No abstract

[1] Planetary boundary layer (PBL) processes control energy, water, and pollutant exchanges between the surface and free atmosphere. However, there is no observationbased global PBL climatology for evaluation of climate, weather, and air quality models or for characterizing PBL variability on large space and time scales. As groundwork for such a climatology, we compute PBL height by seven methods, using temperature, potential temperature, virtual potential temperature, relative humidity, specific humidity, and refractivity profiles from a 10 year, 505-station radiosonde data set. Six methods are directly compared; they generally yield PBL height estimates that differ by several hundred meters. Relative humidity and potential temperature gradient methods consistently give higher PBL heights, whereas the parcel (or mixing height) method yields significantly lower heights that show larger and more consistent diurnal and seasonal variations (with lower nighttime and wintertime PBLs). Seasonal and diurnal patterns are sometimes associated with local climatological phenomena, such as nighttime radiation inversions, the trade inversion, and tropical convection and associated cloudiness. Surface-based temperature inversions are a distinct type of PBL that is more common at night and in the morning than during midday and afternoon, in polar regions than in the tropics, and in winter than other seasons. PBL height estimates are sensitive to the vertical resolution of radiosonde data; standard sounding data yield higher PBL heights than high-resolution data. Several sources of both parametric and structural uncertainty in climatological PBL height values are estimated statistically; each can introduce uncertainties of a few 100 m.

Sudden stratospheric warmings (SSWs) are large, rapid temperature rises in the winter polar stratosphere, occurring predominantly in the Northern Hemisphere. Major SSWs are also associated with a reversal of the climatological westerly zonal-mean zonal winds. Circulation anomalies associated with SSWs can descend into the troposphere with substantial surface weather impacts, such as wintertime extreme cold air outbreaks. After their discovery in 1952, SSWs were classified by the World Meteorological Organization. An examination of literature suggests that a single, original reference for an exact definition of SSWs is elusive, but in many references a definition involves the reversal of the meridional temperature gradient and, for major warmings, the reversal of the zonal circulation poleward of 60° latitude at 10 hPa. Though versions of this definition are still commonly used to detect SSWs, the details of the definition and its implementation remain ambiguous. In addition, other SSW definitions have been used in the last few decades, resulting in inconsistent classification of SSW events. We seek to answer the questions: How has the SSW definition changed, and how sensitive is the detection of SSWs to the definition used? For what kind of analysis is a “standard” definition useful? We argue that a standard SSW definition is necessary for maintaining a consistent and robust metric to assess polar stratospheric wintertime variability in climate models and other statistical applications. To provide a basis for, and to encourage participation in, a communitywide discussion currently underway, we explore what criteria are important for a standard definition and propose possible ways to update the definition.

[1] Although boundary layer processes are important in climate, weather and air quality, boundary layer climatology has received little attention, partly for lack of observational data sets. We analyze boundary layer climatology over Europe and the continental U.S. using a measure of boundary layer height based on the bulk Richardson number. Seasonal and diurnal variations during 1981-2005 are estimated from radiosonde observations, a reanalysis that assimilates observations, and two contemporary climate models that do not. Data limitations in vertical profiles introduce height uncertainties that can exceed 50% for shallow boundary layers (<1 km) but are generally <20% for deeper boundary layers. Climatological heights are typically <1 km during daytime and <0.5 km at night over both regions. Seasonal patterns for daytime and nighttime differ; daytime heights are larger in summer than winter, but nighttime heights are larger in winter. The four data sets show similar patterns of spatial and seasonal variability but with biases that vary spatially, seasonally, and diurnally. Compared with radiosonde observations, the reanalysis and the climate models produce deeper layers due to difficulty simulating stable conditions. The higher-time-resolution reanalysis reveals the diurnal cycle in height, with maxima in the afternoon, and with amplitudes that vary seasonally (larger in summer) and regionally (larger over western U.S. and southern Europe). The lower-time-resolution radiosonde data and climate model simulations capture diurnal variations better over Europe than over the U.S., due to differences in local sampling times.

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Abstract. Major, sudden midwinter stratospheric warmings (SSWs) are large and rapid temperature increases in the winter polar stratosphere are associated with a complete reversal of the climatological westerly winds (i.e., the polar vortex). These extreme events can have substantial impacts on winter surface climate, including increased frequency of cold air outbreaks over North America and Eurasia and anomalous warming over Greenland and eastern Canada. Here we present a SSW Compendium (SSWC), a new database that documents the evolution of the stratosphere, troposphere, and surface conditions 60 days prior to and after SSWs for the period 1958-2014. The SSWC comprises data from six different reanalysis products: MERRA2

An updated analysis of observed stratospheric temperature variability and trends is presented on the basis of satellite, radiosonde, and lidar observations. Satellite data include measurements from the series of NOAA operational instruments, including the Microwave Sounding Unit covering 1979-2007 and the Stratospheric Sounding Unit (SSU) covering 1979-2005. Radiosonde results are compared for six different data sets, incorporating a variety of homogeneity adjustments to account for changes in instrumentation and observational practices. Temperature changes in the lower stratosphere show cooling of ~0.5 K/decade over much of the globe for 1979-2007, with some differences in detail among the different radiosonde and satellite data sets. Substantially larger cooling trends are observed in the Antarctic lower stratosphere during spring and summer, in association with development of the Antarctic ozone hole. Trends in the lower stratosphere derived from radiosonde data are also analyzed, for a longer record (back to 1958); trends for the presatellite era (1958-1978) have a large range among the different homogenized data sets, implying large trend uncertainties. Trends in the middle and upper stratosphere have been derived from updated SSU data, taking into account changes in the SSU weighting functions due to observed atmospheric CO2 increases. The results show mean cooling of 0.5-1.5 K/decade during 1979-2005, with the greatest cooling in the upper stratosphere near 40-50 km. Temperature anomalies throughout the stratosphere were relatively constant during the decade 1995-2005. Long records of lidar temperature measurements at a few locations show reasonable agreement with SSU trends, although sampling uncertainties are large in the localized lidar measurements. Updated estimates of the solar cycle influence on stratospheric temperatures show a statistically significant signal in the tropics (~30°N-S), with an amplitude (solar maximum minus solar minimum) of ~0.5 K (lower stratosphere) to ~1.0 K (upper stratosphere)

26. We chose these values of the target factors to produce our final results because we have concluded that they are the most likely to be free of errors. They are calculated from oceanic observations to reduce errors from uncorrected diurnal variations, and we use unweighted MSU channel 2 data (T2 in SOM) to avoid additional noise due to the differencing procedure used to calculate TLT. The values of the intersatellite offsets needed to be recalculated to remove obvious intersatellite differences. In the supporting online material, we discuss the impact of using different data subsets to determine the target factors. This information is used to help determine the structural uncertainty. 27. We obtain this estimate of the tropical TLT trend when we recalculate the intersatellite offsets to optimize them for tropical data. If this reoptimization is not performed, as it is not in producing maps such as those shown in Fig. 3, we obtain a smaller trend value of 0. The month-to-month variability of tropical temperatures is larger in the troposphere than at Earth's surface. This amplification behavior is similar in a range of observations and climate model simulations and is consistent with basic theory. On multidecadal time scales, tropospheric amplification of surface warming is a robust feature of model simulations, but it occurs in only one observational data set. Other observations show weak, or even negative, amplification. These results suggest either that different physical mechanisms control amplification processes on monthly and decadal time scales, and models fail to capture such behavior; or (more plausibly) that residual errors in several observational data sets used here affect their representation of long-term trends.Tropospheric warming is a robust feature of climate model simulations that include historical increases in greenhouse gases (1-3). Maximum warming is predicted to occur in the middle and upper tropical troposphere. Atmospheric temperature measurements from radiosondes also show warming of the tropical troposphere since the early 1960s (4-7), consistent with model results (8). The observed tropical warming is partly due to a step-like change in the late 1970s (5, 6). Considerable attention has focused on the shorter record of satellite-based atmospheric temperature measurements (1979 to present). In both models and observations, the tropical surface warms over this period. Simulated surface warming is amplified in the tropical troposphere, corresponding to a decrease in lapse rate (2,3,9). In contrast, a number of radiosonde and satellite data sets suggest that the tropical troposphere has warmed less than the surface, or even cooled, which would correspond to an increase in lapse rate (4)(5)(6)(7)(8)(9)(10)(11)(12).This discrepancy may be an artifact of residual inhomogeneities in the observations (13)(14)(15)(16)(17)(18)(19). Creating homogeneous climate records requires the identification and removal of nonclimatic influences from data that were primarily collected for weather forecasting...