Abstract

Time series of snowfall observations from over 500 stations in Oregon (OR) and Washington (WA) were generated for subregions of these states. Data problems encountered were as follows: 1) monthly totals in printed reports prior to 1940 that were not in the digital archive, 2) archived data listed as “missing” that were available, 3) digitized reports after 2010 eliminated good data, and 4) “zero” totals incorrectly entered in the official archive rather than “missing,” especially after 1980. Though addressing these was done, there is reduced confidence that some regional time series are representative of true long-term trends, especially for regions with few systematically reporting stations. For most regions characterized by consistent monitoring and with the most robust statistical reproducibility, we find no statistically significant trends in their periods of record (up to 131 years) for November–April seasonal totals through April 2020. This result includes the main snowfall regions of the Cascade Range. However, snowfall in some lower-elevation areas of OR and WA appear to have experienced declining trends, consistent with an increase in northeastern Pacific Ocean temperatures. Finally, previously constructed time series through April 2011 for regions in California are updated through April 2020 to include the recent, exceptionally low seasonal totals on the western slopes of the Sierra Nevada. This update indicates 2014/15 was the record lowest, 2013/14 was the 5th lowest, and 2012/13 was the 14th lowest of 142 years. Even so, the 1879–2020 linear trend in this key watershed region, though −2.6% decade⁻¹, was not significantly different from zero due to high interannual variability and reconstruction uncertainty.

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.

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.

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.

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.

Abstract

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.

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 tropics to 0.30°C at high latitudes. Simplification of these radiative transfer calculations to a static weighting profile applied to the radiosonde temperature profile leads to an average degradation of only 0.02° in the monthly skill. In terms of a more traditionally measured quantity, the MSU channel 2 anomalies match best with either the radiosonde 100–20-kPa or 100–15-kPa layer anomalies. No significant spurious trends were found in the 10-yr satellite dataset compared to the radiosondes that would indicate a calibration drift in either system. Thus, sequentially launched, overlapping passive microwave radiometers provide a useful system for monitoring intraseasonal to interannual climate anomalies and offer hope for monitoring of interdecadal trends from space. The Appendix includes previously unpublished details of the MSU gridpoint anomaly dataset construction. Part II of this study addresses the removal from channel 2 of the temperature influence above the 30-kPa level, providing a sharper and thus potentially more useful weighting function for monitoring lower tropospheric temperatures.

Abstract

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.

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.

Abstract

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.