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W. D. Nowlin Jr. and C. A. Parker

Abstract

Two surveys of the waters over an area of the continental shelf in the northwestern Gulf of Mexico were made during January 1966. The first observation period was just before a major outbreak of cold, dry air; the second was about 15 days later with the region still under the influence of this outbreak. Waters were well mixed to 100 m, or the bottom in shallower depths. During the 15-day period temperature decreased nearly 5C and salinity increased about 1‰ near the shore. Some 150 mi offshore, temperature decreased only 1–2C and salinity showed no significant change.

Study of the change in T-S relationships before and after the outbreak indicates the strong possibility that subsurface water types generally found beneath the Subtropical Underwater core in the Gulf were formed locally over the shelf by evaporation and sensible heat exchange to the atmosphere.

For the period between observations, the mean rates of change of vertically-averaged salinity, temperature and heat content were computed. Neglecting advection, the local rate of heat extraction averaged about 400 cal cm−2 day−1 within 50 mi from shore and generally increased to 700–1500 cal cm−2 day−1 at the offshore survey limits. These values agree reasonably well in magnitude and spatial distribution with estimates of heat fluxes using bulk formulas and meteorological data taken during the post-outbreak cruise. Average values of sensible and latent heat fluxes for the region were 255 and 542 cal cm−2 day−1, respectively, which generally agree with estimates by other workers for outbreak conditions. Such estimates are reviewed.

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C. E. Coulman and M. A. Parker

Abstract

An instrument which measures the total water mixing ratio in cloud has been calibrated to an accuracy of ∼ ±0.1 g kg−1 in the presence of liquid water contents ranging up to 7 g kg−1. Evaporation occurs in a labyrinth of heated plates and the mixing ratio is measured psychrometrically. Close agreement with independent measurements of liquid and vapor content during flights through cloud is demonstrated.

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1st Lt. Robert E. Parker, A.C. and 1st Lt. John Cochrane, A.C.
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C. E. Birch, S. Webster, S. C. Peatman, D. J. Parker, A. J. Matthews, Y. Li, and M. E. E. Hassim

Abstract

State-of-the-art regional climate model simulations that are able to resolve key mesoscale circulations are used, for the first time, to understand the interaction between the large-scale convective environment of the MJO and processes governing the strong diurnal cycle over the islands of the Maritime Continent (MC). Convection is sustained in the late afternoon just inland of the coasts because of sea breeze convergence. Previous work has shown that the variability in MC rainfall associated with the MJO is manifested in changes to this diurnal cycle; land-based rainfall peaks before the active convective envelope of the MJO reaches the MC, whereas oceanic rainfall rates peak while the active envelope resides over the region. The model simulations show that the main controls on oceanic MC rainfall in the early active MJO phases are the large-scale environment and atmospheric stability, followed by high oceanic latent heat flux forced by high near-surface winds in the later active MJO phases. Over land, rainfall peaks before the main convective envelope arrives (in agreement with observations), even though the large-scale convective environment is only moderately favorable for convection. The causes of this early rainfall peak are strong convective triggers from land–sea breeze circulations that result from high surface insolation and surface heating. During the peak MJO phases cloud cover increases and surface insolation decreases, which weakens the strength of the mesoscale circulations and reduces land-based rainfall, even though the large-scale environment remains favorable for convection at this time. Hence, scale interactions are an essential part of the MJO transition across the MC.

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L. Garcia-Carreras, A. J. Challinor, B. J. Parkes, C. E. Birch, K. J. Nicklin, and D. J. Parker

Abstract

Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty.

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Bruce A. Wielicki, J.T. Suttles, Andrew J. Heymsfield, Ronald M. Welch, James D. Spinhirne, Man-Li C. Wu, David O'C. Starr, Lindsay Parker, and Robert F. Arduini

Abstract

Observations of cirrus and altocumulus clouds during the First International Satellite Cloud Climatology Project Regional Experiment (FIRE) are compared to theoretical models of cloud radiative properties. Three tests are performed. First, Landsat radiances are used to compare the relationship between nadir reflectance at 0.83 μm and beam emittance at 11.5 μm with that predicted by model calculations using spherical and nonspherical phase functions. Good agreement is found between observations and theory when water droplets dominate. Poor agreement is found when ice particles dominate, especially if scattering phase functions for spherical particles am used. Even when compared to a laboratory measured ice particle phase function (Volkovitskiy et al. 1980), the observations show increased side scattered radiation relative to the theoretical calculations. Second, the anisotropy of conservatively scattered radiation is examined using simultaneous multiple-angle views of the cirrus from Landsat and ER-2 aircraft radiometers. Observed anisotropy gives good agreement with theoretical calculations using the laboratory measured ice-particle phase function and poor agreement with a spherical-particle phase function. Third, Landsat radiances at 0.83 μm, 1.65 μm, and 2.21 μm are used to infer particle phase and particle size. For water droplets, good agreement is found with King Air FSSP particle probe measurements in the cloud. For ice particles, the Landsat radiance observations predict an effective radius of 60 μm versus aircraft observations of about 200 μm. It is suggested that this discrepancy may be explained by uncertainty in the imaginary index of ice and by inadequate measurements of small ice particles by microphysical probes.

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N. A. Rayner, P. Brohan, D. E. Parker, C. K. Folland, J. J. Kennedy, M. Vanicek, T. J. Ansell, and S. F. B. Tett

Abstract

A new flexible gridded dataset of sea surface temperature (SST) since 1850 is presented and its uncertainties are quantified. This analysis [the Second Hadley Centre Sea Surface Temperature dataset (HadSST2)] is based on data contained within the recently created International Comprehensive Ocean–Atmosphere Data Set (ICOADS) database and so is superior in geographical coverage to previous datasets and has smaller uncertainties. Issues arising when analyzing a database of observations measured from very different platforms and drawn from many different countries with different measurement practices are introduced. Improved bias corrections are applied to the data to account for changes in measurement conditions through time. A detailed analysis of uncertainties in these corrections is included by exploring assumptions made in their construction and producing multiple versions using a Monte Carlo method. An assessment of total uncertainty in each gridded average is obtained by combining these bias-correction-related uncertainties with those arising from measurement errors and undersampling of intragrid box variability. These are calculated by partitioning the variance in grid box averages between real and spurious variability. From month to month in individual grid boxes, sampling uncertainties tend to be most important (except in certain regions), but on large-scale averages bias-correction uncertainties are more dominant owing to their correlation between grid boxes. Changes in large-scale SST through time are assessed by two methods. The linear warming between 1850 and 2004 was 0.52° ± 0.19°C (95% confidence interval) for the globe, 0.59° ± 0.20°C for the Northern Hemisphere, and 0.46° ± 0.29°C for the Southern Hemisphere. Decadally filtered differences for these regions over this period were 0.67° ± 0.04°C, 0.71° ± 0.06°C, and 0.64° ± 0.07°C.

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Keith D. Sherburn, Matthew D. Parker, Casey E. Davenport, Richard A. Sirico, Jonathan L. Blaes, Brandon Black, Shaelyn E. McLamb, Michael C. Mugrage, and Ryan M. Rackliffe

Abstract

Recent research has improved our knowledge and forecasting of high-shear, low-CAPE (HSLC) severe convection, which produces a large fraction of overnight and cool season tornadoes. However, limited near-storm observations have hindered progress in our understanding of HSLC environments and detection of severe potential within them. This article provides an overview of a research project in central North Carolina aimed toward increasing the number of observations in the vicinity of severe and nonsevere HSLC convection. Particularly unique aspects of this project are a) leadership by student volunteers from a university sounding club and b) real-time communication of observations to local National Weather Service Forecast Offices. In addition to an overview of sounding operations and goals, two case examples are provided that support the potential utility of supplemental sounding observations for operational, educational, and research purposes.

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The JET2000 Project: Aircraft Observations of the African Easterly Jet and African Easterly Waves

Aircraft Observations of the African Easterly Jet and African Easterly Waves

C. D. Thorncroft, D. J. Parker, R. R. Burton, M. Diop, J. H. Ayers, H. Barjat, S. Devereau, A. Diongue, R. Dumelow, D. R. Kindred, N. M. Price, M. Saloum, C. M. Tayor, and A. M. Tompkins

Scientific background and motivation for the JET2000 aircraft observing campaign that took place in West Africa during the last week of August 2000 are presented. The Met Research Flight CI30 aircraft made two flights along the African easterly jet (AEJ) between Sal, Cape Verde, and Niamey, Niger, and two “box” flights that twice crossed the AEJ at longitudes near Niamey. Dropsondes were released at approximately 0.5°–10° intervals. The two box flights also included low-level flights that sampled north–south variations in boundary layer properties in the baroclinic zone beneath the AEJ.

Preliminary results and analysis of the JET2000 period including some of the aircraft data are presented. The JET2000 campaign occurred during a relatively dry period in the Niamey region and, perhaps consistent with this, was also associated with less coherent easterly wave activity compared to other periods in the season. Meridional cross sections of the AEJ on 28 and 29 August (after the passage of a mesoscale system) are presented and discussed. Analysis of dropsonde data on 28 August indicates contrasting convective characteristics north and south of the AEJ with dry convection more dominant to the north and moist convection more dominant to the south. The consequences of this for the AEJ and the relationship with the boundary layer observations are briefly discussed.

Preliminary NWP results indicate little sensitivity to the inclusion of the dropsonde data on the AEJ winds in European Centre for Medium-Range Weather Forecasts (ECMWF) and Met Office analyses. It is proposed that this may be due to a good surface analysis and a realistic model response to this. Both models poorly predict the AEJ in the 5-day forecast indicating the need for more process studies in the region.

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D. J. Seidel, J. K. Angell, J. Christy, M. Free, S. A. Klein, J. R. Lanzante, C. Mears, D. Parker, M. Schabel, R. Spencer, A. Sterin, P. Thorne, and F. Wentz

Abstract

There is no single reference dataset of long-term global upper-air temperature observations, although several groups have developed datasets from radiosonde and satellite observations for climate-monitoring purposes. The existence of multiple data products allows for exploration of the uncertainty in signals of climate variations and change. This paper examines eight upper-air temperature datasets and quantifies the magnitude and uncertainty of various climate signals, including stratospheric quasi-biennial oscillation (QBO) and tropospheric ENSO signals, stratospheric warming following three major volcanic eruptions, the abrupt tropospheric warming of 1976–77, and multidecadal temperature trends. Uncertainty estimates are based both on the spread of signal estimates from the different observational datasets and on the inherent statistical uncertainties of the signal in any individual dataset.

The large spread among trend estimates suggests that using multiple datasets to characterize large-scale upper- air temperature trends gives a more complete characterization of their uncertainty than reliance on a single dataset. For other climate signals, there is value in using more than one dataset, because signal strengths vary. However, the purely statistical uncertainty of the signal in individual datasets is large enough to effectively encompass the spread among datasets. This result supports the notion of an 11th climate-monitoring principle, augmenting the 10 principles that have now been generally accepted (although not generally implemented) by the climate community. This 11th principle calls for monitoring key climate variables with multiple, independent observing systems for measuring the variable, and multiple, independent groups analyzing the data.

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