short, the proposed method cannot only capture the complex relationship between model parameters and forecast quantities, it can also be utilized to optimally control certain combinations of the latter.

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Michael A. Alexander and James D. Scott

Abstract

The influence of oceanic Ekman heat transport (Q ek) on air–sea variability associated with ENSO teleconnections is examined via a pair of atmospheric general circulation model (AGCM) experiments. In the mixed layer model (MLM) experiment, observed sea surface temperatures (SSTs) for the years 1950–99 are specified over the tropical Pacific, while a grid of mixed layer models is coupled to the AGCM elsewhere over the global oceans. The same experimental design was used in the Ekman transport/mixed layer model (EKM) experiment with the addition of Q ek in the mixed layer ocean temperature equation. The ENSO signal was evaluated using differences between composites of El Niño and La Niña events averaged over the 16 ensemble members in each experiment.

In both experiments the Aleutian low deepened and the resulting surface heat fluxes cooled the central North Pacific and warmed the northeast Pacific during boreal winter in El Niño relative to La Niña events. Including Qek amplified the ENSO-related SSTs by ∼⅓ in the central and northeast North Pacific, producing anomalies comparable to those in nature. Differences between the ENSO-induced atmospheric circulation anomalies in the EKM and MLM experiments were not significant over the North Pacific. The sea level pressure (SLP) and SST response to ENSO over the Atlantic strongly projects on the North Atlantic Oscillation (NAO) and the SST tripole pattern in observations and both model experiments. The La Niña anomalies, which are stronger than during El Niño, include high pressure and positive SSTs in the central North Atlantic. Including Ekman transport enhanced the Atlantic SST anomalies, which in contrast to the Pacific, appeared to strengthen the overlying atmospheric circulation.

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James D. Scott and Michael A. Alexander

Abstract

Net surface shortwave fluxes (Q sw) computed from National Aeronautics and Space Administration/Langley satellite data are compared with Q sw from reanalyses of the European Centre for Medium-Range Weather Forecasts (ERA) and the National Centers for Environmental Prediction (NCEP). The mean and variability of Q sw is examined for the period 1983–91, with a focus on the tropical and summer hemisphere oceans during June, July, August (JJA) and December, January, February (DJF). Both reanalyses exhibit a positive bias, indicating too much sunlight is absorbed at the surface, in regions where low-level stratiform clouds are most common, but a negative bias in regions where cumuliform clouds are the dominant cloud type. The ERA has a greater intermonthly variability during JJA than the satellite data over most of the Pacific, especially north of 40°N and in the central and eastern equatorial Pacific. The NCEP variability in JJA is also larger than the satellite estimates over the North Pacific and the eastern equatorial Pacific, but is smaller over most of the western tropical and subtropical Pacific. During DJF, the ERA has more realistic variability in shortwave fluxes over the tropical oceans than the NCEP reanalysis, which underestimates the variability in the tropical Pacific and the Indian Ocean by a factor of 2. Ocean models using atmospheric forcing from reanalyses will be impacted not only by regional and seasonal Q sw biases but also by differences in Q sw variability. It is estimated that the largest impacts on SST due to differences in variability are in the North Pacific, eastern tropical Pacific, and western Atlantic during JJA and in the Indian Ocean and the tropical Pacific and Atlantic during DJF.

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Kelly Mahoney, Michael Alexander, James D. Scott, and Joseph Barsugli

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A high-resolution case-based approach for dynamically downscaling climate model data is presented. Extreme precipitation events are selected from regional climate model (RCM) simulations of past and future time periods. Each event is further downscaled using the Weather Research and Forecasting (WRF) Model to storm scale (1.3-km grid spacing). The high-resolution downscaled simulations are used to investigate changes in extreme precipitation projections from a past to a future climate period, as well as how projected precipitation intensity and distribution differ between the RCM scale (50-km grid spacing) and the local scale (1.3-km grid spacing). Three independent RCM projections are utilized as initial and boundary conditions to the downscaled simulations, and the results reveal considerable spread in projected changes not only among the RCMs but also in the downscaled high-resolution simulations. However, even when the RCM projections show an overall (i.e., spatially averaged) decrease in the intensity of extreme events, localized maxima in the high-resolution simulations of extreme events can remain as strong or even increase. An ingredients-based analysis of prestorm instability, moisture, and forcing for ascent illustrates that while instability and moisture tend to increase in the future simulations at both regional and local scales, local forcing, synoptic dynamics, and terrain-relative winds are quite variable. Nuanced differences in larger-scale and mesoscale dynamics are a key determinant in each event's resultant precipitation. Very high-resolution dynamical downscaling enables a more detailed representation of extreme precipitation events and their relationship to their surrounding environments with fewer parameterization-based uncertainties and provides a framework for diagnosing climate model errors.

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Caren Marzban, Scott Sandgathe, James D. Doyle, and Nicholas C. Lederer

Abstract

Numerical weather prediction models have a number of parameters whose values are either estimated from empirical data or theoretical calculations. These values are usually then optimized according to some criterion (e.g., minimizing a cost function) in order to obtain superior prediction. To that end, it is useful to know which parameters have an effect on a given forecast quantity, and which do not. Here the authors demonstrate a variance-based sensitivity analysis involving 11 parameters in the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). Several forecast quantities are examined: 24-h accumulated 1) convective precipitation, 2) stable precipitation, 3) total precipitation, and 4) snow. The analysis is based on 36 days of 24-h forecasts between 1 January and 4 July 2009. Regarding convective precipitation, not surprisingly, the most influential parameter is found to be the fraction of available precipitation in the Kain–Fritsch cumulus parameterization fed back to the grid scale. Stable and total precipitation are most affected by a linear factor that multiplies the surface fluxes; and the parameter that most affects accumulated snow is the microphysics slope intercept parameter for snow. Furthermore, all of the interactions between the parameters are found to be either exceedingly small or have too much variability (across days and/or parameter values) to be of primary concern.

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Ileana Bladé, Matthew Newman, Michael A. Alexander, and James D. Scott

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The extratropical response to El Niño in late fall departs considerably from the canonical El Niño signal. Observational analysis suggests that this response is modulated by anomalous forcing in the tropical west Pacific (TWP), so that a strong fall El Niño teleconnection is more likely when warm SST conditions and/or enhanced convection prevail in the TWP. While these TWP SST anomalies may arise from noise and/or long-term variability, they may also be generated by differences between El Niño events, through variations in the tropical “atmospheric bridge.” This bridge typically drives subsidence west of the date line and enhanced trade winds over the far TWP, which cool the ocean. In late fall, however, some relatively weaker and/or more eastward-shifted El Niño events produce a correspondingly weakened and displaced tropical bridge, which results in no surface cooling and enhanced convection in the TWP. Because the North Pacific circulation is very sensitive to forcing from the TWP at this time of year, the final outcome is a strong extratropical El Niño teleconnection.

This hypothesis is partly supported by regionally coupled ensemble GCM simulations for the 1950–99 period, in which prescribed observed El Niño SST anomalies in the eastern/central equatorial Pacific and an oceanic mixed layer model elsewhere coexist, so that the TWP is allowed to interact with the El Niño atmospheric bridge. To separate the deterministic signal driven by TWP coupling from that associated with inter–El Niño differences and from the “noise” due to intrinsic TWP convection variability (not induced by local SST anomalies), a second large-ensemble (100) simulation of the 1997/98 El Niño event, with coupling limited to the TWP and tropical Indian Ocean, is carried out. Together, the model findings suggest that the extratropical El Niño teleconnection during late fall is very sensitive to convective forcing in the TWP and that coupling-induced warming in the TWP may enhance this El Niño teleconnection by promoting convection in this critical TWP region. A more general implication is that diagnostic studies using December–February (DJF) seasonal averages may obscure some important aspects of climate anomalies associated with forcing in the tropical Pacific.

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Michael A. Alexander, James D. Scott, Kelly Mahoney, and Joseph Barsugli

Abstract

Precipitation changes between 32-yr periods in the late twentieth and mid-twenty-first centuries are investigated using regional climate model simulations provided by the North American Regional Climate Change Assessment Program (NARCCAP). The simulations generally indicate drier summers in the future over most of Colorado and the border regions of the adjoining states. The decrease in precipitation occurs despite an increase in the surface specific humidity. The domain-averaged decrease in daily summer precipitation occurs in all of the models from the 50th through the 95th percentile, but without a clear agreement on the sign of change for the most extreme (top 1% of) events.

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Michael A. Alexander, Hyodae Seo, Shang Ping Xie, and James D. Scott

Abstract

The recently released NCEP Climate Forecast System Reanalysis (CFSR) is used to examine the response to ENSO in the northeast tropical Pacific Ocean (NETP) during 1979–2009. The normally cool Pacific sea surface temperatures (SSTs) associated with wind jets through the gaps in the Central American mountains at Tehuantepec, Papagayo, and Panama are substantially warmer (colder) than the surrounding ocean during El Niño (La Niña) events. Ocean dynamics generate the ENSO-related SST anomalies in the gap wind regions as the surface fluxes damp the SSTs anomalies, while the Ekman heat transport is generally in quadrature with the anomalies. The ENSO-driven warming is associated with large-scale deepening of the thermocline; with the cold thermocline water at greater depths during El Niño in the NETP, it is less likely to be vertically mixed to the surface, particularly in the gap wind regions where the thermocline is normally very close to the surface. The thermocline deepening is enhanced to the south of the Costa Rica Dome in the Papagayo region, which contributes to the local ENSO-driven SST anomalies. The NETP thermocline changes are due to coastal Kelvin waves that initiate westward-propagating Rossby waves, and possibly ocean eddies, rather than by local Ekman pumping. These findings were confirmed with regional ocean model experiments: only integrations that included interannually varying ocean boundary conditions were able to simulate the thermocline deepening and localized warming in the NETP during El Niño events; the simulation with variable surface fluxes, but boundary conditions that repeated the seasonal cycle, did not.

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