Time series of meteorological variables typically exhibit a pronounced annual cycle and persistence and samples are of finite size. This paper analyses the impact of these complicating features on certain statistics computed from the time series. The presence of an annual cycle means that statistics are nonstationary unless computed from multiyear samples of limited duration. Persistence leads to lack of independence of observations. Large amplitude weather (high frequency) events induce natural variability at low frequencies, known as climatic noise, that is enhanced by the presence of persistence. This natural variability should be, taken into account when estimating population statistics from a finite sample, but generally this has not been done in meteorology. A number of studies in meteorology have computed statistics from daily data by 1) removing the annual cycle; 2) computing second moment statistics over each individual season; and 3) averaging the second moment statistics over all years. This procedure fails to take into account the natural interannual variability that should be present and results in biased estimates of certain statistics. In particular, autocorrelations that lag are systematically negatively biased. It is shown for first order autoregressive (AR) time series that theautocorrelations computed in this way become negative after just a few days lag. Consequently, several studies have drawn doubtful conclusions about the stochastic character of meteorological time series, and a few reported results are questionable. A brief discussion of some papers adversely affected by the methodology is given. The effects of the statistical methodology are illustrated with simulated, and thus known, time series. It is shown that the best possible estimate of autocorrelations for stationary time series is obtained by subtraction of the mean of all available data, rather than subtracting a different mean for each subsample (season) in order to compute the anomalies. Appropriate methods for computing the statistics are discussed.
An analysis of variance approach is used to estimate the potential predictability of interannual fluctuations of the seasonal mean flow over the Southern Hemisphere. The potential predictability of the 1000 and 500 mb geopotential height fields for both summer and winter is assessed. Daily variances at 500 mb are roughly double those at 1000 mb, but otherwise the patterns are quite similar in both seasons. The level of climatic noise is estimated from the daily variances and compared with the actual interannual variances under a null hypothesis that no signal exists. Results reveal that interannual or longer-term variability clearly exceeds the noise level at both levels and in both seasons over Antarctica and in the tropics No clear statement can be made one way or the other in midlatitudes. The methodology appears to fail over the Australia-New Zealand region where clear interannual signals associated with the Southern Oscillation and a quasi-biennial oscillation have previously been found. However, the noise in this region appears to include the 40–50 day oscillation which may be organized by or systematically contribute to the interannual variability. The implied correlation between signal and noise voids a basic assumption of the methodology.
'The Asian monsoon: Global perspectives' published in 'The Asian Monsoon'
No abstract is provided for this article.
No abstract is provided for this article.
The Atlantic Meridional Overturning Circulation plays a major role in moving heat and carbon around in the ocean. A new estimate of ocean heat transports for 2000 through 2013 throughout the Atlantic is derived. Top‐of‐atmosphere radiation is combined with atmospheric reanalyses to estimate surface heat fluxes and combined with vertically integrated ocean heat content to estimate ocean heat transport divergence as a residual. Atlantic peak northward ocean heat transports average 1.18 ± 0.13 PW (1 sigma) at 15°N but vary considerably in latitude and time. Results agree well with observational estimates at 26.5°N from the RAPID array, but for 2004–2013 the meridional heat transport is 1.00 ± 0.11 PW versus 1.23 ± 0.11 PW for RAPID. In addition, these results have no hint of a trend, unlike the RAPID results. Strong westerlies north of a meridian drive ocean currents and an ocean heat loss into the atmosphere that is exacerbated by a decrease in ocean heat transport northward.
Kevin E. Trenberth emphasizes the fundamental role of energy flows in the climate system and anthropogenic climate change. The distribution of heat, or more generally, energy, is the main determinant of weather patterns in the atmosphere and their impacts. The topics addressed cover many facets of climate and the climate crisis. These include the diurnal cycle; the seasons; energy differences between the continents and the oceans, the poles and the tropics; interannual variability such as Niño; natural decadal variability; and ice ages. Human-induced climate change rides on and interacts with all of these natural phenomena, and the result is an unevenly warming planet and changing weather extremes. The book emphasizes the need to not only slow or stop climate change, but also to better prepare for it and build resilience. Students, researchers, and professionals from a wide range of backgrounds will benefit from this deeper understanding of climate change.
No abstract is provided for this article.
A new global 2°×2° monthly sea surface temperature (SST) climatology, primarily derived from a 1950–1979-based SST climatology from the Climate Analysis Center (CAC), is presented and described. The CAC climatology has been modified by using data from the Comprehensive Ocean-Atmosphere Data Set to improve the SST estimates in the regions of the Kuroshio and the Gulf Stream. This results in considerably larger and more realistic SST gradients in these regions. This modified climatology is smoothed in time using a truncated Fourier series to eliminate mean annual cycle fluctuations of three months or less, and finally, some spatial smoothing is applied over the high-latitude southern oceans. This new SST climatology, which we call the Shea-Trenberth-Reynolds (STR) climatology, is compared with the Alexander and Mobley (AM) SST climatology often used as a lower boundary condition by general circulation models. Significant differences are noted. Generally, the STR climatology is warmer in the Northern Hemisphere and in the subtropics of the Southern Hemisphere during the northern winter. It is often colder south of 45°S in all months. The largest differences are more than 5°C in the Kuroshio and Gulf Stream regions, and in the mid- to high-latitude southern oceans, the SSTs are often more than 2°C lower. In addition, the STR climatology is temporally and spatially less noisy than the AM SST climatology. Global SST anomalies spanning the period 1982 to 1990 are discussed. The largest anomalies are associated with the El Niño (1982–83 and 1986–87) and La Niña (1988) events in the tropical Pacific. However, because of differences in procedures in producing the 1982–1990 SSTs compared with the CAC climatology, the anomalies in certain regions are really compensating for deficiencies in the climatology and should not be interpreted as true climate anomalies.
No abstract is provided for this article.
I am delighted to be recognized with this prize. I want to first thank AGU and the prize committee and, especially, Nature's Own for establishing this prize in a field that has become contentious and highly political. It did not used to be this way. Following the media frenzy with the 2007 Intergovernmental Panel on Climate Change (IPCC) report, there was hope at the 2009 Conference of Parties meeting in Copenhagen that an international framework agreement on climate change might be achieved. It was not to be. Planned actions to address issues of climate change were undermined by huge funding of misinformation by vested interests. It was not helped by so‐called “climategate” in which many emails illegally hacked from a computer server at the University of East Anglia in the United Kingdom were released, cherry picked, distorted, and misused by climate change deniers. Minor errors in the IPCC report were blown out of all proportion and ineffectively addressed. I was caught up in all this, and one of my many emails went viral: the “travesty” quote in which I bemoaned the inability to close the global energy balance associated with short‐term climate variability but which was misinterpreted as saying there was no global warming. These examples highlight failures of communication.
Errors arising from the use of a sparse 63-station network in monitoring global and regional temperature changes are estimated by comparing results from a complete global data set from European Centre for Medium Range Forecasts analyses with those from the 63 gridpoints nearest the stations. For nine years of seasonal means, the correlations between the station network and the true values are generally quite high, but root-mean-square errors are also large outside of the tropics and are of the same order as the signal being sought. For the most part, this occurs because the variance of the 63-station network is too large so that although the overall low-frequency fluctuations are reasonably well depicted, their amplitude is too large. However, any missing data could greatly exacerbate errors arising from spatial sampling.
Global climate models used in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are examined for the top‐of‐atmosphere radiation changes as carbon dioxide and other greenhouse gases build up from 1950 to 2100. There is an increase in net radiation absorbed, but not in ways commonly assumed. While there is a large increase in the greenhouse effect from increasing greenhouse gases and water vapor (as a feedback), this is offset to a large degree by a decreasing greenhouse effect from reducing cloud cover and increasing radiative emissions from higher temperatures. Instead the main warming from an energy budget standpoint comes from increases in absorbed solar radiation that stem directly from the decreasing cloud amounts. These findings underscore the need to ascertain the credibility of the model changes, especially insofar as changes in clouds are concerned.
The central objectives of this work have been to explore and improve the depiction of precipitation and related processes in climate models by developing and analyzing observations and their gridded analyses, and developing new approaches and metrics. All three groups worked with the NCAR-based Community Earth System Model (CESM) and international community Climate Model Inter-comparison Project version 5 (CMIP5) models in various ways. At NCAR and SUNYA an initial focus was on the observational record, including updating of the river discharge dataset. A major focus at NCAR was extensive work on new datasets of hourly precipitation from CMORPH (observations) and CESM, and commentary on and validation of the CESM. SUNYA contributed to the comparison and evaluation of existing precipitation products widely used in climate research, the analysis of precipitation characteristics in CESM and other CMIP5 models, and decadal precipitation variability associated with decadal variability. At NCAR and SUNYA work was focused on the frequency and intensity of precipitation, including their dependence on the temporal and spatial resolution of the data used to calculate the frequency and intensity, as well as additional analyses on the effects of precipitation data uncertainties on the estimated historical drying trends. LLNL focused on the diurnal cycle. New insights have resulted in the characteristics of precipitation (frequency, intensity, amount, duration, diurnal cycle, covariability in space and time) and evaluation of these in models. In general models perform poorly and this provides a much-needed focus on what aspects of models are greatly in need of improvement. A substantial number of papers have now been published on these topics. The focus on the characteristics of precipitation and not just amount also provides a natural entrée into examining the extremes of precipitation, that are very important to the general public in terms of impacts. Examples are the deluges from Florence and Harvey, and extensive work has been performed on the latter. On the other side of the coin, considerable work has been performed on dry spells and drought, including improvements in a drought index. There has been considerable outreach to the general public, especially through the media, but also via talks and lectures, and a strong educational component at SUNYA. For example, the Harvey paper has an altimetrics rating of 827 and is the highest for any paper from that journal, it is at the 99th percentile of all papers of the same age, and is in the top 95 percent of all papers. The energy cycle and ocean heat content has been another focus. The entire atmospheric energy cycle has been reformulated and applied to the latest data to include effects from the enthalpy of precipitation. Relationships between ocean heat content and sea level rise have also been extensively explored in observations and models, with new insights into the role of Mount Pinatubo volcanic eruption on distorting and hiding the accelerating sea level rise. This work has been also widely featured in news media. The “year without a summer” has also been explored in the past using models, and how changes in the vertical structure and stability of the ocean with a warming climate may influence a future such volcanic event by amplifying the surface temperature response.
