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Published: 7 July 2024

Last updated: 7 July 2024

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1

Halpern, David. An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, 1995.

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2

Halpern, D. An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, 1995.

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3

Halpern, D. An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, 1995.

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4

Halpern, D. An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity,and TOPEX/POSEIDON sea surface height during 1994. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, 1997.

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5

David, Halpern, and Jet Propulsion Laboratory (U. S.), eds. An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height during 1995. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, 1998.

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6

Andrews, Patricia L. Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model. Fort Collins, CO: United States Department of Agriculture/Forest Service, Rocky Mountain Research Station, 2012.

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7

United States. National Weather Service., ed. Guide to sea state, wind, and clouds. [Washington, D.C.?]: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1995.

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8

Halpern, D. An atlas of monthly mean distributions of SSMI surface wind speed, ARGOS ... wind components during 1990. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, 1993.

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9

O'Muircheartaigh, I. G. Estimation of sea-surface windspeed from whitecap cover: Statistical approaches compared empirically and by simulation. Monterey, Calif: Naval Postgraduate School, 1985.

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10

G, Rehm Ronald, National Institute of Standards and Technology (U.S.), and Building and Fire Research Laboratory (U.S.), eds. An efficient large eddy simulation algorithm for computational wind engineering: Application to surface pressure computations on a single building. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1999.

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11

G, Rehm Ronald, National Institute of Standards and Technology (U.S.), and Building and Fire Research Laboratory (U.S.), eds. An efficient large eddy simulation algorithm for computational wind engineering: Application to surface pressure computations on a single building. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1999.

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12

Crescenti, Gennaro H. A compilation of moored current meter data and wind recorder data from the Severe Environment Surface Mooring (SESMOOR) volume XLIII. Woods Hole, Mass: Woods Hole Oceanographic Institution, 1991.

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13

R, French Jeffrey, Crawford Timothy L, and Air Resources Laboratory (U.S.), eds. Aircraft measurements in the coupled boundary layers air-sea transfer (CBLAST) light wind pilot field study. Silver Spring, Md: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Oceanic and Atmospheric Research Laboratories, Air Resources Laboratory, 2001.

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14

W, Gregg Watson, and Goddard Space Flight Center, eds. An assessment of SeaWiFS and MODIS ocean coverage. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1998.

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15

Jet Propulsion Laboratory (U.S.), ed. 1982-1983 El Niño atlas: Nimbus-7 microwave radiometer data. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1987.

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16

Jet Propulsion Laboratory (U.S.), ed. 1982-1983 El Niño atlas: Nimbus-7 microwave radiometer data. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1987.

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17

Jet Propulsion Laboratory (U.S.), ed. 1982-1983 El Niño atlas: Nimbus-7 microwave radiometer data. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1987.

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18

United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., ed. Effects of upper-surface nacelles on longitudinal aerodynamic characteristics of high-wing transport configuration. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1986.

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19

United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., ed. Effects of upper-surface nacelles on longitudinal aerodynamic characteristics of high-wing transport configuration. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1986.

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20

K, Moore Richard, and United States. National Aeronautics and Space Administration., eds. Correction of WindScat scatterometric measurements by combining with AMSR radiometric data. Lawrence, Kan: Radar Systems and Remote Sensing Laboratory, University of Kansas Center for Research, 1996.

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21

A, Smith Elizabeth. Contents of the NASA Ocean Data System archive. Edited by Lassanyi Ruby A and Jet Propulsion Laboratory (U.S.). Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1990.

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22

A, Smith Elizabeth. Contents of the NASA Ocean Data System archive. Edited by Lassanyi Ruby A and Jet Propulsion Laboratory (U.S.). Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1990.

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23

National Aeronautics and Space Administration (NASA) Staff. Atlas of Monthly Mean Distributions of Ssmi Surface Wind Speed, Avhrr/2 Sea Surface Temperature, Ami Surface Wind Velocity, Topex/Poseidon Sea Surface Height, and Ecmwf Surface Wind Velocity During 1993. Independently Published, 2018.

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24

National Aeronautics and Space Administration (NASA) Staff. Atlas of Monthly Mean Distributions of Geosat Sea Surface Height, Ssmi Surface Wind Speed, Avhrr/2 Sea Surface Temperature, and Ecmwf Surface Wind Components During 1988. Independently Published, 2018.

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25

An atlas of monthly mean distributions of GEOSAT sea surface height, SSMI surface wind Speed, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1988. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1991.

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26

National Aeronautics and Space Administration (NASA) Staff. Sensitivity of Global Sea-Air Co2 Flux to Gas Transfer Algorithms, Climatological Wind Speeds, and Variability of Sea Surface Temperature and Salinity. Independently Published, 2018.

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27

An atlas of monthly mean distributions of SSMI surface wind speed ... wind components during 1991. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, 1993.

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28

Servain, Jacques. Climatic atlas of the tropical Atlantic wind stress and sea surface temperature, 1985-1989. IFREMER, 1990.

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29

Experimental surface pressure data obtained on 65 ̊delta wing across Reynolds number and Mach number ranges. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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30

1982-1983 El Niño atlas: Nimbus-7 microwave radiometer data. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1987.

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31

Christensen, Ole Bøssing, and Erik Kjellström. Projections for Temperature, Precipitation, Wind, and Snow in the Baltic Sea Region until 2100. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.695.

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Abstract:

The ecosystems and the societies of the Baltic Sea region are quite sensitive to fluctuations in climate, and therefore it is expected that anthropogenic climate change will affect the region considerably. With numerical climate models, a large amount of projections of meteorological variables affected by anthropogenic climate change have been performed in the Baltic Sea region for periods reaching the end of this century.Existing global and regional climate model studies suggest that:• The future Baltic climate will get warmer, mostly so in winter. Changes increase with time or increasing emissions of greenhouse gases. There is a large spread between different models, but they all project warming. In the northern part of the region, temperature change will be higher than the global average warming.• Daily minimum temperatures will increase more than average temperature, particularly in winter.• Future average precipitation amounts will be larger than today. The relative increase is largest in winter. In summer, increases in the far north and decreases in the south are seen in most simulations. In the intermediate region, the sign of change is uncertain.• Precipitation extremes are expected to increase, though with a higher degree of uncertainty in magnitude compared to projected changes in temperature extremes.• Future changes in wind speed are highly dependent on changes in the large-scale circulation simulated by global climate models (GCMs). The results do not all agree, and it is not possible to assess whether there will be a general increase or decrease in wind speed in the future.• Only very small high-altitude mountain areas in a few simulations are projected to experience a reduction in winter snow amount of less than 50%. The southern half of the Baltic Sea region is projected to experience significant reductions in snow amount, with median reductions of around 75%.

32

Deay, Norah, and Pimp My Writing. Fishing Adventures: Deep Sea Fishing/7 X 10 Fishing Log/Location/Date/Companions/Water and Air Temps/Hours Fished/Wind Direction and Speed/Humidity/Moon and Tide Phase/ Species/Bait/Length/Weight/Time. Independently Published, 2019.

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33

Räisänen, Jouni. Future Climate Change in the Baltic Sea Region and Environmental Impacts. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.634.

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The warming of the global climate is expected to continue in the 21st century, although the magnitude of change depends on future anthropogenic greenhouse gas emissions and the sensitivity of climate to them. The regional characteristics and impacts of future climate change in the Baltic Sea countries have been explored since at least the 1990s. Later research has supported many findings from the early studies, but advances in understanding and improved modeling tools have made the picture gradually more comprehensive and more detailed. Nevertheless, many uncertainties still remain.In the Baltic Sea region, warming is likely to exceed its global average, particularly in winter and in the northern parts of the area. The warming will be accompanied by a general increase in winter precipitation, but in summer, precipitation may either increase or decrease, with a larger chance of drying in the southern than in the northern parts of the region. Despite the increase in winter precipitation, the amount of snow is generally expected to decrease, as a smaller fraction of the precipitation falls as snow and midwinter snowmelt episodes become more common. Changes in windiness are very uncertain, although most projections suggest a slight increase in average wind speed over the Baltic Sea. Climatic extremes are also projected to change, but some of the changes will differ from the corresponding change in mean climate. For example, the lowest winter temperatures are expected to warm even more than the winter mean temperature, and short-term summer precipitation extremes are likely to become more severe, even in the areas where the mean summer precipitation does not increase.The projected atmospheric changes will be accompanied by an increase in Baltic Sea water temperature, reduced ice cover, and, according to most studies, reduced salinity due to increased precipitation and river runoff. The seasonal cycle of runoff will be modified by changes in precipitation and earlier snowmelt. Global-scale sea level rise also will affect the Baltic Sea, but will be counteracted by glacial isostatic adjustment. According to most projections, in the northern parts of the Baltic Sea, the latter will still dominate, leading to a continued, although decelerated, decrease in relative sea level. The changes in the physical environment and climate will have a number of environmental impacts on, for example, atmospheric chemistry, freshwater and marine biogeochemistry, ecosystems, and coastal erosion. However, future environmental change in the region will be affected by several interrelated factors. Climate change is only one of them, and in many cases its effects may be exceeded by other anthropogenic changes.

34

Yang, Kun. Observed Regional Climate Change in Tibet over the Last Decades. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.587.

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The Tibetan Plateau (TP) is subjected to strong interactions among the atmosphere, hydrosphere, cryosphere, and biosphere. The Plateau exerts huge thermal forcing on the mid-troposphere over the mid-latitude of the Northern Hemisphere during spring and summer. This region also contains the headwaters of major rivers in Asia and provides a large portion of the water resources used for economic activities in adjacent regions. Since the beginning of the 1980s, the TP has undergone evident climate changes, with overall surface air warming and moistening, solar dimming, and decrease in wind speed. Surface warming, which depends on elevation and its horizontal pattern (warming in most of the TP but cooling in the westernmost TP), was consistent with glacial changes. Accompanying the warming was air moistening, with a sudden increase in precipitable water in 1998. Both triggered more deep clouds, which resulted in solar dimming. Surface wind speed declined from the 1970s and started to recover in 2002, as a result of atmospheric circulation adjustment caused by the differential surface warming between Asian high latitudes and low latitudes.The climate changes over the TP have changed energy and water cycles and has thus reshaped the local environment. Thermal forcing over the TP has weakened. The warming and decrease in wind speed lowered the Bowen ratio and has led to less surface sensible heating. Atmospheric radiative cooling has been enhanced, mainly through outgoing longwave emission from the warming planetary system and slightly enhanced solar radiation reflection. The trend in both energy terms has contributed to the weakening of thermal forcing over the Plateau. The water cycle has been significantly altered by the climate changes. The monsoon-impacted region (i.e., the southern and eastern regions of the TP) has received less precipitation, more evaporation, less soil moisture and less runoff, which has resulted in the general shrinkage of lakes and pools in this region, although glacier melt has increased. The region dominated by westerlies (i.e., central, northern and western regions of the TP) received more precipitation, more evaporation, more soil moisture and more runoff, which together with more glacier melt resulted in the general expansion of lakes in this region. The overall wetting in the TP is due to both the warmer and moister conditions at the surface, which increased convective available potential energy and may eventually depend on decadal variability of atmospheric circulations such as Atlantic Multi-decadal Oscillation and an intensified Siberian High. The drying process in the southern region is perhaps related to the expansion of Hadley circulation. All these processes have not been well understood.

35

Kraus, Eric B., and Joost A. Businger. Atmosphere-Ocean Interaction. Oxford University Press, 1995. http://dx.doi.org/10.1093/oso/9780195066180.001.0001.

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With both the growing importance of integrating studies of air-sea interaction and the interest in the general problem of global warming, the appearance of the second edition of this popular text is especially welcome. Thoroughly updated and revised, the authors have retained the accessible, comprehensive expository style that distinguished the earlier edition. Topics include the state of matter near the interface, radiation, surface wind waves, turbulent transfer near the interface, the planetary boundary layer, atmospherically-forced perturbations in the oceans, and large-scale forcing by sea surface buoyancy fluxes. This book will be welcomed by students and professionals in meteorology, physical oceanography, physics and ocean engineering.

36

Hameed, Saji N. The Indian Ocean Dipole. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.619.

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Discovered at the very end of the 20th century, the Indian Ocean Dipole (IOD) is a mode of natural climate variability that arises out of coupled ocean–atmosphere interaction in the Indian Ocean. It is associated with some of the largest changes of ocean–atmosphere state over the equatorial Indian Ocean on interannual time scales. IOD variability is prominent during the boreal summer and fall seasons, with its maximum intensity developing at the end of the boreal-fall season. Between the peaks of its negative and positive phases, IOD manifests a markedly zonal see-saw in anomalous sea surface temperature (SST) and rainfall—leading, in its positive phase, to a pronounced cooling of the eastern equatorial Indian Ocean, and a moderate warming of the western and central equatorial Indian Ocean; this is accompanied by deficit rainfall over the eastern Indian Ocean and surplus rainfall over the western Indian Ocean. Changes in midtropospheric heating accompanying the rainfall anomalies drive wind anomalies that anomalously lift the thermocline in the equatorial eastern Indian Ocean and anomalously deepen them in the central Indian Ocean. The thermocline anomalies further modulate coastal and open-ocean upwelling, thereby influencing biological productivity and fish catches across the Indian Ocean. The hydrometeorological anomalies that accompany IOD exacerbate forest fires in Indonesia and Australia and bring floods and infectious diseases to equatorial East Africa. The coupled ocean–atmosphere instability that is responsible for generating and sustaining IOD develops on a mean state that is strongly modulated by the seasonal cycle of the Austral-Asian monsoon; this setting gives the IOD its unique character and dynamics, including a strong phase-lock to the seasonal cycle. While IOD operates independently of the El Niño and Southern Oscillation (ENSO), the proximity between the Indian and Pacific Oceans, and the existence of oceanic and atmospheric pathways, facilitate mutual interactions between these tropical climate modes.