Amato T. Evan

Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000

million km 2 of cropland (12% of the Earth’s ice-free land surface) and 28.0 (90% confidence range of 23.6–30.0) million km 2 of pasture (22%) in the year 2000.

The Role of Aerosols in the Evolution of Tropical North Atlantic Ocean Temperature Anomalies

Dust in the Wind The temperature of North Atlantic surface waters has a major effect on climate in a variety of ways, not least because its heat content helps to control hurricane formation and strength. The North Atlantic surface has warmed considerably in recent decades, a trend generally associated with global or regional air temperature increases, or with changes in ocean circulation. Evan et al. (p. 778, published online 26 March) use nearly 30 years of satellite data to examine another source of ocean temperature variability, the radiative effects of atmospheric aerosols. Low frequency changes in local tropical North Atlantic surface temperatures seem mostly to be caused by variability in mineral and stratospheric aerosol abundances. Thus, to provide more accurate projections of these temperatures, general circulation models will need to account for long-term changes in dust loadings. Changes in tropical North Atlantic sea surface temperatures are caused by variability in atmospheric aerosol abundances. Observations and models show that northern tropical Atlantic surface temperatures are sensitive to regional changes in stratospheric volcanic and tropospheric mineral aerosols. However, it is unknown whether the temporal variability of these aerosols is a key factor in the evolution of ocean temperature anomalies. We used a simple physical model, incorporating 26 years of satellite data, to estimate the temperature response of the ocean mixed layer to changes in aerosol loadings. Our results suggest that the mixed layer’s response to regional variability in aerosols accounts for 69% of the recent upward trend, and 67% of the detrended and 5-year low pass–filtered variance, in northern tropical Atlantic Ocean temperatures.

A Naive Bayesian Cloud-Detection Scheme Derived from CALIPSO and Applied within PATMOS-x

AbstractThe naive Bayesian methodology has been applied to the challenging problem of cloud detection with NOAA’s Advanced Very High Resolution Radiometer (AVHRR). An analysis of collocated NOAA-18/AVHRR and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations was used to automatically and globally derive the Bayesian classifiers. The resulting algorithm used six Bayesian classifiers computed separately for seven surface types. Relative to CALIPSO, the final results show a probability of correct detection of roughly 90% over water, deserts, and snow-free land; 82% over the Arctic; and below 80% over the Antarctic. This technique is applied within the NOAA Pathfinder Atmosphere’s Extended (PATMOS-x) climate dataset and the Clouds from AVHRR Extended (CLAVR-x) real-time product generation system. Comparisons of the PATMOS-x results with those from International Satellite Cloud Climatology Project (ISCCP) and Moder...

Multidecadal Covariability of North Atlantic Sea Surface Temperature, African Dust, Sahel Rainfall, and Atlantic Hurricanes

AbstractMost studies of African dust and North Atlantic climate have been limited to the short time period since the satellite era (1980 onward), precluding the examination of their relationship on longer time scales. Here a new dust dataset with the record extending back to the 1950s is used to show a multidecadal covariability of North Atlantic SST and aerosol, Sahel rainfall, and Atlantic hurricanes. When the North Atlantic Ocean was cold from the late 1960s to the early 1990s, the Sahel received less rainfall and the tropical North Atlantic experienced a high concentration of dust. The opposite was true when the North Atlantic Ocean was warm before the late 1960s and after the early 1990s. This suggests a novel mechanism for North Atlantic SST variability—a positive feedback between North Atlantic SST, African dust, and Sahel rainfall on multidecadal time scales. That is, a warm (cold) North Atlantic Ocean produces a wet (dry) condition in the Sahel and thus leads to low (high) concentration of dust i...

Arabian Sea tropical cyclones intensified by emissions of black carbon and other aerosols

Throughout the year, average sea surface temperatures in the Arabian Sea are warm enough to support the development of tropical cyclones, but the atmospheric monsoon circulation and associated strong vertical wind shear limits cyclone development and intensification, only permitting a pre-monsoon and post-monsoon period for cyclogenesis. Thus a recent increase in the intensity of tropical cyclones over the northern Indian Ocean is thought to be related to the weakening of the climatological vertical wind shear. At the same time, anthropogenic emissions of aerosols have increased sixfold since the 1930s, leading to a weakening of the southwesterly lower-level and easterly upper-level winds that define the monsoonal circulation over the Arabian Sea. In principle, this aerosol-driven circulation modification could affect tropical cyclone intensity over the Arabian Sea, but so far no such linkage has been shown. Here we report an increase in the intensity of pre-monsoon Arabian Sea tropical cyclones during the period 1979–2010, and show that this change in storm strength is a consequence of a simultaneous upward trend in anthropogenic black carbon and sulphate emissions. We use a combination of observational, reanalysis and model data to demonstrate that the anomalous circulation, which is radiatively forced by these anthropogenic aerosols, reduces the basin-wide vertical wind shear, creating an environment more favourable for tropical cyclone intensification. Because most Arabian Sea tropical cyclones make landfall, our results suggest an additional impact on human health from regional air pollution.

Evidence for climate change in the satellite cloud record

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Development of a new over‐water Advanced Very High Resolution Radiometer dust detection algorithm

A new over–water dust detection algorithm is developed and applied to the 5–channel Advanced Very High Resolution Radiometer (AVHRR) imager onboard the National Oceanic and Atmospheric Administration series of polar orbiting satellites. The algorithm has been developed to improve the distinction between dust and meteorological clouds for very optically thick dust storms that would have previously been flagged as cloud under the Clouds from AVHRR Extended cloud mask algorithm. The algorithm has been assessed by making daily comparisons with data from the Aerosol Robotic Network and by making a climatological comparison with METEOSAT and Total Ozone Mapping Spectrometer data over a portion of the North Atlantic. The new algorithm improves the separation of clouds and airborne dust. Application of the new product to the 5–channel AVHRR historic data sets can provide information on the global dust signal, especially on an interannual time scale.

A Climatology of Arabian Sea Cyclonic Storms

On average 1‐2 tropical cyclones form over the Arabian Sea each year, and few of these storms are intense enough to be classified as very severe or super cyclonic storms. As such, few studies have explicitly identified theseasonaltointerannualchangesin environmental conditionsthatare associated with Arabian Sea tropical cyclogenesis. However, over the last 30 yr several intense Arabian storms did form and make landfall, with large impacts, which motivates this new study of the basin. The conclusions of earlier studies are visited by utilizingmodernobservationalandreanalysisdatatoidentifythelarge-scalefeaturesassociatedwithArabian tropical cyclone variability on seasonal time scales. Then year-to-year changes in environmental conditions that are related to interannual variability in Arabian storms during the pre- and postmonsoon periods are elucidated. The analysis of the relationship between large-scale environmental variables and seasonal storm frequency supports conclusions from work completed more than 40 yr prior. Investigation of the year-to-year changes in premonsoon storm frequency suggests that May (June) storms are associated with an early (late) onsetof the southwestmonsoon.Thefindingsalso demonstratethatNovembercyclones (the monthwhen the majority of postmonsoon cyclogenesis occurs) primarily form during periods when the Bay of Bengal experiencesabroadregionofhighsealevelpressure,implyingthatNovemberstormsformineithertheArabian Sea or the Bay of Bengal but not in both during the same year. Finally, the analysis of changes in a genesis potentialindex suggeststhat long-term variabilityin the potential for a storm to form is dictated by changes in midlevel moisture.

African Dust over the Northern Tropical Atlantic: 1955–2008

African dust outbreaks are the result of complex interactions between the land, atmosphere, and oceans, and only recently has a large body of work begun to emerge that aims to understand the controls on—and impacts of—African dust. At the same time, long-term records of dust outbreaks are either inferred from visibility data from weather stations or confined to a few in situ observational sites. Satellites provide the best opportunity for studying the large-scale characteristics of dust storms, but reliable records of dust are generally on the scale of a decade or less. Here the authors develop a simple model for using modern and historical data from meteorological satellites, in conjunction with a proxy record for atmospheric dust, to extend satellite-retrieved dust opticaldepthoverthenortherntropicalAtlanticOceanfrom1955to2008.Theresultant54-yrrecordofdusthas a spatial resolution of 18 and a monthly temporal resolution. From analysis of the historical dust data, monthly tropical northern Atlanticdust coverisbimodal,has a strongannual cycle,peaked in the early 1980s, and shows minimums in dustiness during the beginning and end of the record. These dust optical depth estimates are used to calculate radiative forcing and heating rates from the surface through the top of the atmosphere over the last half century. Radiative transfer simulations show a large net negative dust forcing from the surface through the topoftheatmosphere,alsowithadistinctannualcycle,andmeantropicalAtlanticmonthlyvaluesofthesurface forcing range from 2 3t o2 9Wm 22 . Since the surface forcing is roughly a factor of 3 larger in magnitude than the top-of-the-atmosphere forcing, there is also a positive heating rate of the midtroposphere by dust.

Empirical Removal of Artifacts from the ISCCP and PATMOS-x Satellite Cloud Records

AbstractThe International Satellite Cloud Climatology Project (ISCCP) dataset and the Pathfinder Atmospheres–Extended (PATMOS-x) dataset are two commonly used multidecadal satellite cloud records. Because they are constructed from weather satellite measurements lacking long-term stability, ISCCP and PATMOS-x suffer from artifacts that inhibit their use for investigating cloud changes over recent decades. The present study describes and applies a post hoc method to empirically remove spurious variability from anomalies in total cloud fraction at each grid box. Spurious variability removed includes that associated with systematic changes in satellite zenith angle, drifts in satellite equatorial crossing time, and unrealistic large-scale spatially coherent anomalies associated with known and unidentified problems in instrument calibration and ancillary data. The basic method is to calculate for each grid box the least squares best-fit line between cloud anomalies and artifact factor anomalies, and to let the...