Search Results

You are looking at 11 - 20 of 21 items for

  • Author or Editor: Chester F. Ropelewski x
  • Refine by Access: All Content x
Clear All Modify Search
Michael S. Halpert and Chester F. Ropelewski

Abstract

No abstract available.

Full access
Donald P. Wylie and Chester F. Ropelewski

A tethered sonde, the Boundary Layer Instrument System (BLIS), was designed for use from shipboard platforms in the GARP Atlantic Tropical Experiment (GATE). This system was able to monitor the thermal and kinematic properties of the boundary layer from approximately 100 m to the level of cloud base (800–1000 m). Five levels were simultaneously sampled for periods up to 24 h in length. More detailed vertical structure measurements were obtained by raising and lowering the tethered balloon. The mechanical details of the system and its accuracy in monitoring boundary layer changes and vertical motions are described.

Full access
Chester F. Ropelewski, Peter J. Lamb, and Diane H. Portis

Abstract

ABSTRACT NOT AVAILABLE

Full access
Robert W. Reeves, Chester F. Ropelewski, and Michael D. Hudlow

Abstract

Upper air and surface data from the GARP Atlantic Tropical Experiment (GATE) are used to examine the interrelationships between convective-scale precipitation and the larger scale wind field. The upper air winds from the inner (B) and outer (A/B) hexagonal observational arrays are fit with second-order polynomials to provide smooth estimates of the vorticity, divergence and vertical motion in the observational array. In these analyses we examined archived validated data from all three phases of the experiment and we formed averages based on the radar-estimated precipitation rates.

Mean profiles for 19-day periods during each of the three observational phases establish the basic similarity of the kinematics during each phase. Strong boundary-layer convergence balanced, for the most part, by upper tropospheric divergence, is common to all three phases.

Radar-estimated precipitation rates are used to define suppressed (precipitation rates <0.1 mm h−1) and highly disturbed (precipitation rates >0.5 mm h−1) states over the observational array. Mean profiles for the disturbed states in each phase show weaker easterly winds and much larger upward vertical velocities than do the mean profiles for the suppressed states. The mean vorticity profiles for each state do not show such clear-cut differences.

Time series of 12 h averages indicate that the precipitation events in Phase III corresponded very closely to the cyclonic maxima of the 700 mb relative vorticity, reflecting the influence of the easterly waves described by Reed et al. (1977). During Phases I and II, when easterly waves were poorly organized, the precipitation events did not correspond closely to the cyclonic vorticity maxima. On the other hand, precipitation events showed good correspondence with the large-scale (A/B) 700 mb upward vertical velocity maxima and surface meridional convergence ∂v/∂y during all three phases. This shows that the precipitation is clearly related to events on a larger scale.

The effects of convective activity on the large-scale flow are examined through the vorticity budget. The vorticity budget residual profiles were similar from phase to phase with cyclonic production maxima in the mid and upper troposphere. The upper tropospheric residual maximum is as strong during the suppressed state as it is during the highly disturbed side. At the surface, individual values of the residual are almost always opposite in sign to the vorticity. The mean vorticity budget for the A/B array shows the tipping term to have magnitudes comparable to other terms in the vorticity budget.

Full access
Alan N. Basist, Chester F. Ropelewski, and Norman C. Grody

Abstract

The Microwave Sounding Units (MSU) aboard the NOAA series of polar-orbiting satellites (TIROS-N to NOAA-12) have provided stable and precise measurements of vertically integrated atmospheric temperature since December 1978. Comparisons are made between the MSU channel measurements and temperatures derived from the global data assimilation system (GDAS) at the National Meteorological Center (NMC) for the period 1979–1990. The largest correlations occur at high to midlatitudes, where the troposphere exhibits large monthly anomaly fields, and where radiosondes provide ample coverage for the GDAS. Intermonthly differences from each dataset had global correlations above 0.97. However, poor correlations with MSU were noted over areas of high terrain and tropical landmasses. These poorer correlations can be attributed to temporal changes and data limitations in the GDAS analysis. Comparisons between the GDAS and MSU temperature anomaly fields indicate that frequent model changes mask the climate signal in the GDAS analysis. Nonetheless, the study suggests that both GDAS- and MSU-derived temperature anomalies detect similar spatial and temporal variability over regions where the GDAS is data rich and the signal is large, that is, the El Niño-Southern Oscillations. This study suggests that the NMC reanalysis, using a fixed assimilation model, will produce a stable dataset of tropospheric temperatures. Therefore, the 35 years of reanalyzed NMC model data can he used in conjunction with satellite data to improve the suite of tools used in climate monitoring.

Full access
Alice M. Grimm, A. K. Sahai, and Chester F. Ropelewski

Abstract

Global climate models forced by sea surface temperature are standard tools in seasonal climate prediction and in projection of future climate change caused by anthropogenic emissions of greenhouse gases. Assessing the ability of these models to reproduce observed atmospheric circulation given the lower boundary conditions, and thus its ability to predict climate, has been a recurrent concern. Several assessments have shown that the performance of models is seasonally dependent, but there has always been the assumption that, for a given season, the model skill is constant throughout the period being analyzed. Here, it is demonstrated that there are periods when these models perform well and periods when they do not capture observed climate variability. The variations of the model performance have temporal scales and spatial patterns consistent with decadal/interdecadal climate variability. These results suggest that there are unmodeled climate processes that affect seasonal climate prediction as well as scenarios of climate change, particularly regional climate change projections. The reliability of these scenarios may depend on the time slice of the model output being analyzed. Therefore, more comprehensive model assessment should include a verification of the long-term stability of their performance.

Full access
Thomas M. Smith, Richard W. Reynolds, and Chester F. Ropelewski

Abstract

Optimal averaging (OA) is used to compute the area-average seasonal sea surface temperature (SST) for a variety of areas from 1860 to 1989. The OA gives statistically improved averages and the objective assignment of confidence intervals to these averages. The ability to assign confidence intervals is the main advantage of this method. Confidence intervals reflect how densely and uniformly an area is sampled during the averaging season. For the global average, the early part of the record (1860–1890) and the times of the two world wars have largest uncertainties. Analysis of OA-based uncertainty estimates shows that before 1930 sampling in the Southern Hemisphere was as good as it was in the Northern Hemisphere. From about 1930 to 1950, uncertainties decreased in both hemispheres, but the magnitude of the Northern Hemisphere uncertainties reduced more and remained smaller. After the early 1950s uncertainties were relatively constant in both hemispheres, indicating that sampling was relatively consistent over the period. During the two world wars, increased uncertainties reflected the sampling decreases over all the oceans, with the biggest decreases south of 40°S. The OA global SST anomalies are virtually identical to estimates of global SST anomalies computed using simpler methods, when the same data corrections are applied. When data are plentiful over an area there is no clear advantage of the OA over simpler methods. The major advantage of the OA over the simpler methods is the accompanying error estimates.

The OA analysis suggests that SST anomalies were not significantly different from 0 from 1860 to 1900. This result is heavily influenced by the choice of the data corrections applied before the 1950s. Global anomalies are also near zero from 1940 until the mid-1970s. The OA analysis suggests that negative anomalies dominated the period from the early 1900s through the 1930s although the uncertainties are quite large during and immediately following World War I. Finally, the OA analysis shows significant positive global SST anomalies beginning in the late 1970s. The SST anomalies in the Indian Ocean and Southern Ocean poleward of 20°S make the strongest contributions to the positive global anomalies observed since the late 1970s. In contrast to the more recent period, the SST anomalies in the period from the early 1900s through 1940 were dominated by the anomalies in the Northern Hemisphere poleward of 20°N.

Full access
Chester F. Ropelewski, Michael S. Halpert, and Xueliang Wang

Abstract

Tropospheric biennial variability in several components of the Southern Oscillation (SO) is defined and described through analysis of observational data from the Comprehensive Ocean-Atmosphere Data Set (COADS), as well as through investigation of several SO index time series. The analysis suggests that the temporal behavior of the SO can be described in terms of three components: 1) a pervasive biennial pulse, which appears to be strong in both the Indian Ocean and the west Pacific surface zonal winds as well as in several SO indices, 2) the annual cycle, which tends to set the phase of biennial variability for the major SO excursions, and 3) a low-frequency, or residual, variability, which may be associated with temporal scales between large SO episodes. This study also supports recent papers in suggesting that complete models of the SO must include the Indian Ocean basin.

Full access
Samuel S. Shen, Thomas M. Smith, Chester F. Ropelewski, and Robert E. Livezey

Abstract

This paper provides a systematic procedure for computing the regional average of climate data in a subregion of the earth surface using the covariance function written in terms of empirical orthogonal functions (EOFs). The method is optimal in the sense of minimum mean square error (mse) and gives an mse estimate of the averaging results. The random measurement error is also included in the total mse. Since the EOFs can account for spatial inhomogeneities, the method can be more accurate than those that assume a homogeneous covariance matrix. This study shows how to further improve the accuracy of optimal averaging (OA) by improving the accuracy of the eigenvalues of the covariance function through an extrapolation method. The accuracy of the authors’ procedure is tested using cross-validation techniques, which simulate past sampling conditions on the recent, well-sampled tropical Pacific SST and use the EOFs independent to the month being tested. The true sampling error of the cross-validated tests is computed with respect to the 1° × 1° data for various sampling conditions. The theoretical sampling error is computed from the authors’ derived formula and compared to the true error from the cross-validation tests. The authors’ numerical results show that (i) the extrapolation method can sometimes improve the accuracy of the eigenvalues by 10%, (ii) the optimal averaging consistently yields smaller mse than the arithmetic averaging, and (iii) the theoretical formula for evaluating the OA error gives estimates that compare well with the true error.

Full access
Michael S. Halpert, Gerald D. Bell, Vernon E. Kousky, and Chester F. Ropelewski

The El Niño-Southern Oscillation (ENSO) phenomenon is a major contributor to the observed year-to-year variability in the Pacific Ocean and in the global atmospheric circulation. The short-term climate system witnessed the return to the mature phase of warm ENSO conditions (commonly referred to as the El Nino) during early 1995 for the third time in four years. This frequency of occurrence is unprecedented in the last 50 years and is comparable to that observed during the prolonged 1911–15 ENSO episode.

These warm ENSO conditions contributed to a large-scale disruption of the normal patterns of wind, rainfall, and temperature over much of the tropics and middle latitudes, particularly during the December 1994–February 1995 period. This period was followed by a dramatic decrease in sea surface temperatures in the tropical Pacific, resulting in a complete disappearance of all warm episode conditions during June–August and in the development of weak coldepisode conditions during September–November.

Changes in the tropical Pacific were accompanied by pronounced, large-scale changes in the atmospheric circulation patterns from those that had prevailed during much of the early 1990s. Particular examples of these changes include 1) a dramatic return to a very active hurricane season over the North Atlantic, following four consecutive years of significantly below-normal hurricane activity; 2) the return to above-normal rainfall throughout Indonesia, northern Australia, and southern Africa, following a prolonged period of below-normal rainfall and periodic drought; and 3) a northward shift of the jet stream and storm track position over the eastern half of the North Pacific during the latter part of the year, following several winter seasons (three in the last four) characterized by a significant strengthening, southward shift, and eastward extension of these features toward the southwestern United States.

Other regional climate anomalies during 1995 included extreme warmth throughout western and central Asia during January–May and colder than normal conditions in this region during November–December, severe flooding in the midwestern United States (April–May), abnormally wet conditions in California and the southwestern United States (December–February) combined with near-record warmth over eastern North America, deadly heat waves in the central United States (mid-July) and India (first three weeks of June), drought in the northeastern United States (August), a drier-than-normal rainy season in central Brazil (September–December), and an intensification of drier-than-normal conditions over southern Brazil, Uruguay, and northeastern Argentina at the end of the year.

The global annual mean surface temperature for land and marine areas during 1995 averaged 0.40°C above the 1961–90 mean. This value exceeds the previous warmest year in the record (1990) by 0.04°C. The Northern Hemisphere also recorded its warmest year on record during 1995, with a mean departure from normal of 0.55°C. The global annual mean surface temperature for land areas only during 1995 was the second warmest since 1951.

The year also witnessed near-record low ozone amounts in the Southern Hemisphere stratosphere, with minimum values only slightly higher than the record low values observed in 1993. The areal extent of very low ozone values during 1995 was as widespread over Antarctica as in the record low year of 1993.

Full access