William B. Norris

Error Estimates of Version 5.0 of MSU-AMSU Bulk Atmospheric Temperatures

Abstract Deep-layer temperatures derived from satellite-borne microwave sensors since 1979 are revised (version 5.0) to account for 1) a change from microwave sounding units (MSUs) to the advanced MSUs (AMSUs) and 2) an improved diurnal drift adjustment for tropospheric products. AMSU data, beginning in 1998, show characteristics indistinguishable from the earlier MSU products. MSU–AMSU error estimates are calculated through comparisons with radiosonde-simulated bulk temperatures for the low–middle troposphere (TLT), midtroposphere (TMT), and lower stratosphere (TLS.) Monthly (annual) standard errors for global mean anomalies of TLT satellite temperatures are estimated at 0.10°C (0.07°C). The TLT (TMT) trend for January 1979 to April 2002 is estimated as +0.06° (+0.02°) ±0.05°C decade–1 (95% confidence interval). Error estimates for TLS temperatures are less well characterized due to significant heterogeneities in the radiosonde data at high altitudes, though evidence is presented to suggest that since 19...

Methodology and Results of Calculating Central California Surface Temperature Trends: Evidence of Human-Induced Climate Change?

Abstract A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this “homogeneous segments” of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910–2003. Results show that twentieth-century Valley minimum...

Tropospheric temperature change since 1979 from tropical radiosonde and satellite measurements

Received 11 November 2005 revised 14 June 2006 ; accepted 10 August 2006; published 16 March 2007. [i] Temperature change of the lower troposphere (LT) in the tropics (20°S-20°N) during the period 1979-2004 is examined using 58 radiosonde (sonde) stations and the microwave-based satellite data sets of the University of Alabama in Huntsville (UAH v5.2) and Remote Sensing Systems (RSS v2.1). At the 29 stations that make both day and night observations, the average nighttime trend (+0.12 K decade -1 ) is 0.05 K decades -1 more positive than that for the daytime (+0.07 K decade -1 ) in the unadjusted observations, an unlikely physical possibility indicating adjustments are needed. At the 58 sites the UAH data indicate a trend of +0.08 K decade -1 , the RSS data, +0.15. When the largest discontinuities in the sondes are detected and removed through comparison with UAH data, the trend of day and night releases combined becomes +0.09, and using RSS data, +0.12. Relative to several data sets, the RSS data show a warming shift, broadly occurring in 1992, of between +0.07 K and +0.13 K. Because the shift occurs at the time NOAA-12 readings began to be merged into the satellite data stream and large NOAA-11 adjustments were applied, the discrepancy appears to be due to bias adjustment procedures. Several comparisons are consistent with a 26-year trend and error estimate for the UAH LT product for the full tropics of +0.05 ± 0.07, which is very likely less than the tropical surface trend of+0.13 K decade -1 .

Surface Temperature Variations in East Africa and Possible Causes

Abstract Surface temperatures have been observed in East Africa for more than 100 yr, but heretofore have not been subject to a rigorous climate analysis. To pursue this goal monthly averages of maximum (TMax), minimum (TMin), and mean (TMean) temperatures were obtained for Kenya and Tanzania from several sources. After the data were organized into time series for specific sites (60 in Kenya and 58 in Tanzania), the series were adjusted for break points and merged into individual gridcell squares of 1.25°, 2.5°, and 5.0°. Results for the most data-rich 5° cell, which includes Nairobi, Mount Kilimanjaro, and Mount Kenya, indicate that since 1905, and even recently, the trend of TMax is not significantly different from zero. However, TMin results suggest an accelerating temperature rise. Uncertainty estimates indicate that the trend of the difference time series (TMax − TMin) is significantly less than zero for 1946–2004, the period with the highest density of observations. This trend difference continues i...

Satellite and VIZ–Radiosonde Intercomparisons for Diagnosis of Nonclimatic Influences

Abstract Radiosonde datasets of temperature often suffer from discontinuities due to changes in instrumentation, location, observing practices, and algorithms. To identify temporal discontinuities that affect the VIZ/Sippican family of radiosondes, the 1979–2004 time series of a composite of 31 VIZ stations are compared to composites of collocated values of layer temperatures from two microwave sounding unit datasets—the University of Alabama in Huntsville (UAH) and Remote Sensing Systems (RSS). Discontinuities in the radiosonde time series relative to the two satellite datasets were detected with high significance and with similar magnitudes; however, some instances occurred where only one satellite dataset differed from the radiosondes. For the products known as lower troposphere (LT; surface–300 hPa) and midtroposphere (MT; surface–75-hPa layer), significant discontinuities relative to both satellite datasets were found—two cases for LT and four for MT. These are likely associated with changes in the r...

Development of a comprehensive, multiscale ''one-atmosphere'' modeling system: application to the Southern Appalachian Mountains

A comprehensive three-dimensional Eulerian photochemical model (URM-1ATM) was developed that simulates urban and regional gas and size-resolved aerosol concentrations of pollutants in the atmosphere and both wet and dry deposition. In this study, RAMS and EMS-95 are used to generate meteorological and emission input files, respectively. The modeling system is then applied to simulate the evolution, transport, and removal of atmospheric pollutants over the Eastern US for the 11–19 July 1995 episode. Performance statistics are calculated for ozone, speciated fine particles, and acid deposition mass fluxes. r 2002 Elsevier Science Ltd. All rights reserved.

Meteorological conditions during the 1995 Southern Oxidants Study Nashville/Middle Tennessee Field Intensive

As a background for other papers presented in this issue on the 1995 Southern Oxidants Study (SOS) Nashville/Middle Tennessee Field Intensive, the role of meteorology in the field study is reviewed. Descriptions of the meteorological observing systems are given, and the strategy behind the observational network is defined. The tools used in making forecasts and their use for operational decisions are described. In particular, the use in real time of a dynamic boundary layer model coupled with a Lagrangian plume model to forecast power plant and urban plumes is examined. The weather occurring during the field intensive is summarized and put into a climatological perspective. Specific attention is given to the episodes of July 1–3 and July 10–14, 1995, when some of the highest ozone values were recorded. The role of nocturnal, low-level jets observed by the boundary layer wind profiler network in dispersing urban emissions into the regional background is explored.

Differential trends in tropical sea surface and atmospheric temperatures since 1979

A variety of measurements indicate that the rate of atmospheric warming in the tropics since 1979 is less than the observed warming of the sea surface. This result is further examined using the high quality buoys monitored by the Pacific Marine Environmental Laboratory in the Tropical Pacific Ocean. These buoys show cooling (most cases being statistically significant) of the air at 3m height relative to the sea at l m depth over 8 to 20-year periods in the eastern region. A global surface temperature dataset which uses only near-surface air temperature over both land and ocean, indicates less warming since 1979 than those using SSTs over the oceans, though large uncertainties remain with marine air temperatures.

Discontinuity Issues with Radiosonde and Satellite Temperatures in the Australian Region 1979–2006

Abstract The temperature records of 28 Australian radiosonde stations were compared with the bulk-layer temperatures of three satellite products of The University of Alabama in Huntsville (UAH) and Remote Sensing Systems (RSS) for the period 1979–2006. The purpose was to use the satellite data as “reference truth” to quantify the effect of changes in station equipment, software, and operations on the reported upper air temperatures and resulting trends. The products are lower troposphere (LT), midtroposphere (MT), and lower stratosphere (LS). Four periods of significant shifts in temperatures were found in the radiosondes relative to both satellite datasets. In the first two shifts—around 1982/83 and 1987/88—the radiosondes experienced an accumulated LT and MT warming shift of 0.5 K on average. These shifts coincided with equipment changes. If unadjusted for these shifts, the radiosondes report spurious tropospheric warming of almost 0.2 K decade−1. For LS in the first period, there is relative warming bu...

Estimation of Tropospheric Temperature Trends from MSU Channels 2 and 4

Abstract The problems inherent in the estimation of global tropospheric temperature trends from a combination of near-nadir Microwave Sounding Unit (MSU) channel-2 and -4 data are described. The authors show that insufficient overlap between those two channels’ weighting functions prevents a physical removal of the stratospheric influence on tropospheric channel 2 from the stratospheric channel 4. Instead, correlations between stratospheric and tropospheric temperature fluctuations based upon ancillary (e.g., radiosonde) information can be used to statistically estimate a correction for the stratospheric influence on MSU 2 from MSU 4. Fu et al. developed such a regression relationship from radiosonde data using the 850–300-hPa layer as the target predictand. There are large errors in the resulting fit of the two MSU channels to the tropospheric target layer, so the correlations from the ancillary data must be relied upon to provide a statistical minimization of the resulting errors. Such relationships dep...