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John R. Christy

Abstract

The International Surface Temperature Initiative is a worldwide effort to locate weather observations, digitize them for public access, and attach provenance to them. As part of that effort, this study sought documents of temperature observations for the nation of Uganda. Although scattered reports were found for the 1890s, consistent record keeping appears to have begun in 1900. Data were keyed in from images of several types of old forms as well as accessed electronically from several sources to extend the time series of 32 stations with at least 4 yr of data back as far as data were available. Important gaps still remain; 1979–93 has virtually no observations from any station. Because many stations were represented by more than one data source, a scheme is described to extract the “best guess” values for each station of monthly averages of the daily maximum, minimum, and mean temperature. A preliminary examination of the national time series indicates that, since the early twentieth century, it appears that Uganda experienced essentially no change in monthly-average daily maximum temperature but did experience a considerable rise in monthly-average daily minimum temperature, concentrated in the last three decades. Because there are many gaps in the data, it is hoped that readers with information on extant data that were not discovered for this study will contact the author or the project so that the data may be archived.

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John R. Christy

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.

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John R. Christy

Abstract

Monthly snowfall totals from over 500 stations in California, some of which date back to 1878, are examined. Most data were accessed through the NOAA archive, but several thousand station months of data were separately keyed in from image files of original documents. Over 26 000 of these entries were new relative to the NOAA archive, generally providing data prior to 1920. The stations were then subdivided into 18 regions for the construction of representative time series of each area. There were problems with the basic data—the most difficult with which to deal was the increasing presence of “zero” totals that should have been recorded as “missing.” This and other issues reduce the confidence that the regional time series are representative of true variations and trends, especially for regions with few systematically reporting stations. Interpreting linear trends on time series with infrequent large anomalies of one sign (i.e., heavy snowfall years) and unresolved data issues should be done with caution. For those regions characterized by consistent monitoring and with the most robust statistical reproducibility, no statistically significant trends in their periods of record (up to 133 years) nor in the most recent 50 years are found. This result encompasses the main snowfall region of the western slope of the Sierra Nevada Mountains.

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WHEN WAS THE HOTTEST SUMMER?

A State Climatologist Struggles for an Answer

John R. Christy

To answer this very common though surprisingly difficult question, a technique was developed to reconstruct a local temperature time series of summer average maximum temperatures in north-central Alabama since 1893. The results show that the warmest summer was 1925 at 34.9° ±0.4°C but that 5 other years are statistically so close they could not be eliminated as contenders. (The trend is −0.13°C decade−1.) Our insistence that this ambiguity be recognized by the inquirer, usually the media, causes confusion and reduces their interest level because they desire an absolute answer to, in their view, a very simple question.

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Masami Sakamoto and John R. Christy

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A Japanese long-term reanalysis (JRA-25) was completed in 2006 utilizing the comprehensive set of observations from the 40-yr ECMWF Re-Analysis (ERA-40). JRA-25 and ERA-40 adopted the same type of assimilation systems: 3DVAR with direct use of satellite sounding radiances. Long-term upper-air thermal tendencies in both reanalyses are examined and compared with the observational deep-layer temperatures of the University of Alabama in Huntsville (UAH) and Remote Sensing Systems (RSS). The upper-air temperature tendencies in the reanalyses are significantly different from those of UAH and RSS, and they appear to be influenced by the way the observations of the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) are used.

This study focuses on documenting problems in TOVS assimilation, especially problems in bias corrections used in the reanalyses. Referring to quantitative results in an examination of biases between the reanalyses and raw TOVS observations, this study identifies (i) spurious thermal tendencies derived from transitions in TOVS and in the reanalysis calculation streams, (ii) an excessive enhancement of the tropical water cycle in ERA-40, and (iii) an excessive cooling trend and unstable behavior in the stratospheric temperature in JRA-25.

The results of this study suggest that any inconsistencies in TOVS usage can lead to serious inconsistencies in the reanalyses. Therefore, time-consuming efforts to obtain reliable observational information from TOVS are necessary for further progress in reanalyses.

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John R. Christy and William B. Norris

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 radiosonde system. Three apparent radiosonde discontinuities were also determined for the lower-stratospheric product (LS; 150–15 hPa). Because they cannot be definitely traced to changes in the radiosonde system, they could be the result of common errors in the satellite products. When adjustments are applied to the radiosondes based independently on each satellite dataset, 26-yr trends of UAH (RSS) are consistent with the radiosondes for LT, MT, and LS at the level of ±0.06, ±0.04, and ±0.07 (±0.12, ±0.10, and ±0.10) K decade−1. Also, simple statistical retrievals based on radiosonde-derived relationships of LT, MT, and LS indicate a higher level of consistency with UAH products than with those of RSS.

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John R. Christy and Roy W. Spencer

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Po-Chedley and Fu investigated the difference in the magnitude of global temperature trends generated from the Microwave Sounding Unit (MSU) for the midtroposphere (T MT, surface to about 75 hPa) between the University of Alabama in Huntsville (UAH) and Remote Sensing Systems (RSS). Their approach was to examine the magnitude of a noise-reduction coefficient of one short-lived satellite, NOAA-9, which differed from UAH and RSS. Using radiosonde comparisons over a 2-yr period, they calculated an adjustment to the UAH coefficient that, when applied to the UAH data, increased the UAH global T MT trend for 1979–2009 by +0.042 K decade−1, which then happens to agree with RSS’s T MT trend. In studying their analysis, the authors demonstrate 1) the adjustment calculated using radiosondes is inconclusive when errors are accounted for; 2) the adjustment was applied in a manner inconsistent with the UAH satellite merging strategy, creating a larger change than would be generated had the actual UAH methodology been followed; and 3) that trends of a similar product that uses the same UAH coefficient are essentially identical to UAH and RSS. Based on the authors’ previous analysis and additional work here, UAH will continue using the NOAA-9 noise-reduction coefficient, as is, for version 5.4 and the follow-on version 5.5.

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John R. Christy and Richard T. McNider

Abstract

Three time series of average summer [June–August (JJA)] daily maximum temperature (TMax) are developed for three interior regions of Alabama from stations with varying periods of record and unknown inhomogeneities. The time frame is 1883–2014. Inhomogeneities for each station’s time series are determined from pairwise comparisons with no use of station metadata other than location. The time series for the three adjoining regions are constructed separately and are then combined as a whole assuming trends over 132 yr will have little spatial variation either intraregionally or interregionally for these spatial scales. Varying the parameters of the construction methodology creates 333 time series with a central trend value based on the largest group of stations of −0.07°C decade−1 with a best-guess estimate of measurement uncertainty from −0.12° to −0.02°C decade−1. This best-guess result is insignificantly different (0.01°C decade−1) from a similar regional calculation using NOAA’s divisional dataset based on daily data from the Global Historical Climatology Network (nClimDiv) beginning in 1895. Summer TMax is a better proxy, when compared with daily minimum temperature and thus daily average temperature, for the deeper tropospheric temperature (where the enhanced greenhouse signal is maximized) as a result of afternoon convective mixing. Thus, TMax more closely represents a critical climate parameter: atmospheric heat content. Comparison between JJA TMax and deep tropospheric temperature anomalies indicates modest agreement (r 2 = 0.51) for interior Alabama while agreement for the conterminous United States as given by TMax from the nClimDiv dataset is much better (r 2 = 0.86). Seventy-seven CMIP5 climate model runs are examined for Alabama and indicate no skill at replicating long-term temperature and precipitation changes since 1895.

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John R. Christy and William B. Norris

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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 but in the second, cooling. If unadjusted, the radiosondes overstate LS cooling by about −0.15 K decade−1.

The third (early 1990s) and fourth (1998 LT and MT and 2002 LS) shifts are less robustly connected to changes in the radiosondes. Errors in the construction methodology of the satellite products likely account for at least part of the discrepancies but cannot be attributed with confidence to a specific cause. Having opposite signs in the two periods, the last two discrepancies tend to cancel each other. The net effect of these last two shifts on the overall LT and MT trends of ±0.03 K decade−1 is small.

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Roy W. Spencer and John R. Christy

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TIROS-N satellite Microwave Sounding Unit (MSU) channel 2 data from different view angles across the MSU man swath are combined to remove the influence of the lower stratosphere and much of the upper troposphere on the measured brightness temperatures. The retrieval provides a sharper averaging kernel than the raw channel 2 weighting function, with a peak lowered from 50 kPa to 70 kPa and with only slightly more surface influence than raw channel 2. Monthly 2.5° gridpoint anomalies of this tropospheric retrieval compared between simultaneously operating satellites indicate close agreement, 0.15°C in the tropics to around 0.30°C over much of the higher latitudes. The agreement is not as close as with raw channel 2 anomalies because synoptic-scale temperature gradient information across the 2000-km swath of the MSU is lost in the retrieval procedure and because the retrieval involves the magnification of a small difference between two large numbers. Single gridpoint monthly anomaly correlations between the satellite measurements and the radiosonde calculations range from around 0.95 at high latitudes to below 0.8 in the tropical west Pacific, with standard errors of estimate of 0.16°C at Guam to around 0.50°C at high-latitude continental stations. Calculation of radiosonde temperature with a static weighting function instead of the radiative transfer equation degrades the standard errors by an average of less than 0.04°C. Of various standard tropospheric layers, the channel 2 retrieval anomalies correlate best with radiosonde 100–50- or 100–40-kPa-thickness anomalies. A comparison between global and hemispheric anomalies computed for raw channel 2 data versus the tropospheric retrieval show a correction in the 1979–90 time series for the volcano-induced stratospheric warming of 1982–83, which was independently observed by MSU channel 4. This correction leads to a slightly greater tropospheric warming trend in the 12-year time series (1979–90) for the tropospheric retrieval [0.039°C (±0.03°C) per decade] than for channel 2 alone [0.022°C (±0.02°C) per decade].

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