Monthly mean global satellite data sets available in CCM history tape format

Satellite data for climate monitoring have become increasingly important over the past decade, especially with increasing concern for inadvertent antropogenic climate change. Although most satellite based data are of short record, satellites can provide the global coverage that traditional meteorological observations network lack. In addition, satellite data are invaluable for the validation of climate models, and they are useful for many diagnostic studies. Herein, several satellite data sets were processed and transposed into 'history tape' format for use with the Community Climate Model (CCM) modular processor. Only a few of the most widely used and best documented data sets were selected at this point, although future work will expand the number of data sets examined as well as update the archived data sets. An attempt was made to include data of longer record and only monthly averaged data were processed. For studies using satellite data over an extended period, it is important to recognize the impact of changes in instrumentation, drift in instrument calibration, errors introduced by retrieval algorithms and other sources of errors such as those resulting from insufficient space and/or time sampling

Decadel climate prediction: challenges and opportunities

Abstract. The scientific understanding of climate change is now sufficiently clear to show that climate change from global warming is already upon us, and the rate of change as projected exceeds anything seen in nature in the past 10,000 years. Uncertainties remain, however, especially regarding how climate will change at regional and local scales where the signal of natural variability is large. Addressing many of these uncertainties will require a movement toward high resolution climate system predictions, with a blurring of the distinction between shorter-term predictions and longer-term climate projections. The key is the realization that climate system predictions, regardless of timescale, will require initialization of coupled general circulation models with best estimates of the current observed state of the atmosphere, oceans, cryosphere, and land surface. Formidable challenges exist: for instance, what is the best method of initialization given imperfect observations and systematic errors in models? What effect does initialization have on climate predictions? What predictions should be attempted, and how would they be verified? Despite such challenges, the unrealized predictability that resides in slowly evolving phenomena, such as ocean current systems, is of paramount importance for society to plan and adapt for the next few decades. Moreover, initialized climate predictions will require stronger collaboration with shared knowledge, infrastructure and technical capabilities among those in the weather and climate prediction communities. The potential benefits include improved understanding and predictions on all time scales Introduction The Earth's climate is changing, and detection and attribution studies consistently find an anthropogenic signal in the climate record of at least the last half-century. Human activities are rapidly changing the composition of the atmosphere through the burning of fossil fuels and changes in land use, such as those associated with agriculture and deforestation. Many recent observed changes in climate are broadly consistent with increased radiative heating at the Earth's surface. These include (1) an increase in the globally averaged surface temperature of 0.75°C over the past century, including warming of 0.17ºC per decade since 1979; (2) the rapid melting of glaciers in nonpolar regions around the world; (3) dramatic decreases in the areal coverag

Tropical Origins for Recent North Atlantic Climate Change

Evidence is presented that North Atlantic climate change since 1950 is linked to a progressive warming of tropical sea surface temperatures, especially over the Indian and Pacific Oceans. The ocean changes alter the pattern and magnitude of tropical rainfall and atmospheric heating, the atmospheric response to which includes the spatial structure of the North Atlantic Oscillation (NAO). The slow, tropical ocean warming has thus forced a commensurate trend toward one extreme phase of the NAO during the past half-century

Two Time Scales for The Price Of One (Almost)

Although differences exist between seasonal- and decadal-scale climate variability, predictability, and prediction, investment in observations, prediction systems, and decision systems for either time scale can benefit both

Dynamics and energetics of the South Pacific Convergence Zone during FGGE SOP-1 and South Pacific Convergence Zone and global-scale

Significant accomplishments (papers published, conference presentations, and education degrees) are presented. The focus of the current research is outlined. Plans for the coming year are discussed briefly

Indicator patterns of forced change learned by an artificial neural network

Many problems in climate science require the identification of signals obscured by both the "noise" of internal climate variability and differences across models. Following previous work, we train an artificial neural network (ANN) to identify the year of input maps of temperature and precipitation from forced climate model simulations. This prediction task requires the ANN to learn forced patterns of change amidst a background of climate noise and model differences. We then apply a neural network visualization technique (layerwise relevance propagation) to visualize the spatial patterns that lead the ANN to successfully predict the year. These spatial patterns thus serve as "reliable indicators" of the forced change. The architecture of the ANN is chosen such that these indicators vary in time, thus capturing the evolving nature of regional signals of change. Results are compared to those of more standard approaches like signal-to-noise ratios and multi-linear regression in order to gain intuition about the reliable indicators identified by the ANN. We then apply an additional visualization tool (backward optimization) to highlight where disagreements in simulated and observed patterns of change are most important for the prediction of the year. This work demonstrates that ANNs and their visualization tools make a powerful pair for extracting climate patterns of forced change.Comment: The first version of this manuscript has been submitted to the Journal of Advances in Modeling Earth Systems (JAMES), 202

A modulation of the mechanism of the semiannual oscillation in the Southern Hemisphere.

ABSTRACT The local pressure changes associated with the twice-annual contraction/intensification and expansion/weakening of the circumpolar trough of low pressure around Antarctica, termed the semiannual oscillation (SAO), was the dominant signal in the annual cycle at mid and high southern latitudes before 1979. The mechanism, as shown by Van Loon (1967), arises from different response to the surface heat budget over the polar continent and the midlatitude ocean. It has subsequently been shown that in most years since 1979 the SAO has weakened considerably. Evidence is presented here from surface temperature data, 500 mb temperatures from a station pair and zonal mean 500 mb temperatures from the NCAR/NCEP reanalyses to show that a warming trend since 1979 has not been evenly distributed through the year at each latitude. Thus an anomalous change in the temperature gradient between 50°S and 65°S, with peaks in roughly May and November, has modulated the mechanism that produces the SAO, with its peaks in March and September. Consequently, the magnitude of the SAO has decreased in the more recent period

Relationship Between Intraseasonal Oscillation and Subtropical Wind Maxima Over the South Pacific Ocean

The significance of tropical heat sources on higher latitude jet streams has been examined by numerous investigators. Hurrell and Vincent (1990) provide a summary of many of these investigations in their observational case study of the relationship between tropical heating and subtropical wind maxima in the Southern Hemisphere during SOP-1, FGGE. They showed that the divergent outflow from tropical heating associated with the South Pacific Convergence Zone (SPCZ), acted on by the coriolis force, was an important factor in maintaining the subtropical jet on the poleward side of the SPCZ during the period, 6-20 January 1979. They found a similar, but weaker relationship, over the southern Indian Ocean from 3-17 February 1979, a period when the SPCZ heating was greatly reduced and the jet was essentially non-existent. Since their findings were based on a case study and involved the use of the highly-specialized FGGE data set, the natural questions which arose were: (1) Is this relationship a regular feature of the circulation over the South Pacific? and, (2) If so, can it be detected with a routine data set? Another question posed by Hurrell and Vincent in their papers was:(3) How important was the intraseasonal oscillation in causing the enhanced heating and divergent outflow in the Pacific Ocean in January and southern Indian Ocean in February? The purpose of the present paper is to address the answer to these three questions. To accomplish this, some circulation features for an entire warm season in the Southern Hemisphere were examined. The year selected was 1984-85, and the warm season consisted of the 6-month period, 1 November 1984 - 30 April 1985. This period was chosen because there were numerous cases of the westerly wind maxima over the South Pacific and the intraseasonal oscillation was well documented

Variability of the Atlantic meridional overturning circulation in CCSM4

Author Posting. © American Meteorological Society, 2012. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 25 (2012): 5153–5172, doi:10.1175/JCLI-D-11-00463.1.Atlantic meridional overturning circulation (AMOC) variability is documented in the Community Climate System Model, version 4 (CCSM4) preindustrial control simulation that uses nominal 1° horizontal resolution in all its components. AMOC shows a broad spectrum of low-frequency variability covering the 50–200-yr range, contrasting sharply with the multidecadal variability seen in the T85 × 1 resolution CCSM3 present-day control simulation. Furthermore, the amplitude of variability is much reduced in CCSM4 compared to that of CCSM3. Similarities as well as differences in AMOC variability mechanisms between CCSM3 and CCSM4 are discussed. As in CCSM3, the CCSM4 AMOC variability is primarily driven by the positive density anomalies at the Labrador Sea (LS) deep-water formation site, peaking 2 yr prior to an AMOC maximum. All processes, including parameterized mesoscale and submesoscale eddies, play a role in the creation of salinity anomalies that dominate these density anomalies. High Nordic Sea densities do not necessarily lead to increased overflow transports because the overflow physics is governed by source and interior region density differences. Increased overflow transports do not lead to a higher AMOC either but instead appear to be a precursor to lower AMOC transports through enhanced stratification in LS. This has important implications for decadal prediction studies. The North Atlantic Oscillation (NAO) is significantly correlated with the positive boundary layer depth and density anomalies prior to an AMOC maximum. This suggests a role for NAO through setting the surface flux anomalies in LS and affecting the subpolar gyre circulation strength.The CCSM project is supported by NSF and the Office of Science (BER) of the U.S. Department of Energy. SGY and YOK were supported by the NOAA Climate Program Office under Climate Variability and Predictability Program Grants NA09OAR4310163 and NA10OAR4310202, respectively.2013-02-0