scholarly journals Space-time variability of the rainfall over the western Mediterranean region: A statistical analysis

2013 ◽  
Vol 118 (15) ◽  
pp. 8448-8459 ◽  
Author(s):  
J.-F. Rysman ◽  
S. Verrier ◽  
Y. Lemaître ◽  
E. Moreau
Keyword(s):  
Statistical Analysis ◽  
Mediterranean Region ◽  
Western Mediterranean ◽  
Space Time ◽  
Time Variability

Precipitation and temperature space–time variability and extremes in the Mediterranean region: evaluation of dynamical and statistical downscaling methods

2012 ◽  
Vol 40 (11-12) ◽  
pp. 2687-2705 ◽  
Author(s):  
Emmanouil Flaounas ◽  
Philippe Drobinski ◽  
Mathieu Vrac ◽  
Sophie Bastin ◽  
Cindy Lebeaupin-Brossier ◽  
...  
Keyword(s):  
Statistical Downscaling ◽  
Mediterranean Region ◽  
Space Time ◽  
Time Variability ◽  
The Mediterranean ◽  
Precipitation And Temperature

Potential of Arabic documentary sources for reconstructing past climate in the western Mediterranean region from AD 680 to 1815

The Holocene ◽  
2021 ◽  
pp. 095968362110332
Author(s):  
Yassin Meklach ◽  
Chantal Camenisch ◽  
Abderrahmane Merzouki ◽  
Ricardo Garcia Herrera
Keyword(s):  
Spatial Resolution ◽  
Mediterranean Region ◽  
Climate Extremes ◽  
Western Mediterranean ◽  
Historical Documents ◽  
Atmospheric Conditions ◽  
Documentary Sources ◽  
Drought Conditions ◽  
Temporal And Spatial ◽  
Climate Proxies

Archival records and historical documents offer direct observation of weather and atmospheric conditions and have the highest temporal and spatial resolution, and precise dating, of the available climate proxies. They also provide information about variables such as temperature, precipitation and climate extremes, as well as floods, droughts and storms. The present work studied Arab-Islamic documentary sources covering the western Mediterranean region (documents written by Arab-Islamic historians that narrate social, political and religious history) available for the period AD 680–1815. They mostly provide information on hydrometeorological events. In Iberia the most intense droughts were reported during AD 747–753, AD 814–822, AD 846–847, AD 867–874 and AD 914–915 and in the Maghreb AD 867–873, AD 898–915, AD 1104–1147, AD 1280–1340 and AD 1720–1815 had prevalent drought conditions. Intense rain episodes are also reported.

scholarly journals Forecasting the SST Space-time variability of the Alboran Sea with genetic algorithms

2000 ◽  
Vol 27 (17) ◽  
pp. 2709-2712 ◽  
Author(s):  
Alberto Álvarez ◽  
Cristóbal López ◽  
Margalida Riera ◽  
Emilio Hernández-García ◽  
Joaquín Tintoré
Keyword(s):  
Genetic Algorithms ◽  
Space Time ◽  
Time Variability ◽  
Alboran Sea ◽  
Alborán Sea

scholarly journals Modeling the Variability of Drop Size Distributions in Space and Time

2007 ◽  
Vol 46 (6) ◽  
pp. 742-756 ◽  
Author(s):  
Gyu Won Lee ◽  
Alan W. Seed ◽  
Isztar Zawadzki
Keyword(s):  
Drop Size ◽  
Temporal Structure ◽  
Space Time ◽  
Cascade Model ◽  
Time Variability ◽  
Size Distributions ◽  
Precipitation Field ◽  
Stochastic Fluctuations ◽  
Taylor Hypothesis ◽  
Drop Size Distributions

Abstract The information on the time variability of drop size distributions (DSDs) as seen by a disdrometer is used to illustrate the structure of uncertainty in radar estimates of precipitation. Based on this, a method to generate the space–time variability of the distributions of the size of raindrops is developed. The model generates one moment of DSDs that is conditioned on another moment of DSDs; in particular, radar reflectivity Z is used to obtain rainfall rate R. Based on the fact that two moments of the DSDs are sufficient to capture most of the DSD variability, the model can be used to calculate DSDs and other moments of interest of the DSD. A deterministic component of the precipitation field is obtained from a fixed R–Z relationship. Two different components of DSD variability are added to the deterministic precipitation field. The first represents the systematic departures from the fixed R–Z relationship that are expected from different regimes of precipitation. This is generated using a simple broken-line model. The second represents the fluctuations around the R–Z relationship for a particular regime and uses a space–time multiplicative cascade model. The temporal structure of the stochastic fluctuations is investigated using disdrometer data. Assuming Taylor hypothesis, the spatial structure of the fluctuations is obtained and a stochastic model of the spatial distribution of the DSD variability is constructed. The consistency of the model is validated using concurrent radar and disdrometer data.

scholarly journals AXIS—An Autonomous Expendable Instrument System

2017 ◽  
Vol 34 (12) ◽  
pp. 2673-2682 ◽  
Author(s):  
D. M. Fratantoni ◽  
J. K. O’Brien ◽  
C. Flagg ◽  
T. Rossby
Keyword(s):  
Thermal Structure ◽  
New Technology ◽  
Space Time ◽  
Time Variability ◽  
Upper Ocean ◽  
Time Stamp ◽  
Merchant Marine ◽  
Marine Vessels ◽  
System Axis

AbstractExpendable bathythermographs (XBT) to profile upper-ocean temperatures from vessels in motion have been in use for some 50 years now. Developed originally for navy use, they were soon adapted by oceanographers to map out upper-ocean thermal structure and its space–-time variability from both research vessels and merchant marine vessels in regular traffic. These activities continue today. This paper describes a new technology—the Autonomous Expendable Instrument System (AXIS)—that has been developed to provide the capability to deploy XBT probes on a predefined schedule, or adaptively in response to specific events without the presence of an observer on board. AXIS is a completely self-contained system that can hold up to 12 expendable probes [XBTs, XCTDs, expendable sound velocimeter (XSV)] in any combination. A single-board Linux computer keeps track of what probes are available, takes commands from ashore via Iridium satellite on what deployment schedule to follow, and records and forwards the probe data immediately with a time stamp and the GPS position. This paper provides a brief overview of its operation, capabilities, and some examples of how it is improving coverage along two lines in the Atlantic.

scholarly journals Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets

2010 ◽  
Vol 14 (10) ◽  
pp. 1919-1930 ◽  
Author(s):  
T. Raziei ◽  
I. Bordi ◽  
L. S. Pereira ◽  
A. Sutera
Keyword(s):  
Time Series ◽  
Singular Spectrum Analysis ◽  
Standardized Precipitation Index ◽  
Principal Component ◽  
Reanalysis Data ◽  
Space Time ◽  
Hydrological Drought ◽  
Time Variability ◽  
Climate Conditions ◽  
Good Agreement

Abstract. Space-time variability of hydrological drought and wetness over Iran is investigated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and the Global Precipitation Climatology Centre (GPCC) dataset for the common period 1948–2007. The aim is to complement previous studies on the detection of long-term trends in drought/wetness time series and on the applicability of reanalysis data for drought monitoring in Iran. Climate conditions of the area are assessed through the Standardized Precipitation Index (SPI) on 24-month time scale, while Principal Component Analysis (PCA) and Varimax rotation are used for investigating drought/wetness variability, and drought regionalization, respectively. Singular Spectrum Analysis (SSA) is applied to the time series of interest to extract the leading nonlinear components and compare them with linear fittings. Differences in drought and wetness area coverage resulting from the two datasets are discussed also in relation to the change occurred in recent years. NCEP/NCAR and GPCC are in good agreement in identifying four sub-regions as principal spatial modes of drought variability. However, the climate variability in each area is not univocally represented by the two datasets: a good agreement is found for south-eastern and north-western regions, while noticeable discrepancies occur for central and Caspian sea regions. A comparison with NCEP Reanalysis II for the period 1979–2007, seems to exclude that the discrepancies are merely due to the introduction of satellite data into the reanalysis assimilation scheme.

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