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No abstract is provided for this article.

The co‐variability of monthly mean surface temperature and precipitation is determined globally for 1979–2002 from observationally‐based analyses (ERA‐40) for surface air temperature and the Global Precipitation Climatology Project (GPCP) version 2 for precipitation and compared with results from the NCAR Community Atmospheric Model version 3 (CAM3) and Community Climate System Model version 3 (CCSM3). Results are combined for the 5 months for northern winter (November to March) and summer (May to September). Over land, negative correlations dominate, as dry conditions favor more sunshine and less evaporative cooling, while wet summers are cool. At high latitudes in winter, positive correlations dominate as warm moist advection in extratropical cyclones favors precipitation and the water holding capacity of the atmosphere limits precipitation amounts in cold conditions. Where ocean conditions drive the atmosphere, higher surface air temperatures are associated with precipitation, as in El Niño, but some areas, such as the western Pacific in northern summer, feature negative correlations indicating that the atmosphere determines the surface temperatures. In the CAM driven with observed sea surface temperatures and the CCSM in fully coupled mode the latter mechanism is largely absent, and correlations are generally much stronger than observed, indicating more local control. Neither temperature nor precipitation records should be interpreted without considering the strong covariability that exists.

Analysis of global surface air temperature records has indicated that recent years have been among the warmest since the late nineteenth century1, with 1995 being the warmest year on record2. But the rate of global annual mean surface warming of 0.13 °C per decade during the period 1979–95 differs substantially from the global lower-tropospheric cooling trend of – 0.05 °C per decade3 Inferred from the record (MSU-2R) of radiance measurements by the satellite Microwave Sounder Unit (MSU)4,5. Accordingly, the satellite record has been widely cited by sceptics as evidence against global warming6–10. However, a substantial fraction of the measured radiance originates not from the atmosphere but from the Earth's surface11, and gives rise to high noise levels. This noise can lead to errors when merging temperature time series obtained from different satellites. Here we present comparisons among different MSU retrievals, sea surface temperatures (SSTs), and equivalent MSU temperatures derived from an atmospheric general circulation model forced with observed SSTs. The comparisons, focused on the tropics where atmospheric temperatures are closely tied to SSTs, strongly suggest that two spurious downward jumps occur in the MSU-2R record coinciding with changes in satellites, and that the real trend in MSU temperatures is likely to be positive, albeit small.

A comprehensive comparison is made between two tropospheric temperature datasets over the period 1979–98: the most recent and substantially revised (version d) microwave sounding unit (MSU) channel 2 data retrievals, and a gridded radiosonde analysis provided by the Hadley Centre of the U.K. Meteorological Office. The latter is vertically weighted to approximate the deep layer temperatures measured by the satellite data. At individual grid points, there is good overall agreement among monthly anomalies, especially over the Northern Hemisphere continents where the climate signal is large, although monthly root-mean-square (rms) differences typically exceed 0.6°C. Over the Tropics, correlations are lower and rms differences can be as large as the standard deviations of monthly anomalies. Differences in the gridpoint variances are significant at many locations, which presumably reflects sources of noise in one or both measurement systems. It is often argued for climate purposes that temperature anomalies are large in scale so that averaging over larger areas better serves to define the anomalies while reducing sampling error. This is the case for the Tropics (20°S–20°N) where the large signal associated with El Niño-Southern Oscillation events is well captured in both datasets. Over the extratropics, however, the results indicate that it is essential to subsample the satellite data with the radiosonde coverage in both space and time in any evaluation. For collocated global average monthly anomalies, correlations are ~0.9 with rms differences ~0.10°C for both lower- (MSU2LT) and mid- (MSU2) tropospheric anomalies. The agreement between the satellite and radiosonde data is slightly better for the latest version of MSU2LT than it is for MSU2, in spite of the higher noise levels of the former. This is primarily attributable to a strong warming trend in the MSU2, data relative to the radiosonde data toward the end of the record. Given the global nature of this discrepancy, it is suspected that it primarily reflects problems in the MSU analysis. As radiosonde records almost universally contain temporal inhomogeneities as well, caution is required when interpreting trends, which are not known to within 0.1 °C decade−1. However, the evidence suggests that global surface air temperatures are indeed warming at a significantly faster rate than tropospheric temperatures over the past 20 yr, and this is primarily attributable to physical differences in these two quantities.

Ocean meridional heat transports (MHTs) are deduced as a residual using energy budgets to produce latitude versus time series for the globe, Indo-Pacific, and Atlantic. The top-of-atmosphere (TOA) radiation is combined with the vertically integrated atmospheric energy divergence from atmospheric reanalyses to produce the net surface energy fluxes everywhere. The latter is then combined with estimates of the vertically integrated ocean heat content (OHC) tendency to produce estimates of the ocean heat divergence. Because seasonal sea ice and land runoff effects are not fully considered, the mean annual cycle is incomplete, but those effects are small for interannual variability. However, there is a mismatch between 12-month inferred surface flux and the corresponding OHC changes globally, requiring adjustments to account for the Earth’s global energy imbalance. Estimates are greatly improved by building in the constraint that MHT must go to zero at the northern and southern extents of the ocean basin at all times, enabling biases between the TOA and OHC data to be reconciled. Zonal mean global, Indo-Pacific, and Atlantic basin ocean MHTs are computed and presented as 12-month running means and for the mean annual cycle for 2000–16. For the Indo-Pacific, the tropical and subtropical MHTs feature a strong relationship with El Niño–Southern Oscillation (ENSO), and in the Atlantic, MHT interannual variability is significantly affected by and likely influences the North Atlantic Oscillation (NAO). However, Atlantic and Pacific changes are linked, suggesting that the northern annular mode (as opposed to NAO) is predominant. There is also evidence of decadal variability or trends.

Changes in the average net radiation at the top of the atmosphere due to perturbations in the incident solar radiation from the changes internal to the Sun or from changes in the orbit of Earth around the Sun lead to a change in heating, and climate change. There is no doubt about this physically, but the question is how large are these fluctuations?

No abstract is provided for this article.

Progress toward understanding the causes of and physical mechanisms involved in the 1988 North American drought is reported. An earlier study demonstrated that major sea surface temperature (SST) anomalies in the tropical Pacific Ocean, in association with the 1988 La Niña, may have disrupted atmospheric heating patterns by changing the location and intensity of the intertropical convergence zone and that such heating anomalies could have initiated the circulation anomalies across North America responsible for the drought. A key issue of when the drought circulation anomalies developed and their relation to changes in tropical Pacific SSTs is examined. Although unusually dry soil moisture and heat waves persisted into August, the anomalous atmospheric conditions that brought on the drought occurred in April, May, and June of 1988. The evolution of the Pacific SSTs and tropical convection, as revealed by outgoing longwave radiation, is shown to be consistent with the development of the conditions favorable for initiating the drought circulation pattern in April through June of 1988. On the equator at 110°W, SST anomalies exceeded −2.75°C in only April, May, and June and were largest (−4.1°C) in May 1988. The issues of how the 1988 La Niña differed from those in the past and the importance of the whole SST field in determining the anomalous diabatic heating are also discussed. Diagnostic calculations of atmospheric diabatic heating confirm that atmospheric heating anomalies existed in the tropical Pacific in association with the major SST anomalies during this time. The link between the anomalous heating and the tropical SSTs supports the view that influences external to the atmosphere were important and that the drought was not generated solely by mechanisms internal to the atmosphere. The distribution of diagnosed heating anomalies over North America, together with a planetary wave model response to idealized forcing, is described to clarify the possible role of soil moisture anomalies in perpetuating the drought. It is argued that feedback-caused soil moisture anomalies may have been secondary sources for the drought circulation but could not have been the primary instigator. For the most part, other diagnosed heating anomalies during the drought are found to have little influence on the North American region. Criteria to help judge the ability of general circulation models to simulate the drought are discussed.

The variability of zonally resolved tropical energy budgets in association with El Niño–Southern Oscillation (ENSO) is investigated. The most recent global atmospheric reanalyses from 1979 to 2011 are employed with removal of apparent discontinuities to obtain best possible temporal homogeneity. The growing length of record allows a more robust analysis of characteristic patterns of variability with cross-correlation, composite, and EOF methods. A quadrupole anomaly pattern is found in the vertically integrated energy divergence associated with ENSO, with centers over the Indian Ocean, the Indo-Pacific warm pool, the eastern equatorial Pacific, and the Atlantic. The smooth transition, particularly of the main maxima of latent and dry static energy divergence, from the western to the eastern Pacific is found to require at least two EOFs to be adequately described. The canonical El Niño pattern (EOF-1) and a transition pattern (EOF-2; referred to as El Niño Modoki by some authors) form remarkably coherent ENSO-related anomaly structures of the tropical energy budget not only over the Pacific but throughout the tropics. As latent and dry static energy divergences show strong mutual cancellation, variability of total energy divergence is smaller and more tightly coupled to local sea surface temperature (SST) anomalies and is mainly related to the ocean heat discharge and recharge during ENSO peak phases. The complexity of the structures throughout the tropics and their evolution during ENSO events along with their interactions with the annual cycle have often not been adequately accounted for; in particular, the El Niño Modoki mode is but part of the overall evolutionary patterns.

No abstract is provided for this article.

Issues relevant to achieving an accuracy of better than 10 W m−2 on 250-km scales for monthly means in the atmospheric energy balance are explored from the standpoint of the formulation and computational procedures using the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR, hereafter referred to as NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses. The focus is on the vertically integrated energy components, their monthly tendencies, transports, and divergences, using the most accurate computations in model and pressure coordinates. Approximate equations have often been used previously; although relatively small compared with the moist static energy, kinetic energy transports should be taken into account, as divergences can exceed several tens of watts per square meter. Changes in energy storage terms over a month are not negligible, as they are typically over 25 W m−2 in storm track regions. Transports of energy are meaningful only if the mass budget is closed. Typical magnitudes of the divergence of sensible heat and potential energy are very large (several hundred watts per square meter), but partly cancel when combined as dry static energy, reflecting the role of isentropic flow. The latent energy and sensible heat contributions are strongly positively correlated because of the dominance of low-level flow, and the latent energy divergence also cancels a large component of the dry static energy divergence, leaving a modest residual. This arises from the dominance of moist adiabatic processes in the Tropics and subtropics as the net divergent transports depend on temperature departures in the vertical from the saturated adiabatic lapse rate and their covariability with wind. Careful numerical treatments are required or else small errors in the large terms that should cancel can be amplified. Common assumptions that diagnostics can be computed on model terrain-following coordinates, which therefore vary from day to day as the surface pressure changes, lead to errors in energy budgets of the order of 5 W m−2 owing to the covariability of energy terms with surface pressure. How well model coordinate results can be replicated in pressure coordinates has been explored along with the role of vertical resolution using a postprocessor developed at NCAR. The standard 17-level reanalysis pressure level archive does not adequately resolve the atmosphere, and we propose a new set of 30 pressure levels that has 25-mb vertical resolution below 700 mb and 50-mb vertical resolution in the rest of the troposphere. The diagnostics reveal major problems in the NCEP reanalyses in the stratosphere that are inherent in the model formulation, making them unsuitable for quantitative use for energetics in anything other than model coordinates. In addition, small flaws are found in the ECMWF postprocessing onto pressure levels. These stem from the way the vector fields are truncated, which is a necessary step to avoid aliasing before putting the values out on a 2.5° grid. Moreover, it is desirable to compute the gridpoint values exactly rather than interpolating them from the Gaussian grid, as currently done by ECMWF. The diagnostic results computed with 30 levels replicate the full model level vertically integrated energy divergences to within about 2 W m−2 over the ocean, while errors exceed 10 W m−2 in small spots over Greenland, Antarctica, and the Himalayan–Tibetan Plateau complex.

A review is given of the trends, variability, mean and annual cycle of energy flowing through the climate system, and its storage, release, and transport in the atmosphere, ocean, and land surface as estimated with recent observations, with some new updates using the latest datasets. The current imbalance in radiation at the top-of-atmosphere owing to human-induced increases in greenhouse gases means that the atmosphere, land and ocean are warming up, and ice is melting, leading to a rise in sea level. A discussion is given of our ability to track these changes with current observations and analyses. Current global analyses of the atmosphere and the ocean contain spurious variability on decadal time scales that arises from inadequacies and changes in the observing system. A holistic integrated approach that brings all information to bear can provide constraints on what is happening and where the main weaknesses are in the observing system. Results for ocean heat content are discussed in the light of recent corrections to ocean soundings and new ocean observations, and in the context of the thermosteric contributions to sea level rise.

Climate projections point toward more frequent and intense weather and climate extremes such as heat waves, droughts, and floods, in a warmer climate. These projections, together with recent extreme climate events, including flooding in Pakistan and the heat wave and wildfires in Russia, highlight the need for improved risk assessments to help decision makers and the public. But accurate analysis and prediction of risk of extreme climate events require new methodologies and information from diverse disciplines. A recent workshop sponsored by the World Climate Research Programme (WCRP) and hosted at United Nations Educational, Scientific and Cultural Organization (UNESCO) headquarters in France brought together, for the first time, a unique mix of climatologists, statisticians, meteorologists, oceanographers, social scientists, and risk managers (such as those from insurance companies) who sought ways to improve scientists' ability to characterize and predict climate extremes in a changing climate.