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 1979 the trend is −0.51° ± 0.10°C decade–1.
Microwave Sounding Unit channel 4 data from the TIROS-N series of NOAA satellites are intercalibrated to provide a continuous global record of deep-layer averaged lower stratospheric temperatures during 1979–1991. A 13-year record of temperature anomalies is time averaged into pentads and months on a 2.5° grid. The monthly gridpoint anomalies are validated with ten years of radiosonde data during 1979–88. The calibration stability of each satellite's measurements is evaluated during satellite overlap periods, the longest of which reveal no measurable instrumental drift at the level of 0.01°C yr−1. Intercomparisons between NOAA-6 and NOAA-7 anomalies indicate monthly gridpoint precision of 0.05°C in the tropics to around 0.10°C in the extratropies, and signal-to-noise ratios generally over 500, while global monthly precision is 0.01° to 0.02°C. These precision and stability statistics are much better than have been previously reported by other investigators for MSU channel 4. Pentad precision is about 0.10°C in the tropics to around 0.25°C at high latitudes and signal-to- noise ratios generally over 250 in the tropics and high latitude but 100–200 in the middle latitudes. Radiosonde comparisons to the monthly gridpoint anomalies have correlations ranging from 0.90 in the tropics (when the interannual variability is smallest) to as high as 0.99 at high-latitude stations. The corresponding standard error of estimate is generally around 0.3°C. A significant difference in decadal trends is found between the satellite and radiosonde systems, with a step change of 0.217°C (sondes cooler) compared to the satellite measurements. Investigations of the possible sources of the discrepancy lead us to suspect that the gradual transition from on-site calibration of sondes with thermometers to factory calibration of sondes around 1982 might have caused a change in the calibration, although this conclusion must be viewed as tentative. The largest globally averaged temperature variations during 1979–91 occur after the El Chichón (1982) and Pinatubo (1991) volcanic eruptions. These warm events are superimposed upon a net downward trend in temperatures during the period. This cooling trend has more of a step function than linear character, with the step occurring during the El Chichón warm event. It is strongest in polar regions and the Northern Hemisphere middle latitudes. These characteristics are qualitatively consistent with radiative adjustments expected to occur with observed ozone depictions.
The potential of microwave sounding units (MSU) for augmenting the surface-based thermometer record by providing a measurement representing a significant depth of the troposphere is considered. These radiometers measure the thermal emission by molecular oxygen in the atmosphere at different spectral intervals in the oxygen absorption complex near 60 GHz. Brightness temperature variations measured by NOAA-6 and NOAA-7 MSUs during a near-two year period are analyzed and compared with monthly averaged surface air temperature data. It is demonstrated that MSUs, while of limited use for vertical profiling of the atmosphere, provide stable measurements of vertically average atmospheric temperatures, centered at a constant pressure level.
Global archives were established for ECMWF 12-hour, multilevel analysis beginning 1 January 1985; day and night IR temperatures, and solar incoming and solar absorbed. Routines were written to access these data conveniently from NASA/MSFC MASSTOR facility for diagnostic analysis. Calculations of diabatic heating rates were performed from the ECMWF data using 4-day intervals. Calculations of precipitable water (W) from 1 May 1985 were carried out using the ECMWF data. Because a major operational change on 1 May 1985 had a significant impact on the moisture field, values prior to that date are incompatible with subsequent analyses.
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 Chichón. 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 Chichón 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.
Abstract Temperature readings observed at surface weather stations have been used for detecting changes in climate due to their long period of observations. The most common temperature metrics recorded are the daily maximum (TMax) and minimum (TMin) extremes. Unfortunately, influences besides background climate variations impact these measurements such as changes in (1) instruments, (2) location, (3) time of observation, and (4) the surrounding artifacts of human civilization (buildings, farms, streets, etc.) Quantifying (4) is difficult because the surrounding infrastructure, unique to each site, often changes slowly and variably and is thus resistant to general algorithms for adjustment. We explore a direct method of detecting this impact by comparing a single station that experienced significant development from 1895 to 2019, and especially since 1970, relative to several other stations with lesser degrees of such development (after adjustments for the (1) to (3) are applied). The target station is Fresno, California (metro population ~ 15,000 in 1900 and ~ 1 million in 2019) situated on the eastern side of the broad, flat San Joaquin Valley in which several other stations reside. A unique component of this study is the use of pentad (5-day averages) as the test metric. Results indicate that Fresno experienced + 0.4 °C decade −1 more nighttime warming (TMin) since 1970 than its neighbors—a time when population grew almost 300%. There was little difference seen in TMax trends between Fresno and non-Fresno stations since 1895 with TMax trends being near zero. A case is made for the use of TMax as the preferred climate metric relative to TMin for a variety of physical reasons. Additionally, temperatures measured at systematic times of the day (i.e., hourly) show promise as climate indicators as compared with TMax and especially TMin (and thus TAvg) due to several complicating factors involved with daily high and low measurements.
Abstract Coats raises issues regarding the utility of the snowfall metric presented by Christy in “Searching for information in 133 years of California snowfall observations,” suggesting that variance issues need more attention and that alternative metrics would be more useful than snowfall. Although discussed by Christy, the variance question is further addressed here. Regarding other metrics, it is shown that they are either inconsistently measured for long-term analysis or are actually consistent with Christy’s findings. In addition, it is demonstrated that Tahoe City, discussed by Coats, is inappropriate for examining long-term precipitation trends because of inconsistent measuring practices through time. Christy’s results remain unchanged.
Relatively few studies have attempted to simulate synthetic MSU temperatures with use of a radiation model. Most employ the simpler and computationally less-expensive method of applying a static, global-mean weighting function to three-dimensional profiles of atmospheric temperature. Both approaches require a number of key assumptions. One of the major assumptions relates to surface emissivity. To date, two different strategies have been used for prescribing surface emissivity values. The first assumes a fixed global surface emissivity, while the second specifies separate (time-invariant) emissivity values for land and ocean. In this research, we introduce space- and time-dependence to the specified emissivity fields, using recent observationally-based estimates of surface emissivity changes over 1988 to 2000. We use a radiative transfer code to explore the impact of this more complex treatment of surface emissivity. This sensitivity analysis is performed with monthly-mean fields of surface temperature, atmospheric temperature, and moisture taken from multiple reanalyses. Our goal is to quantify the possible impact of emissivity changes on global-scale estimates of tropospheric temperature trends (e.g., trends estimated from MSU channel 2 and MSU 2LT), and to document the sensitivity of synthetic MSU temperatures to a variety of input data and processing choices.
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