Abstract

Total cloudiness of 29 models participating in the Atmospheric Model Intercomparison Project is compared with the ISCCP C2 as well as the Nimbus-7 and Meteor observational estimates. The root-mean-square differences between the annual means of the model calculations and the C2 observations after global means are removed vary from about twice to nearly four times the difference between the C2 and Meteor observations. The large differences are in some cases due to the fact that although a model qualitatively has patterns of spatial variations similar to those of the observations, the magnitude of those variations is much too small. In other cases the models have produced the approximate magnitude of the spatial variability of the observations but display sizable errors in the pattern of that variability.

Deficiencies with respect to the model simulations of the mean seasonal cycle are also pronounced. For instance, the differences between the zonal averages of total cloudiness for contrasting seasons suggest that near 60° most models predict minima in cloudiness in summer, whereas observations strongly suggest the opposite. In addition, smoothed seasonal cycle analyses suggest that a portion of these deficiencies in some models is the result of a simulated seasonal cycle that leads that of the observations by about two months. However, some models, which appear to have the proper phase of the seasonal cycle, still show large root-mean-square differences and small correlations when compared with the smoothed seasonal cycle of the C2 observations. The C2 and Meteor observations show a modest signal in total cloudiness for the only important interannual variation during the July 1983 through June 1988 observation period—the 1986/87 ENSO event. A few models reproduce this event about as well as do the Meteor observations, whereas many models fail to show any evidence of it.

Overall, models that better reproduce the ENSO results also tend to do well with seasonal variations. No specific differences are evident in the physical characteristics of models that are relatively adept at reproducing seasonal and interannual variations and those that perform more poorly. However, there is the general conclusion that models that have more sophisticated physical processes tend to better simulate the cloud observations.

Abstract

Significant changes and a general redistribution in the frequencies of various cloud types have been observed during the past 40–50 years over the midlatitude land areas of the Northern Hemisphere. This is evident for North America and northern Eurasia in the daytime synoptic data of the United States and the former Soviet Union (FUSSR). An abrupt increase prior to the 1960s largely contributed to the upward trend in the frequency of convective clouds over both regions, particularly in the warm season. However, over both regions during the intermediate seasons and during the winter season over the FUSSR, the frequencies of convective clouds still showed gradual increase after the 1960s. The increase in the frequency of convective clouds has been accompanied by increases in the frequency of observation of high-level cloudiness (at elevations above 6 km) and heavy precipitation. Low cloudiness (stratiform types) has decreased over the FUSSR but increased over the contiguous United States. The latter increase was due to an increase in the frequency of stratocumulus clouds, while the frequency of stratus clouds has decreased. Generally, it appears that during the post-World War II period over the FUSSR high cloud-type frequencies increased and low cloudiness decreased with a relatively small change (increase) in total cloud cover, while over the United States cloud cover has increased at both low and high levels. The analyses of cloudiness information from the United States and the FUSSR reveal noticeable differences in definitions and observational practices that affect the estimates of climatology and interpretation of the results presented here in terms of changes of convective activity and its relation to precipitation in these two regions of Eurasia and North America.

Abstract

This paper presents an extension of the recently developed method for simultaneous dimension reduction and metastability analysis of high-dimensional time series. The modified approach is based on a combination of ensembles of hidden Markov models (HMMs) with state-specific principal component analysis (PCA) in extended space (guaranteeing that the overall dynamics will be Markovian). The main advantage of the modified method is its ability to deal with the gaps in the high-dimensional observation data. The proposed method allows for (i) the separation of the data according to the metastable states, (ii) a hierarchical decomposition of these sets into metastable substates, and (iii) calculation of the state-specific extended empirical orthogonal functions simultaneously with identification of the underlying Markovian dynamics switching between those metastable substates. The authors discuss the introduced model assumptions, explain how the quality of the resulting reduced representation can be assessed, and show what kind of additional insight into the underlying dynamics such a reduced Markovian representation can give (e.g., in the form of transition probabilities, statistical weights, mean first exit times, and mean first passage times). The performance of the new method analyzing 500-hPa geopotential height fields [daily mean values from the 40-yr ECMWF Re-Analysis (ERA-40) dataset for a period of 44 winters] is demonstrated and the results are compared with information gained from a numerically expensive but assumption-free method (Wavelets–PCA), and the identified metastable states are interpreted w.r.t. the blocking events in the atmosphere.

Abstract

A 30-yr climatology of blocking events was compiled by stratifying the data into seasonal and three regional categories for both the Northern and Southern Hemispheres using the NCEP–NCAR reanalyses. Several characteristics of blocking anticyclones were included in the study and these were frequency of occurrence, preferred formation regions, duration, blocking days, and intensity. The block intensity (BI) calculation was modified successfully from a previous study in order to automate the procedure for use with large datasets, and it is applied for the first time to derive a long-term observational record of this quantity. This modification also makes BI suitable for use as a diagnostic tool. Blocking events in the Northern (Southern) Hemisphere were the most persistent and strongest during the cold season and over the Atlantic (Pacific) region, as found using BI to measure intensity.

The characteristics of blocking events derived in this study were compared to previous long-term climatological studies and across each hemisphere. It was found that the temporal and spatial distributions in both hemispheres were similar to those of longer-term studies. The interannual variability of blocking was also examined with respect to ENSO-related variability for the entire blocking year. It was found that Northern (Southern) Hemisphere blocking events were stronger and more frequent during La Niña (El Niño) years, a result that is consistent with cyclone variability in each hemisphere. Additionally, these results were compared with previously published studies of interannual variability in blocking occurrence.

Abstract

A long-term climatology of cloudiness over the Norwegian, Barents, and Kara Seas (NBK) based on visual surface observations is presented. Annual mean total cloud cover (TCC) is almost equal over solid-ice (SI) and open-water (OW) regions of the NBK (73% ± 3% and 76% ± 2%, respectively). In general, TCC has higher intra- and interannual variability over SI than over OW. A decrease of TCC in the middle of the twentieth century and an increase in the last few decades was found at individual stations and for the NBK as a whole. In most cases these changes are statistically significant with magnitudes exceeding the data uncertainty that is associated with the surface observations. The most pronounced trends are observed in autumn when the largest changes to the sea ice concentration (SIC) occur. TCC over SI correlates significantly with SIC in the Barents Sea, with a statistically significant correlation coefficient between annual TCC and SIC of −0.38 for the period 1936–2013. Cloudiness over OW shows nonsignificant correlation with SIC. An overall increase in the frequency of broken and scattered cloud conditions and a decrease in the frequency of overcast and cloudless conditions were found over OW. These changes are statistically significant and likely to be connected with the long-term changes of morphological types (an increase of convective and a decrease of stratiform cloud amounts).

The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.

Abstract

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. Most EMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6–6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO₂ emissions after 2300 results in slowly decreasing atmospheric CO₂ concentrations. At year 3000 atmospheric CO₂ is still at more than half its year-2300 level in all EMICs for RCPs 4.5–8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination of CO₂ emissions in all EMICs. Restoration of atmospheric CO₂ from RCP to preindustrial levels over 100–1000 years requires large artificial removal of CO₂ from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO₂.