ABSTRACT:The observed warming of the surface air temperature (SAT) over the last 50 years has not been homogenous. There are strong differences in the temperature changes both geographically and on different time frames. Here, we review the observed diurnal asymmetry in the global warming trend: the night-time temperatures have increased more rapidly than day-time temperatures. Several explanations for this asymmetric warming have been offered in the literature. These generally relate differences in the temperature trends to regionalized feedback effects, such as changes to cloud cover, precipitation or soil moisture. Here, we discuss a complementary mechanism through which the planetary boundary layer (PBL) modulates the SAT response to changes in the surface energy balance. This reciprocal relationship between boundary-layer depth and temperature response can explain a part of why the night-time has warmed more rapidly than the daytime. We used a multi-linear regression model to compare the effect of the PBL, cloud cover, precipitation and soil moisture on the SAT. From this, we demonstrate that it is the boundary-layer depth which is the strongest predictor of the strength of temperature trends in the boreal annual cycle, and in all seasons except the summer.

Over the past 60 years, both average daily precipitation intensity and extreme precipitation have increased in many regions 1-3 . Part of these changes, or even individual events 4,5 , have been attributed to anthropogenic warming 6,7 . Over the Black Sea and Mediterranean region, the potential for extreme summertime convective precipitation has grown 8 alongside substantial sea surface temperature increase. A particularly devastating convective event experienced in that region was the July 2012 precipitation extreme near the Black Sea town of Krymsk 9 . Here we study the e ect of sea surface temperature (SST) increase on convective extremes within the region, taking the Krymsk event as a showcase example. We carry out ensemble sensitivity simulations with a convection-permitting atmospheric model and show the crucial role of SST increase in the extremeness of the event. The enhancement of lower tropospheric instability due to the current warmer Black Sea allows deep convection to be triggered, increasing simulated precipitation by more than 300% relative to simulations with SSTs characteristic of the early 1980s. A highly nonlinear precipitation response to incremental SST increase suggests that the Black Sea has exceeded a regional threshold for the intensification of convective extremes. The physical mechanism we identify indicates that Black Sea and Mediterranean coastal regions may face abrupt amplifications of convective precipitation under continued SST increase, and illustrates the limitations of thermodynamical bounds for estimating the temperature scaling of convective extremes.Extreme precipitation responds sensitively to both dynamical and thermodynamical forcings 10-12 . Changes in precipitation extremes can occur owing to changes in evaporation, the increased saturation vapour pressure in a warmer climate 13 , and changes in storm dynamics 12 . Global climate models project increased heavy precipitation, mainly over the tropics and high latitudes 14,15 . As temperature increases, large-scale precipitation extremes tend to scale at about 7% K −1 , along the thermodynamical bounds given by the Clausius-Clapeyron (CC) relation 3 . Convective extremes, however, are strongly influenced by mesoscale dynamics and may scale well above the CC rate 10,11 . Local factors, such as orography and moisture availability, can also impact the convective response to temperature increase.The Krymsk precipitation extreme saw a daily precipitation total that exceeded all previous annual daily maxima since 1936 by a factor of two (Fig. 1a), and a flash flood that killed over 170 people 9 . On the basis of statistical evidence from the pre-2012 record,

During the summer of 2010, an unusually persistent blocking episode resulted in anomalously warm dry weather over the European part of Russia. The excessive heat resulted in forest and peat fires, impacted terrestrial ecosystems, greatly increased pollution in urban areas, and increased mortality rates in the region. Using the National Centers for Atmospheric Research (NCAR), National Centers for Environmental Prediction (NCEP) reanalysis datasets, the climatological and dynamic character of blocking events for summer 2010 and a precursor May blocking event were examined. We found that these events were stronger and longer lived than typical warm season events. Using dynamic methods, we demonstrate that the July 2010 event was a synoptic-scale dominant blocking event; unusual in the summer season. An analysis of phase diagrams demonstrated that the planetary-scale did not become stable until almost one week after block onset. For all other blocking events studied here and previously, the planetary-scale became stable around onset. Analysis using area integrated regional enstrophy (IRE) demonstrated that for the July 2010 event, synoptic-scale IRE increased at block onset. This was similar for the May 2010 event, but different from case studies examined previously that demonstrated the planetary-scale IRE was prominent at block onset.

Total cloud fraction over the Arctic (north of 60 • N) has been evaluated and intercompared based on 16 Arctic cloud climatologies from different satellite and surface observations and reanalyses. The Arctic annual-mean total cloud fraction is about 0.70 ± 0.03 according to different observational data. It is greater over the ocean (0.74 ± 0.04) and less over land (0.67 ± 0.03). Different observations for total cloud fraction are in a better agreement in summer than in winter and over the ocean than over land. An interannual variability is higher in winter than in summer according to all observations. The Arctic total cloud fraction has a prominent annual cycle according to most of the observations. The time of its maximum concurs with the time of the sea ice extent minimum (early summer-late autumn) and vice versa (late spring). The main reason for the discrepancies among observations is the difference in the cloud-detection algorithms, especially when clouds are detected over the ice/snow surface (during the whole year) or over the regions with the presence of strong low-tropospheric temperature inversions (mostly in winter). Generally, reanalyses are not in a close agreement with satellite and surface observations of cloudiness in the Arctic.

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