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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

The atmospheric sulfur cycle over the Amazon Basin. II - Wet season

The fluxes and concentrations of atmospheric sulfur species were determined at ground level and from aircraft over the Amazon Basin during the 1987 wet season, providing a comprehensive description of the sulfur cycle over a remote tropical region. The vertical profile of dimethylsulfide (DMS) during the wet season was found to be very similar to that measured during the dry season, suggesting little seasonal variation in DMS fluxes. The concentrations of H2S were almost an order of magnitude higher than those of DMS, which makes H2S the most important biogenic source species in the atmosheric sulfur cycle over the Amazon Basin. Using the gradient-flux approach, the flux of DMS at the top of the tree canopy was estimated. The canopy was a source of DMS during the day, and a weak sink during the night. Measurements of sulfur gas emissions from soils, using the chamber method, showed very small fluxes, consistent with the hypothesis that the forest canopy is the major source of sulfur gases. The observed soil and canopy emission fluxes are similar to those measured in temperate regions. The concentrations of SO2 and sulfate aerosol in the wet season atmosphere were similar to dry season values.

Andreae, M. O.↗
NASA NTRS1990

Aerosol chemistry during the wet season in central Amazonia - The influence of long-range transport

The temporal variation in the concentration and chemistry of the atmospheric aerosol over central Amazonia, Brazil, during the 1987 wet season is discussed based on ground and aircraft collected data obtained during the NASA GTE ABLE 2B expedition conducted in April/May 1987. It is found that wet-season aerosol concentrations and composition are variable in contrast to the more uniform biogenic aerosol observed during the 1985 dry season; four distinct intervals of enhanced aerosol concentration coincided with short periods (3 to 5 d) of extensive rainfall. It is hypothesized that aerosol chemistry in Amazonia during the wet season is strongly influenced by long-range transport of soil dust, marine aerosol, and possibly biomass combustion products advected into the central Basin by large-scale tropospheric circulation, producing periodic pulses of material input to local boundary layer air. The resultant wet-season aerosol regime is dynamic, in contrast to the uniformity of natural biogenic aerosols during the dry season.

Talbot, R. W.↗
NASA NTRS1990

The role of the seasonal cycle in the quasi-biennial oscillation of ozone

The evidence for seasonal synchronization of the ozone quasi-biennial oscillation (QBO) is reviewed, showing how this behavior is not expected on the basis of QBO transport alone but may arise due to the seasonal cycle. Near the equator, the ozone QBO is closely tied to the dynamical QBO and exhibits the same period as that oscillation. Maximum column ozone is attained soon after the transition to westerlies at 50 mb. In the subtropics, the ozone QBO is strongly tied to the seasonal cycle, with anomalies centered in the winter-spring season irrespective of QBO phase. These anomalies result from the interaction of the annual cycle and the QBO. Numerical model results are reported which establish that hemispheric asymmetry in the ozone QBO does not require seasonal asymmetries in the strength or location of the Hadley circulation. The fundamental cause of hemispheric asymmetry in the subtropical ozone QBO is the timing of equatorial, ozone anomalies relative to the seasonal cycle.

Gray, Lesley J.↗
NASA NTRS1991

Soil emissions of nitric oxide in a seasonally dry tropical forest of Mexico

Soil emissions of NO were measured at the Chamela Biological Station, Mexico, using soil covers and a field apparatus of NO detection based on CrO3 conversion of NO to NO2 and detection of NO2 by chemiluminescence with Luminol. Mean NO fluxes from forest soils ranged from 0.14 to 0.52 ng NO-N/sq cm/hr during the dry season and from 0.73 to 1.27 ng NO-N/sq cm/hr during the wet season. A fertilized floodplain pasture exhibited higher fluxes, but an unfertilized upland pasture, which represents the fastest growing land use in the region, had flux rates similar to the forest sites. Wetting experiments at the end of the dry season caused large pulses of NO flux, equaling 10 percent to 20 percent of the estimated annual NO emissions of 0.5-1.0 kg N/ha from the forest sites. Absence of a forest canopy during the dry season and the first wet season rain probably results in substantial NO(x) export from the forest system that may be important to regional atmospheric chemical processes. Wetting experiments during the wet season and a natural rain event had little or no stimulatory effect on NO flux rates.

Davidson, Eric A.↗
NASA NTRS1992

Modeling the Martian seasonal CO2 cycle. I - Fitting the Viking Lander pressure curves. II - Interannual variability

The present diurnal and seasonal thermal model for Mars, in which surface CO2 frost condensation and sublimation are determined by the net effects of radiation, latent heat, and heat conduction in subsurface soil layers, in order to simulate seasonal exchanges of CO2 between the polar caps and atmosphere, successfully reproduces the measured pressured variations at the Viking Lander 1 site. In the second part of this work, the year-to-year differences between measured surface pressures at Viking sites as a function of season are used as upper limits on the potential magnitudes of interannual variations in the Martian atmosphere's mass. Simulations indicate that the dust layers deposited onto the condensing north seasonal polar cap during dust storms can darken seasonal frost deposits upon their springtime uncovering, while having little effect on seasonal pressure variations.

Wood, Stephen E.↗
NASA NTRS1993

Simulations of the general circulation of the Martian atmosphere. II - Seasonal pressure variations

The CO2 seasonal cycle of the Martian atmosphere and surface is simulated with a hybrid energy balance model that incorporates dynamical and radiation information from a large number of general circulation model runs. This information includes: heating due to atmospheric heat advection, the seasonally varying ratio of the surface pressure at the two Viking landing sites to the globally averaged pressure, the rate of CO2 condensation in the atmosphere, and solar heating of the atmosphere and surface. The predictions of the energy balance model are compared with the seasonal pressure variations measured at the two Viking landing sites and the springtime retreat of the seasonal polar cap boundaries. The following quantities are found to have a strong influence on the seasonal pressures at the Viking landing sites: albedo of the seasonal CO2 ice deposits, emissivity of this deposit, atmospheric heat advection, and the pressure ratio.

Pollack, James B.↗
NASA NTRS1994

Remote Sensing of Seasonal Leaf Area Index Across the Oregon Transect

Remotely sensed data acquired from four remote-sensing instruments on three different aircraft platforms over a transect of coniferous forest stands in Oregon were analyzed with respect to seasonal leaf area index (LAI). Data from the four instruments were corrected for the varying seasonal and geographic atmospheric conditions present along the transect. Strong logarithmic relationships were observed between seasonal maximum and minimum LAI and the simple ratio (SR) (near infrared/red reflectance) calculated from the broad-spectral-band Thematic Mapper Simulator (TMS), as well as from the narrow-spectral-band Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Compact Airborne Spectrographic Imager (CASI), and a Spectron SE590 spectro-radiometer (R(exp 2) = 0.82-0.97). The TMS SR reached an asymptote at an LAI of approx. 7-8. However, the SE590 and the CASI SR continued to increase up to the maximum LAI of 10.6. The variability of the relationship between the AVIRIS SR and LAI increased at stands with LAIs greater than 7, making a trend in the AVIRIS SR-LAI relationship at LAIs greater than 7 difficult to discern. The SRs of the coniferous forest stands measured by the narrow-spectral-band instruments were higher than they were from the broad-spectral-band TMS. This is attributed partially to the integration of the TMS over a broad wavelength region in the red and more strongly to calibration differences between the sensors. Seasonal TMS SR trends for four time periods for some of the stands deviated from the expected seasonal LAI trends, possibly because of smoke and very low sun angles during some of the acquisition periods. However, the expected SR differences for the seasonal minimum and maximum LAI were observed for all of the sensors for nearly all of the forest stands. This study, demonstrates that remotely, sensed data from both broad- and narrow spectral band instruments can provide estimates of LAI for use in forest ecosystems simulation models to estimate evapotranspiration, photosynthesis, canopy turnover, and net primary production over large areas.

Spanner, Michael↗
NASA NTRS1998

Statistical Aspects of Intense Hurricanes in the Atlantic Basin during the Past 49 Hurricane Seasons (1950-1998)

Statistical aspects of intense hurricanes (those of category 3 or higher) in the Atlantic basin for the interval of 1950-1998 are investigated with respect to the ENSC, cycle and the postulated 'more versus less' activity modes for intense hurricane activity. This is accomplished in order to evaluate the statistical basis for these specific groupings and to presage a forecast for the number of expected intense hurricanes during the forthcoming 1999 hurricane season. Statistically speaking, because the 1998-1999 La Nina (onset presumed to be September 1998) should persist longer than about a year - the average duration for La Nina events based on the 10 previously occurring La Nina, each having a duration in the range of 7-22 months - it seems likely that the 1999 season will be classified as a 'non-El Nino-related' (NENR) season. If true, then, greater than or equal to 2 intense hurricanes are to be expected. Based on Poisson statistics, the probability of greater than or equal to 2 events is about 77% when the season is classified as NENR, and it is about 87% when the season is classified as NENR and the 'more active' phase is in fashion; likewise, the probability of greater than or equal to 4 events is about 31% and 48%, respectively, for the two cases. Therefore, an above average rate (possibly, as many as 4 +/- 1, or higher) of intense hurricanes forming in the Atlantic basin seems a very distinct possibility during the 1999 season.

Wilson, Robert M.↗
NASA NTRS1998

Seasonal Cycles of Meridional Overturning and Heat Transport of the Indian Ocean

A general circulation model of the Indian Ocean is fitted to monthly averaged climatological temperatures, salinities, and surface fluxes using the adjoint method. Interannual variability is minimized by penalizing the temporal drift from one seasonal cycle to another during a two-year integration. The resultant meridional overturning and heat transport display large seasonal variations, with maximum amplitudes of 18 and 22 (x 10(exp 6) cubic m/s) for the overturning and 1.8 and 1.4 (x 10(exp 15) W) for heat transport near 10 S and 10 N, respectively. A dynamical decomposition of the overturning and heat transport shows that the time-varying Ekman How plus its barotropic compensation can explain a large part of the seasonal variations in overturning and heat transport. The maximum variations at 10 deg N and 10 deg S are associated with monsoon reversal over the northern Indian Ocean and changes of the easterlies over the southern Indian Ocean. An external mode with variable topography has a moderate contribution where the Somali Current and the corresponding gyre reverse direction seasonally. Contribution front vertical shear (thermal wind and ageostrophic shear) is dominant near the southern boundary and large near the Somali Current latitudes. The dominant balance in the zonally integrated heat budget is between heat storage change and heat transport convergence except south of 15 S. Optimization with seasonal forcings improves estimates of sea surface temperatures, but the annual average overturning and heat transport are very similar to previous results with annual mean forcings. The annual average heat transport consists of roughly equal contributions from time-mean and time-varying fields of meridional velocities and temperatures in the northern Indian Ocean. indicating a significant rectification to the heat transport due to the time-varying fields. The time-mean and time-varying contributions are primarily due to the overturning and horizontal gyre, respectively. Inclusion of TOPEX data enhances the seasonal cycles of the estimated overturning and heat transport in the central Indian Ocean significantly and improves the estimated equatorial zonal flows but leads 10 unrealistic estimates of the velocity structure near the Indonesian Throughflow region, most likely owing to the deficiencies in the lateral boundary conditions.

Lee, Tong↗
NASA NTRS2005

Interannual Variability of Seasonal Pblooms in the North Polar Atlantic in Response to Atmospheric Forcing

The year-to-year variability of timing, intensity, and spatial distribution of surface phytoplankton during spring-summer seasons is examined in the north polar region of the Atlantic using satellite-derived chlorophyll a concentration (Chl) over 7 years (1998 2004). Each year phytoplankton bloom differed in onset, temporal evolution, and intensity. This interannual variability is to a large degree controlled by local weather, as indicated by the analysis of coincident meteorological data. The atmospheric forcing was parameterized in terms of the generation rate of turbulent kinetic energy (TKE(sub RT)) supplied from the atmosphere to the ocean. Timing of the bloom is delayed in years with high TKE(sub RT) supplied to the ocean in March. In April, Chl (local and regionally averaged) and TKE(sub RT) are inversely related to one another. The late winter and early spring atmospheric conditions influence the seasonal Chl patterns. The seasonal (April-August) Chl correlates well with net heat flux, wind energy, and TKE(sub RT) in March and April, but the correlation can be negative or positive in different areas of the north polar Atlantic. The correlation between TKE(sub RT) and seasonal Chl is positive in the Greenland Gyre (higher seasonal Chl corresponds to higher TKE(sub RT) in March April) and negative in the regions of East Greenland and North Atlantic/West Spitsbergen Currents. The most likely explanation for the positive correlation between TKE(sub RT) and Chl within the Greenland Gyre is that higher TKE(sub RT) in spring increases the seasonal supply of nutrients into surface waters.

Stramska, Malgorzata↗
NASA NTRS1997

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Potter, C. S.↗
NASA NTRS1997

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

Potter, C. S.↗
NASA NTRS2007

Comparison of Seasonal Terrestrial Water Storage Variations from GRACE with Groundwater-level Measurements from the High Plains Aquifer (USA)

This study presents the first direct comparison of variations in seasonal GWS derived from GRACE TWS and simulated SM with GW-level measurements in a semiarid region. Results showed that variations in GWS and SM are the main sources controlling TWS changes over the High Plains, with negligible storage changes from surface water, snow, and biomass. Seasonal variations in GRACE TWS compare favorably with combined GWS from GW-level measurements (total 2,700 wells, average 1,050 GW-level measurements per season) and simulated SM from the Noah land surface model (R = 0.82, RMSD = 33 mm). Estimated uncertainty in seasonal GRACE-derived TWS is 8 mm, and estimated uncertainty in TWS changes is 11 mm. Estimated uncertainty in SM changes is 11 mm and combined uncertainty for TWS-SM changes is 15 mm. Seasonal TWS changes are detectable in 7 out of 9 monitored periods and maximum changes within a year (e.g. between winter and summer) are detectable in all 5 monitored periods. Grace-derived GWS calculated from TWS-SM generally agrees with estimates based on GW-level measurements (R = 0.58, RMSD = 33 mm). Seasonal TWS-SM changes are detectable in 5 out of the 9 monitored periods and maximum changes are detectable in all 5 monitored periods. Good correspondence between GRACE data and GW-level measurements from the intensively monitored High Plains aquifer validates the potential for using GRACE TWS and simulated SM to monitor GWS changes and aquifer depletion in semiarid regions subjected to intensive irrigation pumpage. This method can be used to monitor regions where large-scale aquifer depletion is ongoing, and in situ measurements are limited, such as the North China Plain or western India. This potential should be enhanced by future advances in GRACE processing, which will improve the spatial and temporal resolution of TWS changes, and will further increase applicability of GRACE data for monitoring GWS.

Strassberg, Gil↗
NASA NTRS2006

Intra-seasonal Oscillations Inferred from SABER (TIMED) and MLS (UARS) Temperature Measurements

In the zonal mean meridional winds of the upper mesosphere, intra-seasonal oscillations with periods between 1 and 4 months have been inferred from UARS measurements and independently predicted with the Numerical Spectral Model WSM). The wind oscillations tend to be confined to low latitudes and appear to be driven, at least in part, by small-scale gravity waves propagating in the meridional direction. Winds across the equator should generate, due to dynamical heating and cooling, temperature oscillations with opposite phase in the two hemispheres. Investigating this phenomenon, we have analyzed SABER temperatures from TIMED in the altitude range between 55 and 95 km to delineate with an empirical model, the year-long variability of the migrating tides and zonal mean components. The inferred seasonal variations of the diurnal tide, characterized by amplitude maxima near equinox, are in substantial agreement with UARS observations and results from the NSM. For the zonal mean, the dominant seasonal variations in the SABER temperatures, with annual (12 months) and semiannual (6 months) periodicities, agree well with those derived from UARS measurements. The intra-seasonal variations with periods between 2 and 4 months have amplitudes close to 2 K, almost half as large as those for the dominant seasonal variations. Their amplitudes are in qualitative agreement with the corresponding values inferred from UARS during different years. The SABER and UARS temperature variations reveal pronounced hemispherical asymmetries, consistent with meridional wind oscillations across the equator. The phase of the semi-annual temperature oscillations from the NSM agrees with the observations from UARS and SABER. But the amplitudes are systematically smaller, which may indicate that planetary waves are more important than is allowed for in the model. For the shorter-period intra-seasonal variations, which can be generated by gravity wave drag, the model results are generally in better agreement with the observations.

Huang, F. T.↗
NASA NTRS2009

A Look at Seasonal Snow Cover and Snow Mass in the Southern Hemisphere from 1979-2006 Using SMMR and SSM/I Passive Microwave Data

Seasonal snow cover in extra-tropical areas of South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and from the Special Sensor Microwave Imagers (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow mass were estimated for the months of May-September. Most of the seasonal snow in South America occurs in the Patagonia region of Argentina. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 sq km. The seasonal (May-September) 2 average snow cover extent was greatest in 1984 (464,250 sq km) and least in 1990 (69,875 sq km). In terms of snow mass, 1984 was also the biggest year (1.19 x 10(exp 13) kg) and 1990 was the smallest year (0.12 X 10(exp 13) kg). A strong relationship exists between the snow cover area and snow mass, correlated at 0.95, though no significant trend was found over the 28 year record for either snow cover extent or snow mass. For this long term climatology, snow mass and snow cover extent are shown to vary considerably from month to month and season to season. This analysis presents a consistent approach to mapping and measuring snow in South America utilizing an appropriate and readily available long term snow satellite dataset. This is the optimal dataset available, thus far, for deriving seasonal snow cover and snow mass in this region. Nonetheless, shallow snow, wet snow, snow beneath forests, as well as snow along coastal areas all may confound interpretation using passive microwave approaches. More work needs to be done to reduce the uncertainties in the data and hence, increase the confidence of the interpretation

Foster, James↗
NASA NTRS2012

Estimating the Length of the North Atlantic Basin Hurricane Season

For the interval 1945-2011, the length of the hurricane season in the North Atlantic basin averages about 130 +/- 42 days (the +/-1 standard deviation interval), having a range of 47 to 235 days. Runs-testing reveals that the annual length of season varies nonrandomly at the 5% level of significance. In particular, its trend, as described using 10-yr moving averages, generally has been upward since about 1979, increasing from about 113 to 157 days (in 2003). Based on annual values, one finds a highly statistically important inverse correlation at the 0.1% level of significance between the length of season and the occurrence of the first storm day of the season. For the 2012 hurricane season, based on the reported first storm day of May 19, 2012 (i.e., DOY = 140), the inferred preferential regression predicts that the length of the current season likely will be about 173 +/- 23 days, suggesting that it will end about November 8 +/- 23 days, with only about a 5% chance that it will end either before about September 23, 2012 or after about December 24, 2012.

Wilson, Robert M.↗
NASA NTRS2013

Prediction of Seasonal Climate-induced Variations in Global Food Production

Consumers, including the poor in many countries, are increasingly dependent on food imports and are therefore exposed to variations in yields, production, and export prices in the major food-producing regions of the world. National governments and commercial entities are paying increased attention to the cropping forecasts of major food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We assessed the reliability of hindcasts (i.e., retrospective forecasts for the past) of crop yield loss relative to the previous year for two lead times. Pre-season yield predictions employ climatic forecasts and have lead times of approximately 3 to 5 months for providing information regarding variations in yields for the coming cropping season. Within-season yield predictions use climatic forecasts with lead times of 1 to 3 months. Pre-season predictions can be of value to national governments and commercial concerns, complemented by subsequent updates from within-season predictions. The latter incorporate information on the most recent climatic data for the upcoming period of reproductive growth. In addition to such predictions, hindcasts using observations from satellites were performed to demonstrate the upper limit of the reliability of crop forecasting.

variations↗
NASA NTRS2014

On the Relationship Between the Length of Season and Tropical Cyclone Activity in the North Atlantic Basin During the Weather Satellite Era, 1960-2013

Officially, the North Atlantic basin tropical cyclone season runs from June 1 through November 30 of each year. During this 183-day interval, the vast majority of tropical cyclone onsets are found to occur. For example, in a study of the 715 tropical cyclones that occurred in the North Atlantic basin during the interval 1945-2010, it was found that about 97 percent of them had their onsets during the conventional hurricane season, with the bulk (78 percent) having had onset during the late summer-early fall months of August, September, and October and with none having had onset in the month of March. For the 2014 hurricane season, it already has had the onset of its first named storm on July 1 (day of year (DOY) 182), Arthur, which formed off the east coast of Florida, rapidly growing into a category-2 hurricane with peak 1-minute sustained wind speed of about 90 kt and striking the coast of North Carolina as a category-2 hurricane on July 3. Arthur is the first hurricane larger than category-1 to strike the United States (U.S.) since the year 2008 when Ike struck Texas as a category-2 hurricane and there has not been a major hurricane (category-3 or larger) to strike the U.S. since Wilma struck Florida as a category-3 hurricane in 2005. Only two category-1 hurricanes struck the U.S. in the year 2012 (Isaac and Sandy, striking Louisiana and New York, respectively) and there were no U.S. land-falling hurricanes in 2013 (also true for the years 1962, 1973, 1978, 1981, 1982, 1990, 1994, 2000, 2001, 2006, 2009, and 2010). In recent years it has been argued that the length of season (LOS), determined as the inclusive elapsed time between the first storm day (FSD) and the last storm day (LSD) of the yearly hurricane season (i.e., when peak 1-minute sustained wind speed of at least 34 kt occurred and the tropical cyclone was not classified as 'extratropical'), has increased in length with the lengthening believed to be due to the FSD occurring sooner and the LSD occurring later and with both being related to global warming. In this study, the relationship between the LOS and tropical cyclone activity and climate is examined for the weather satellite era, 1960-2013. Estimates are also given for the LOS and LSD, as well as for the expected number of tropical cyclones (NTC), the total number of storm days (NSD), the total accumulated cyclone energy (ACE), and the net tropical cyclone activity (NTCA) index for the 2014 hurricane season.

Wilson, Robert M.↗