Abstract

Short-term (1–10 day) forecasts are made with climate models to assess the parameterizations of the physical processes. The time period for the integrations is that of the intensive observing period (IOP) of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). The models used are the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3.1 (CAM3.1); CAM3.1 with a modified deep convection parameterization; and the Geophysical Fluid Dynamics Laboratory (GFDL) Atmospheric Model, version 2 (AM2). The models were initialized using the state variables from the 40-yr ECMWF Re-Analysis (ERA-40).

The CAM deep convective parameterization fails to demonstrate the sensitivity to the imposed forcing to simulate precipitation patterns associated with the Madden–Julian oscillations (MJOs) present during the period. AM2 and modified CAM3.1 exhibit greater correspondence to the observations at the TOGA COARE site, suggesting that convective parameterizations that have some type of limiter (as do AM2 and the modified CAM3.1) simulate the MJO rainfall with more fidelity than those without. None of the models are able to fully capture the correct phasing of westerly wind bursts with respect to precipitation in the eastward-moving MJO disturbance. Better representation of the diabatic heating and effective static stability profiles is associated with a better MJO simulation.

Because the models’ errors in the forecast mode bear a resemblance to the errors in the climate mode in simulating the MJO, the forecasts may allow for a better way to dissect the reasons for model error.

Abstract

Using a coupled general circulation model, the responses of the climate mean state, the annual cycle, and the El Niño–Southern Oscillation (ENSO) phenomenon to orbital changes are studied. The authors analyze a 1650-yr-long simulation with accelerated orbital forcing, representing the period from 142 000 yr b.p. (before present) to 22 900 yr a.p. (after present). The model simulation does not include the time-varying boundary conditions due to ice sheet and greenhouse gas forcing.

Owing to the mean seasonal cycle of cloudiness in the off-equatorial regions, an annual mean precessional signal of temperatures is generated outside the equator. The resulting meridional SST gradient in the eastern equatorial Pacific modulates the annual mean meridional asymmetry and hence the strength of the equatorial annual cycle. In turn, changes of the equatorial annual cycle trigger abrupt changes of ENSO variability via frequency entrainment, resulting in an anticorrelation between annual cycle strength and ENSO amplitude on precessional time scales.

Abstract

In this study, several metrics and diagnostics are proposed and implemented to systematically explore and diagnose climate model biases in short-range hindcasts and quantify how fast hindcast biases approach to climate biases with an emphasis on tropical precipitation and associated moist processes. A series of 6-day hindcasts with NCAR and the U.S. Department of Energy Community Atmosphere Model, version 4 (CAM4) and version 5 (CAM5), were performed and initialized with ECMWF operational analysis every day at 0000 UTC during the Year of Tropical Convection (YOTC). An Atmospheric Model Intercomparison Project (AMIP) type of ensemble climate simulations was also conducted for the same period. The analyses indicate that initial drifts in precipitation and associated moisture processes (“fast processes”) can be identified in the hindcasts, and the biases share great resemblance to those in the climate runs. Comparing to Tropical Rainfall Measuring Mission (TRMM) observations, model hindcasts produce too high a probability of low- to intermediate-intensity precipitation at daily time scales during northern summers, which is consistent with too frequently triggered convection by its deep convection scheme. For intense precipitation events (>25 mm day⁻¹), however, the model produces a much lower probability partially because the model requires a much higher column relative humidity than observations to produce similar precipitation intensity as indicated by the proposed diagnostics. Regional analysis on precipitation bias in the hindcasts is also performed for two selected locations where most contemporary climate models show the same sign of bias. Based on moist static energy diagnostics, the results suggest that the biases in the moisture and temperature fields near the surface and in the lower and middle troposphere are primarily responsible for precipitation biases. These analyses demonstrate the usefulness of these metrics and diagnostics to diagnose climate model biases.

Abstract

The objective of this study is to examine the effectiveness of the variational objective analysis (VOA) for producing realistic diagnoses of atmospheric field program data. Simulations from the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) were sampled in a manner consistent with a typical field program using idealized sounding arrays and, surface and top of the atmosphere flux information. These data were then subject to a conventional form of analysis in which only a mass constraint was applied, hereafter referred to as the reference analysis, as well as to the complete VOA procedure. The diagnosed results from both analyses were then compared to time- and domain-averaged quantities from the model.

The results showed that for diagnosed vertical velocity and vertical advective tendencies, the VOA values typically exhibited considerably smaller errors compared to the values from the reference analyses, with the level of improvement and overall accuracy being dependent on synoptic and sampling conditions. The improvements tend to be greatest during disturbed conditions, with the errors typically being smaller and comparable between the two analyses during undisturbed conditions. The errors for both analyses increase as the spatial domain decreases and for the most part decrease with more frequent temporal sampling. However, the improvement achieved by having more frequent sampling is rather modest for the VOA since it already incorporates time-mean surface and TOA fluxes as constraints and thus indirectly incorporates some aspects of the variability between soundings. Highly relevant is the finding that overall the errors in vertical velocity and vertical advective tendencies from the reference analyses have a magnitude similar to, or greater than, the variability of the field being diagnosed, whereas the errors in these quantities from the VOA are typically less than the variability of the field. The analysis also showed no obvious systematic level-by-level improvement gained by the VOA analysis over the reference analysis in diagnosing the horizontal moisture flux convergence, mass divergence, or horizontal advective tendencies, notwithstanding the VOA's application of column-integrated constraints of mass, moisture, heat, and momentum conservation.

Additional soundings were found to be more beneficial to the reference analyses than the VOA analyses and in some cases allowed the error characteristics of the reference analysis to become similar to those of the VOA analysis. Noteworthy is the finding that the results from the VOA analyses using five soundings were often as good or better than the results from the reference analyses using nine soundings. The impact that hydrometeor measurements would have in providing additional constraints on the VOA was also investigated. The impact was found to be mostly negligible when averaging over relatively large space scales or timescales. On the other hand, for frequent sampling (e.g., 1–3 h) and small spatial scales (i.e., <∼100 km), there is a definite favorable impact on the VOA results for highly disturbed periods. The implications that the above results have on conducting atmospheric field programs and analyzing their results are discussed.

Abstract

High-resolution satellite observations are used to investigate air–sea interaction over the eastern Pacific warm pool. In winter, strong wind jets develop over the Gulfs of Tehuantepec, Papagayo, and Panama, accelerated by the pressure gradients between the Atlantic and Pacific across narrow passes of Central American cordillera. Patches of cold sea surface temperatures (SSTs) and high chlorophyll develop under these wind jets as a result of increased turbulent heat flux from the ocean and enhanced mixing across the base of the ocean mixed layer. Despite a large decrease in SST (exceeding 3°C in seasonal means), the cold patches associated with the Tehuantepec and Papagayo jets do not have an obvious effect on local atmospheric convection in winter since the intertropical convergence zone (ITCZ) is located farther south. The cold patch of the Panama jet to the south, on the other hand, cuts through the winter ITCZ and breaks it into two parts.

A pronounced thermocline dome develops west of the Gulf of Papagayo, with the 20°C isotherm only 30 m deep throughout the year. In summer when the Panama jet disappears and the other two wind jets weaken, SST is 0.5°C lower over this Costa Rica Dome than the background. This cold spot reduces local precipitation by half, punching a hole of 500 km in diameter in the summer ITCZ. The dome underlies a patch of open-ocean high chlorophyll. This thermocline dome is an ocean dynamic response to the positive wind curls south of the Papagayo jet, which is optimally oriented to excite ocean Rossby waves that remotely affect the ocean to the west. The meridionally oriented Tehuantepec and Panama jets, by contrast, only influence the local thermocline depth with few remote effects on SST and the atmosphere. The orographical-triggered air–sea interaction described here is a good benchmark for testing high-resolution climate models now under development.

Abstract

The western Arabian Sea exhibits strong spatial variability in sea surface temperature (SST) during the southwest monsoon, with changes in SST that can exceed 5°C over 200 km. Exploration of satellite-based and in situ data shows a strong connection between mesoscale SST features and changes in the atmospheric boundary layer. The fundamental relationship is that of weak (strong) wind velocities overlying cold (warm) SST features. There are also coherent changes in other near-surface meteorological parameters, such as the air–sea temperature difference and relative humidity—indicating changes in the stability of the planetary boundary layer over the mesoscale SST features. These relationships are similar to those recently reported over the equatorial Pacific tropical instability wave region.

This observed covariability of atmospheric boundary layer structure and SST results in variations of the surface heat and moisture fluxes; latent heat flux is modified by changes in relative humidity (principally through the temperature dependence of saturation specific humidity), wind speed, and boundary layer stability over the cold filaments. The nonlinear dependence of latent heat flux on the three parameters leads to a net enhancement of latent heat flux from the mesoscale features, as compared to that computed using spatially averaged parameters.

Additionally, the spatial structure of the heat-flux variability will tend to dampen the mesoscale SST features. The mesoscale wind variability results in strong wind stress curl patterns on the same spatial scales as the oceanic features. The resulting Ekman pumping variations may play an important role in the evolution of the ocean eddy fields in this region. Further examination of the processes controlling the observed covariability, and the oceanic and atmospheric response to the coupling should therefore be undertaken.

Abstract

Satellite measurements from January 1985 to December 1989 show that warmer tropical oceans as a whole are associated with less longwave greenhouse effect of clouds and less cloud reflection of solar radiation to the space. The regression slopes of longwave and shortwave cloud radiative forcings against sea surface temperatures averaged from 30°N to 30°S are about −3 and 2 W m⁻² K⁻¹, respectively. Relationships of cloud forcings and sea surface temperatures are analyzed for regions with different sizes. As has been reported in previous studies, the magnitude of area-averaged cloud radiative forcing for both longwave and shortwave radiations increases with sea surface temperatures in the equatorial eastern Pacific and is insensitive to sea surface temperatures over the tropical Pacific basin. Yet, when the region extends beyond the tropical Pacific, the magnitude decreases with sea surface temperatures. This phenomenon is shown to relate to changes in clouds over the tropical Indian Ocean and Atlantic, where sea surface temperatures increased but clouds decreased during the 1987 El Niño event. Relevance of the results to other climate changes is discussed.

Abstract

The twentieth-century simulations using by 17 coupled ocean–atmosphere general circulation models (CGCMs) submitted to the Intergovernmental Panel on Climate Change’s Fourth Assessment Report (IPCC AR4) are evaluated for their skill in reproducing the observed modes of Indian Ocean (IO) climate variability. Most models successfully capture the IO’s delayed, basinwide warming response a few months after El Niño–Southern Oscillation (ENSO) peaks in the Pacific. ENSO’s oceanic teleconnection into the IO, by coastal waves through the Indonesian archipelago, is poorly simulated in these models, with significant shifts in the turning latitude of radiating Rossby waves. In observations, ENSO forces, by the atmospheric bridge mechanism, strong ocean Rossby waves that induce anomalies of SST, atmospheric convection, and tropical cyclones in a thermocline dome over the southwestern tropical IO. While the southwestern IO thermocline dome is simulated in nearly all of the models, this ocean Rossby wave response to ENSO is present only in a few of the models examined, suggesting difficulties in simulating ENSO’s teleconnection in surface wind.

A majority of the models display an equatorial zonal mode of the Bjerknes feedback with spatial structures and seasonality similar to the Indian Ocean dipole (IOD) in observations. This success appears to be due to their skills in simulating the mean state of the equatorial IO. Corroborating the role of the Bjerknes feedback in the IOD, the thermocline depth, SST, precipitation, and zonal wind are mutually positively correlated in these models, as in observations. The IOD–ENSO correlation during boreal fall ranges from −0.43 to 0.74 in the different models, suggesting that ENSO is one, but not the only, trigger for the IOD.

Abstract

Prior to the 1976–77 climate shift (1950–76), sea surface temperature (SST) anomalies in the tropical Indian Ocean consisted of a basinwide warming during boreal fall of the developing phase of most El Niños, whereas after the shift (1977–99) they had an east–west asymmetry—a consequence of El Niño being associated with the Indian Ocean Dipole/Zonal mode. In this study, the possible impact of these contrasting SST patterns on the ongoing El Niño is investigated, using atmospheric reanalysis products and solutions to both an atmospheric general circulation model (AGCM) and a simple atmospheric model (LBM), with the latter used to identify basic processes. Specifically, analyses of reanalysis products during the El Niño onset indicate that after the climate shift a low-level anticyclone over the South China Sea was shifted into the Bay of Bengal and that equatorial westerly anomalies in the Pacific Ocean were considerably stronger. The present study focuses on determining influence of Indian Ocean SST on these changes.

A suite of AGCM experiments, each consisting of a 10-member ensemble, is carried out to assess the relative importance of remote (Pacific) versus local (Indian Ocean) SST anomalies in determining precipitation anomalies over the equatorial Indian Ocean. Solutions indicate that both local and remote SST anomalies are necessary for realistic simulations, with convection in the tropical west Pacific and the subsequent development of the South China Sea anticyclone being particularly sensitive to Indian Ocean SST anomalies. Prior to the climate shift, the basinwide Indian Ocean SST anomalies generate an atmospheric Kelvin wave associated with easterly flow over the equatorial west-central Pacific, thereby weakening the westerly anomalies associated with the developing El Niño. In contrast, after the shift, the east–west contrast in Indian Ocean SST anomalies does not generate a significant Kelvin wave response, and there is little effect on the El Niño–induced westerlies. The Linear Baroclinic Model (LBM) solutions confirm the AGCM’s results.

Abstract

As new observation systems are developed and deployed, new and presumably more precise information is becoming available for weather forecasting and climate monitoring. To take advantage of these new observations, it is desirable to have schemes to accurately retrieve the information before statistical analyses are performed so that statistical computation can be more effectively used where it is needed most. The authors propose a sequential variational approach that possesses advantages of both a standard statistical analysis [such as with a three-dimensional variational data assimilation (3DVAR) or Kalman filter] and a traditional objective analysis (such as the Barnes analysis). The sequential variational analysis is multiscale, inhomogeneous, anisotropic, and temporally consistent, as shown by an idealized test case and observational datasets in this study. The real data cases include applications in two-dimensional and three-dimensional space and time for storm outflow boundary detection (surface application) and hurricane data assimilation (three-dimensional space application). Implemented using a multigrid technique, this sequential variational approach is a very efficient data assimilation method.