John R. Christy

Climate forcings in Goddard Institute for Space Studies SI2000 simulations

[1] We define the radiative forcings used in climate simulations with the SI2000 version of the Goddard Institute for Space Studies (GISS) global climate model. These include temporal variations of well-mixed greenhouse gases, stratospheric aerosols, solar irradiance, ozone, stratospheric water vapor, and tropospheric aerosols. Our illustrations focus on the period 1951–2050, but we make the full data sets available for those forcings for which we have earlier data. We illustrate the global response to these forcings for the SI2000 model with specified sea surface temperature and with a simple Q-flux ocean, thus helping to characterize the efficacy of each forcing. The model yields good agreement with observed global temperature change and heat storage in the ocean. This agreement does not yield an improved assessment of climate sensitivity or a confirmation of the net climate forcing because of possible compensations with opposite changes of these quantities. Nevertheless, the results imply that observed global temperature change during the past 50 years is primarily a response to radiative forcings. It is also inferred that the planet is now out of radiation balance by 0.5 to 1 W/m 2 and that additional global warming of about 0.5� C is already ‘‘in the pipeline.’’ INDEX TERMS: 1620 Global Change: Climate dynamics (3309); 1635 Global Change: Oceans (4203); 1650 Global Change: Solar variability;

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...

MSU Tropospheric Temperatures: Dataset Construction and Radiosonde Comparisons

Abstract Two deep-layer tropospheric temperature products, one for the lower troposphere (T2LT) and one for the midtroposphere (T2, which includes some stratospheric emissions), are based on the observations of channel 2 of the microwave sounding unit on National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites. Revisions to version C of these datasets have been explicitly applied to account for the effects of orbit decay (loss of satellite altitude) and orbit drift (east–west movement). Orbit decay introduces an artificial cooling in T2LT, while the effects of orbit drift introduce artificial warming in both T2LT and T2. The key issues for orbit drift are 1) accounting for the diurnal cycle and 2) the adjustment needed to correct for spurious effects related to the temperature of the instrument. In addition, new calibration coefficients for NOAA-12 have been applied. The net global effect of these revisions (version D) is small, having little impact on the year-to-year anomalies. T...

Precise Monitoring of Global Temperature Trends from Satellites

Passive microwave radiometry from satellites provides more precise atmospheric temperature information than that obtained from the relatively sparse distribution of thermometers over the earths surface. Accurate global atmospheric temperature estimates are needed for detection of possible greenhouse warming, evaluation of computer models of climate change, and for understanding important factors in the climate system. Analysis of the first 10 years (1979 to 1988) of satellite measurements of lower atmospheric temperature changes reveals a monthly precision of 0.01�C, large temperature variability on time scales from weeks to several years, but no obvious trend for the 10-year period. The warmest years, in descending order, were 1987, 1988, 1983, and 1980. The years 1984, 1985, and 1986 were the coolest.

Solar radiative forcing at selected locations and evidence for global lower tropospheric cooling following the eruptions of El Chichón and Pinatubo

As a result of the eruption of Mt. Pinatubo (June 1991), direct solar radiation was observed to decrease by as much as 25–30% at four remote locations widely distributed in latitude. The average total aerosol optical depth for the first 10 months after the Pinatubo eruption at those sites is 1.7 times greater than that observed following the 1982 eruption of El Chichon. Monthly-mean clear-sky total solar irradiance at Mauna Loa, Hawaii, decreased by as much as 5% and averaged 2.4% and 2.7% in the first 10 months after the El Chichon and Pinatubo eruptions, respectively. By September 1992 the global and northern hemispheric lower tropospheric temperatures had decreased 0.5°C and 0.7°C, respectively compared to pre-Pinatubo levels. The temperature record examined consists of globally uniform observations from satellite microwave sounding units.

Analysis of the Merging Procedure for the MSU Daily Temperature Time Series

Abstract The merging procedure utilized to generate homogeneous time series of three deep-layer atmospheric temperature products from the nine microwave sounding units (MSUs) is described. A critically important aspect in the process is determining and removing the bias each instrument possesses relative to a common base (here being NOAA-6). Special attention is given to the lower-tropospheric layer and the calculation of the bias of the NOAA-9 MSU and its rather considerable impact on the trend of the overall time series. We show that the bias is best calculated by a direct comparison between NOAA-6 and NOAA-9, though there other possible methods available, and is determined to be +0.50°C. Spurious variations of individual MSUs due to orbital drift and/or cyclic variations tied to the annual cycle are also identified and eliminated. In general, intersatellite biases for the three instruments that form the backbone of the time series (MSUs on NOAA-6, -10 and -12) are known to within 0.01°C. After slight m...

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...

Precision and Radiosonde Validation of Satellite Gridpoint Temperature Anomalies. Part I: MSU Channel 2

Abstract In Part I of this study, monthly 2.5° gridpoint anomalies in the TIROS-N satellite series Microwave Sounding Unit (MSU) channel 2 brightness temperatures during 1979–88 are evaluated with multiple satellites and radiosonde data for their climate temperature monitoring capability. The MSU anomalies are computed about a 10-year mean annual cycle at each grid point, with the MSUs intercalibrated to a common arbitrary level. The intercalibrations remove relative biases between instruments of up to several tenths of a degree celsius. The monthly gridpoint anomaly agreement between concurrently operating satellites reveals single-satellite precision generally better than 0.07°C in the tropics and better than 0.15°C at higher latitudes. Monthly anomalies in radiosonde channel 2 brightness temperatures computed with the radiative transfer equation compare very closely to the MSU measured anomalies in all climate zones, with correlations generally from 0.94 to 0.98 and standard errors of 0.15°C in the tro...

Global atmospheric temperature monitoring with satellite microwave measurements - Method and results 1979-84

Abstract A method for measuring global atmospheric temperature anomalies to a high level of precision from satellites is demonstrated. Global data from the Microwave Sounding Units (MSUs), flying on NOAA satellites since late 1978, have been analysed to determine the extent to which these data can reveal atmospheric temperature anomalies on bidaily and longer time scales for regional and larger space scales. The global sampling provided by the MSUs is an important asset, with most of the earth sampled bidaily from each of (typically) two instruments flying concurrently on separate satellites at different solar times. The primary source of tropospheric thermal information is from the MSU 53.74 GHz channel. This channel is primarily sensitive to thermal emission from molecular oxygen in the middle troposphere, with relatively little sensitivity to water vapor, the earths surface, and cloud (especially cirrus) variations. The long-term stability of the oxygen mixing ratio in the atmosphere makes it an ideal...

Uncertainty in Signals of Large-Scale Climate Variations in Radiosonde and Satellite Upper-Air Temperature Datasets

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 upperair 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.