Relevant bibliographies by topics / Seasonal climatology

Academic literature on the topic 'Seasonal climatology'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Seasonal climatology"

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McDonald, Jessica, Alan Srock, and Joseph Charney. "Development and Application of a Hot-Dry-Windy Index (HDW) Climatology." Atmosphere 9, no. 7 (July 20, 2018): 285. http://dx.doi.org/10.3390/atmos9070285.

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In this paper, we describe and analyze a climatology of the Hot-Dry-Windy Index (HDW), with the goal of providing fire-weather forecasters with information about the daily and seasonal variability of the index. The 30-year climatology (1981–2010) was produced using the Climate Forecast System Reanalysis (CFSR) for the contiguous United States, using percentiles to show seasonal and geographical variations of HDW contained within the climatology. The method for producing this climatology is documented and the application of the climatology to historical fire events is discussed. We show that the HDW climatology provides insight into near-surface climatic conditions that can be used to identify temperature and humidity trends that correspond to climate classification systems. Furthermore, when used in conjunction with daily traces of HDW values, users can follow trends in HDW and compare those trends with historical values at a given location. More usefully, this climatology adds value to HDW forecasts; by combining the CFSR climatology and a Global Ensemble Forecast System (GEFS) ensemble history and forecast, we can produce a single product that provides seasonal, climatological, and short-term context to help determine the appropriate fire-management response to a given HDW value.
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Gatebe, C. K., P. D. Tyson, H. Annegarn, S. Piketh, and G. Helas. "A seasonal air transport climatology for Kenya." Journal of Geophysical Research: Atmospheres 104, no. D12 (June 1, 1999): 14237–44. http://dx.doi.org/10.1029/1998jd200103.

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Willmott, Cort J., Clinton M. Rowe, and Yale Mintz. "Climatology of the terrestrial seasonal water cycle." Journal of Climatology 5, no. 6 (November 1985): 589–606. http://dx.doi.org/10.1002/joc.3370050602.

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Henderson‐Sellers, A., K. McGuffie, and J. G. Cogley. "Seasonal climatology of cloud at resolute (75°N)." Atmosphere-Ocean 23, no. 1 (March 1985): 80–93. http://dx.doi.org/10.1080/07055900.1985.9649216.

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Moraes, Bergson Cavalcanti, Giordani Rafael Conceição Sodré, Everaldo Barreiros Souza, João Batista Miranda Ribeiro, Luiz Gylvan Meira Filho, Douglas Batista da Silva Ferreira, and Juarez Ventura Oliveira. "Climatology of seasonal rainfall in the eastern Amazon." Revista Brasileira de Geografia Física 8, no. 5 (2015): 1359–73. http://dx.doi.org/10.5935/1984-2295.20150074.

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Wallace, Emily, and Alberto Arribas. "Forecasting with Reference to a Specific Climatology." Monthly Weather Review 140, no. 11 (November 1, 2012): 3795–802. http://dx.doi.org/10.1175/mwr-d-12-00159.1.

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Abstract Seasonal forecasts are most commonly issued as anomalies with respect to some multiyear reference period. However, different seasonal forecasting centers use different reference periods. This paper shows that for near-surface temperature, precipitation, and mean sea level pressure, over most regions of the world there is evidence that these differences between reference periods should not be ignored, especially when forecasters combine outputs from several prediction systems. Three methods are presented by which reference periods could be adjusted, and it is shown that the differences between the proposed methods are smaller than the errors that result from not correcting for different reference periods.
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Horan, Matthew F., and Thomas Reichler. "Modeling Seasonal Sudden Stratospheric Warming Climatology Based on Polar Vortex Statistics." Journal of Climate 30, no. 24 (December 2017): 10101–16. http://dx.doi.org/10.1175/jcli-d-17-0257.1.

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This study investigates the climatological frequency distribution of sudden stratospheric warmings (SSWs). General circulation models (GCMs) tend to produce SSW maxima later in winter than observations, which has been considered as a model deficiency. However, the observed record is short, calling into question the representativeness of the observational record. To study the seasonality of SSWs and the factors behind it, the authors use observations, a long control simulation with a stratosphere resolving GCM, and also a simple statistical model that is based on the climatological seasonal cycle of the polar vortex winds. From the combined analysis, the authors conclude that the late-winter SSW maximum seen in most climate models is realistic and that observations would also have a late-winter SSW maximum if more data were available. The authors identify the seasonally varying strengths of the polar vortex and stratospheric wave driving as the two main factors behind the seasonal SSW distribution. The statistical model also indicates that there exists a continuum of weak polar vortex states and that SSWs simply form the tail of normally distributed stratospheric winds.
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Crochemore, Louise, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin. "Seasonal streamflow forecasting by conditioning climatology with precipitation indices." Hydrology and Earth System Sciences 21, no. 3 (March 14, 2017): 1573–91. http://dx.doi.org/10.5194/hess-21-1573-2017.

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Abstract. Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.
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Iona, Athanasia, Athanasios Theodorou, Sylvain Watelet, Charles Troupin, Jean-Marie Beckers, and Simona Simoncelli. "Mediterranean Sea Hydrographic Atlas: towards optimal data analysis by including time-dependent statistical parameters." Earth System Science Data 10, no. 3 (July 16, 2018): 1281–300. http://dx.doi.org/10.5194/essd-10-1281-2018.

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Abstract. The goal of the present work is to provide the scientific community with a high-resolution atlas of temperature and salinity for the Mediterranean Sea based on the most recent datasets available and contribute to the studies of the long-term variability in the region. Data from the pan-European marine data infrastructure SeaDataNet were used, the most complete and, to our best knowledge, best quality dataset for the Mediterranean Sea as of today. The dataset is based on in situ measurements acquired between 1900 and 2015. The atlas consists of horizontal gridded fields produced by the Data-Interpolating Variational Analysis, in which unevenly spatial distributed measurements were interpolated onto a 1∕8° × 1∕8° regular grid on 31 depth levels. Seven different types of climatological fields were prepared with different temporal integration of observations. Monthly, seasonal and annual climatological fields have been calculated for all the available years, seasonal to annual climatologies for overlapping decades and specific periods. The seasonal and decadal time frames have been chosen in accordance with the regional variability and in coherence with atmospheric indices. The decadal and specific-period analysis was not extended to monthly resolution due to the lack of data, especially for the salinity. The Data-Interpolating Variational Analysis software has been used in the Mediterranean region for the SeaDataNet and its predecessor Medar/Medatlas Climatologies. In the present study, a more advanced optimization of the analysis parameters was performed in order to produce more detailed results. The past and present states of the Mediterranean region have been extensively studied and documented in a series of publications. The purpose of this atlas is to contribute to these climatological studies and get a better understanding of the variability on timescales from months to decades and longer. Our gridded fields provide a valuable complementary source of knowledge in regions where measurements are scarce, especially in critical areas of interest such as the Marine Strategy Framework Directive (MSFD) regions and subregions. The dataset used for the preparation of the atlas is available from https://doi.org/10.12770/8c3bd19b-9687-429c-a232-48b10478581c.The climatologies in netCDF are available at the following sources: annual climatology (https://doi.org/10.5281/zenodo.1146976), seasonal climatology for 57 running decades (https://doi.org/10.5281/zenodo.1146938), seasonal climatology (https://doi.org/10.5281/zenodo.1146953), annual climatology for 57 running decades (https://doi.org/10.5281/zenodo.1146957), seasonal climatology for six periods (https://doi.org/10.5281/zenodo.1146966), annual climatology for six periods (https://doi.org/10.5281/zenodo.1146970), monthly climatology (https://doi.org/10.5281/zenodo.1146974).
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Allen, Douglas R., and Noboru Nakamura. "A seasonal climatology of effective diffusivity in the stratosphere." Journal of Geophysical Research: Atmospheres 106, no. D8 (April 1, 2001): 7917–35. http://dx.doi.org/10.1029/2000jd900717.

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Dissertations / Theses on the topic "Seasonal climatology"

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Cannon, Alex Jason. "Multivariate statistical models for seasonal climate prediction and climate downscaling." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2892.

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This dissertation develops multivariate statistical models for seasonal forecasting and downscaling of climate variables. In the case of seasonal climate forecasting, where record lengths are typically short and signal-to-noise ratios are low, particularly at long lead-times, forecast models must be robust against noise. To this end, two models are developed. Robust nonlinear canonical correlation analysis, which introduces robust cost functions to an existing model architecture, is outlined in Chapter 2. Nonlinear principal predictor analysis, the nonlinear extension of principal predictor analysis, a linear model of intermediate complexity between multivariate regression and canonical correlation analysis, is developed in Chapter 3. In the case of climate downscaling, the goal is to predict values of weather elements observed at local or regional scales from the synoptic-scale atmospheric circulation, usually for the purpose of generating climate scenarios from Global Climate Models. In this context, models must not only be accurate in terms of traditional model verification statistics, but they must also be able to replicate statistical properties of the historical observations. When downscaling series observed at multiple sites, correctly specifying relationships between sites is of key concern. Three models are developed for multi-site downscaling. Chapter 4 introduces nonlinear analog predictor analysis, a hybrid model that couples a neural network to an analog model. The neural network maps the original predictors to a lower-dimensional space such that predictions from the analog model are improved. Multivariate ridge regression with negative values of the ridge parameters is introduced in Chapter 5 as a means of performing expanded downscaling, which is a linear model that constrains the covariance matrix of model predictions to match that of observations. The expanded Bernoulli-gamma density network, a nonlinear probabilistic extension of expanded downscaling, is introduced in Chapter 6 for multi-site precipitation downscaling. The single-site model is extended by allowing multiple predictands and by adopting the expanded downscaling covariance constraint.
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Mohammadi-Sheshnarmi, Hossein Morad. "Seasonal rainfall regime in the Central Elburz, Iran." Thesis, University of Newcastle Upon Tyne, 1998. http://hdl.handle.net/10443/342.

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The area chosen for this study is the Central Elburz of Iran surrounding the southern end of the Caspian Sea. It includes an important rainfall dependent agricultural area and merges into the semi arid zone with a well defined boundary. From social and agricultural points of view rainfall is by far the most important climatic factor in many tropical and subtropical countries. An important aspect in the development of agriculture in the Central Elburz is the determination of the seasonal rainfall patterns. This thesis should be considered as a contribution to the study of the seasonal rainfall regime of Iran, with direct value to agriculture in the region. The purpose of this thesis is to examine the pattern of rainfall especially in relation to the growing season both in time and spatially. Also the thesis describes the variation in the availability of moisture for growth throughout this region. The thesis examines annual, monthly and seasonal rainfall over the region. Multivariate analysis has demonstrated that the study area can be divided into three rainfall regions. Before considering any analysis which could allow prediction on probability of future rainfall amounts, it is important to consider whether or not there on trends or fluctuations. The result of this analysis is that, few stations show positive trends, others negative trends. Rainfall variability has been quantified by the coefficient of variation index and analysed in a similar way to that of rainfall distribution. The results for most stations shown a relationship between variability indices and rainfall amounts. In relation to the study of variability, an assessment of rainfall probability and reliability has been considered with reference to rainfall critical for crops. Probability has a particular value in its application to agriculture. In this study 90% probability is examined and this is related to the economy of the agriculture units in the Central Elburz. Also 80 and 75 percent probability are presented. These spatial patterns of probability thus provide maps of agricultural potential. Rainfall records are analysed to provide estimates, percentage points of rainfall totals, variation in the start, and end of the rainy season and or the probability of dry spells within the rainy season. The estimation of potential evapotranspiration which are discussed and explained in this study are based on the Blaney- Criddle and Pan evaporation methods. The water balance approach provides the most rational method of analysing seasonal pattern since it considers characteristics of the dominant crops in this area, wheat and citrus, and it examines effectiveness of rainfall for these crops. Blaney- Criddle and Pan evaporation have been used to estimate potential evaporation for wheat and citrus and compared to actual evapotranspiration to give potential water deficit. The adoption of probability analysis of potential water deficit provides a valuable description of water availability for crops in this region of variable rainfall.
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James, Allan R. "Remote sensing of seasonal variations in albedo over southern Britain." Thesis, University of Nottingham, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.278922.

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Linnard, David Simon. "Long range seasonal weather prediction : data analysis and numerical experiments." Thesis, University of Exeter, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.237875.

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Collins, Jennifer Mary. "Seasonal environmental conditions related to tropical cyclone activity in the Northeast Pacific Basin." Thesis, University College London (University of London), 2002. http://discovery.ucl.ac.uk/1317673/.

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This thesis presents the first in-depth study on interannual tropical cyclone activity in the Northeast (NE) Pacific, using statistical methods to investigate tropical cyclone frequency and its relationship with seasonal environmental conditions from 1972 to 1997. An improved method of calculating wind shear is first presented. It is demonstrated that the NE Pacific has more than one population of tropical cyclones with regard to causal factors, and tropical cyclones in the two regions show large differences in trends with time and in their relationships with environmental variables. Large increasing trends are found in the western development region (10˚N to 20˚N , 116˚W to 180˚W), with no significant trends in the eastern development region (10˚N to 20˚N, < 116˚W). No significant relationships were found in the eastern development region between tropical cyclone frequency and any of the environmental variables tested, except outgoing long-wave radiation, implying that the main causal factor here is triggering disturbances and their variations. However, in the western development region, some highly significant relationships exist. Important local variables there include relative humidity (RH) and SST. El Niño Southern Oscillation (ENSO) is also a significant factor. The local relationships are probably largely due to the intensity-frequency effect and the spatial averaging of the variables, with threshold effects acting locally to provide conducive/non-conducive conditions in different parts of the region. Physical influences on the most important of these variables (RH) are investigated. (The reverse influence, of hurricanes on RH, is shown to be negligible. ) RH is shown to be significantly influenced, via the wind field, by ENSO and the intensity of the thermal low in North America. ENSO influences provide significant inverse relationships between tropical cyclone frequencies in the western development region and the North Atlantic.
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Lawal, Kamoru Abiodun. "Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models." Doctoral thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16556.

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Includes bibliographical references
A good understanding of seasonal climate and the limit to which it can be predicted is crucial in addressing various socio-economic challenges in Africa. However, how to improve the capability of the dynamical models of the climate system in reproducing the regional seasonal climate variability and in replicating the role of various atmospheric circulation anomalies on the regional variability remains a major challenge. Thus far, understanding of seasonal climate over these regions, as well as the ability of climate models to predict them, has focused on the agreement of simulations of dynamical models of the climate system, rather than considering outliers as potentially vital contributors to understanding and predictability. This thesis uses discrepancy in a large ensemble of climate simulations as a tool to investigate variability in dominant seasonal rainfall and temperature patterns (i.e. classes) over West and Southern Africa, to examine the capability of climate models in reproducing the variability, and to study the predictability of the seasonal climates over South Africa. The dominant classes of variability (of rainfall and maximum temperature fields) in both regions are examined based on the Self-Organizing Map (SOM) classifications. The sequences in which each class occurs cannot be linked simply to a single common index of global scale atmospheric circulation anomalies, implying that the chaotic regional atmospheric circulations that modulate the global scale modes of variability are indispensable. The climate model examined adequately reproduces the dominant classes of seasonal climate over West and Southern Africa.
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Sandery, Paul Anthony, and paul sandery@flinders edu au. "Seasonal Variability of Water Mass Properties in Bass Strait: Three-dimensional oceanographic modelling studies." Flinders University. Chemistry, Physics and Earth Sciences, 2007. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20070831.093503.

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The climatology of the seasonal cycle of water mass variation and transformation in Bass Strait, south-eastern Australia, is studied using a high resolution three-dimensional sigma-coordinate hydrodynamic model coupled with data from observations and previous studies. Model forcing consists of the principal tidal constituents from the Australian National Tidal Centre and long-term monthly mean atmospheric forcing fields from NCEP reanalysis. The initial density field is established using temperature and salinity means and annual and semi-annual harmonics from the CARS2000 hydrographic atlas. This is also used to prescribe incoming water mass properties at model open-sea boundaries with seasonal variation. Far-field forcing is included with open-sea boundary parameterisation of residual sea-level representing both the South Australian Current and the East Australian Current. Lagrangian and Eulerian tracer methods are used to derive transport timescales, such as age, residence times and flushing times. These are used to examine and summarise model predictions and as a diagnostic tool in sensitivity studies. Currents, sea-level and water mass properties in the model compare favourably with previous studies and observations, despite limitations in the model and in the data used for comparison. The seasonal cycle, in model results, is characterised by formation of a shallow (< 20 m) saltier surface-layer in late spring to summer and subsequent downward mixing and erosion of the salinity field in autumn to winter with water mass from the west. This leaves behind water mass with positive age and salinity anomalies in areas of low flushing. In late winter-early spring most parts of this water mass leave the Strait interior. These areas are thought to be related to the source water of the Bass Strait Cascade. The residual circulation in all model experiments is shown to be related to seasonal-mean sea-level anomalies, arising from both barotropic and baroclinic adjustment, both in and surrounding the Strait.
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Van, Cooten Suzanne. "Statistical Analysis of Seasonal Precipitation for the Lake Pontchartrain Basin and Associated Watersheds." ScholarWorks@UNO, 2005. http://scholarworks.uno.edu/td/154.

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To investigate seasonal patterns of precipitation, statistical analysis was performed on a dataset of daily rainfall observed at 63 south Louisiana stations from 1836 to 2002. Each station record was examined for data quality and continuity with special attention to time periods surrounding station relocation or equipment exchange. Mean Areal Precipitation (MAP) sheets were compiled for every month from 1836 to 2002 to document the daily rainfall across south Louisiana and neighboring portions of southern and coastal Mississippi. Using these MAP sheets, missing data was examined to see if a reasonable value could be substituted to extend the continuity of a station's rainfall record. Once these data quality and continuity checks were completed, a series of statistical tests were conducted to determine an accurate scheme to form station groups. To group stations together, each station was required to have a normal distribution of monthly average rainfall, a statistically equivalent variance, and a statistically equivalent mean when compared with other stations in the group. As a result of the Shapiro-Wilk Test, the F-Test, and the Student T-test, eight station groups were formed. To define seasonal rainfall patterns across south Louisiana, statistical tests were conducted for a 12 month period and six and three month intervals. For the six month intervals, group rainfall averages and pooled variances were calculated for each interval beginning with January-July and ending with December-May. For the three month intervals, group rainfall averages and pooled variances were calculated for January-March and concluded with December-February. To test the hypothesis of a statistically significant difference in mean rainfall between the eight groups for a 12, six, and three month period, the Student T-test was conducted. For an annual basis, there is a statistically significant difference in average rainfall at a five percent level of significance between all of the groups except the Southshore (S.S) group when compared to the SW1 group. For six and three month intervals, statistically significant differences exist between the eight groups especially during winter and segments of the Hurricane season from June to November.
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Malin, Melissa L. "Teleconnection pattern impacts on intra-seasonal climate variability in United States winters." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 244 p, 2009. http://proquest.umi.com/pqdweb?did=1891555391&sid=3&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Maitaria, Kazungu. "ENABLING HYDROLOGICAL INTERPRETATION OF MONTHLY TO SEASONAL PRECIPITATION FORECASTS IN THE CORE NORTH AMERICAN MONSOON REGION." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/193926.

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The aim of the research undertaken in this dissertation was to use medium-range to seasonal precipitation forecasts for hydrologic applications for catchments in the core North American Monsoon (NAM) region. To this end, it was necessary to develop a better understanding of the physical and statistical relationships between runoff processes and the temporal statistics of rainfall. To achieve this goal, development of statistically downscaled estimates of warm season precipitation over the core region of the North American Monsoon Experiment (NAME) were developed. Currently, NAM precipitation is poorly predicted on local and regional scales by Global Circulation Models (GCMs). The downscaling technique used here, the K-Nearest Neighbor (KNN) model, combines information from retrospective GCM forecasts with simultaneous historical observations to infer statistical relationships between the low-resolution GCM fields and the locally-observed precipitation records. The stochastic nature of monsoon rainfall presents significant challenges for downscaling efforts and, therefore, necessitate a regionalization and an ensemble or probabilistic-based approach to quantitative precipitation forecasting. It was found that regionalization of the precipitation climatology prior to downscaling using KNN offered significant advantages in terms of improved skill scores.Selected output variables from retrospective ensemble runs of the National Centers for Environmental Predictions medium-range forecast (MRF) model were fed into the KNN downscaling model. The quality of the downscaled precipitation forecasts was evaluated in terms of a standard suite of ensemble verification metrics. This study represents the first time the KNN model has been successfully applied within a warm season convective climate regime and shown to produce skillful and reliable ensemble forecasts of daily precipitation out to a lead time of four to six days, depending on the forecast month.Knowledge of the behavior of the regional hydrologic systems in NAM was transferred into a modeling framework aimed at improving intra-seasonal hydrologic predictions. To this end, a robust lumped-parameter computational model of intermediate conceptual complexity was calibrated and applied to generate streamflow in three unregulated test basins in the core region of the NAM. The modeled response to different time-accumulated KNN-generated precipitation forcing was investigated. Although the model had some difficulty in accurately simulating hydrologic fluxes on the basis of Hortonian runoff principles only, the preliminary results achieved from this study are encouraging. The primary and most novel finding from this study is an improved predictability of the NAM system using state-of-the-art ensemble forecasting systems. Additionally, this research significantly enhanced the utility of the MRF ensemble forecasts and made them reliable for regional hydrologic applications. Finally, monthly streamflow simulations (from an ensemble-based approach) have been demonstrated. Estimated ensemble forecasts provide quantitative estimates of uncertainty associated with our model forecasts.
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Books on the topic "Seasonal climatology"

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Lofgren, Brent Melvin. Seasonal climatology of surface energy fluxes on the Great Lakes. Ann Arbor, Mich: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Great Lakes Environmental Research Laboratory, 1999.

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Hansen, Donald V. A seasonal isotherm depth climatology for the eastern tropical Pacific. Miami, Fla: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Atlantic Oceanographic and Meteorological Laboratory, 1988.

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1921-, Douglas A. S., ed. Seasonal variation in health and diseases: With sections on effects of weather and temperature : a bibliography. London: Mansell Pub., 1994.

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Kasper, Siegfried. Jahreszeit und Befindlichkeit in der Allgemeinbevölkerung: Eine Mehrebenenuntersuchung zur Epidemiologie, Biologie und therapeutischen Beeinflussbarkeit (Lichttherapie) saisonaler Befindlichkeitsschwankungen. Berlin: Springer-Verlag, 1991.

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Keane, T. Meteorological support systems for the control of foot-and-mouth disease of animals. Dublin: Met Eireann, 1998.

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Weijing, Li, ed. Zhongguo ji ping jun wen du ji jiang shui liang bai fen bi ju ping tu ji: 1880-2007 = Atlas of seasonal temperature and precipitation anomalies over China : 1880-2007. Beijing Shi: Qi xiang chu ban she, 2009.

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Boyle, James S. Monthly and seasonal climatology of the northern winter over the global tropics and subtropics for the decade 1974 to 1983: Surface winds. Monterey, Calif: Naval Postgraduate School, 1986.

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Boyle, James S. Monthly and seasonal climatology of the northern winter over the global tropics and subtropics for the period 1974 to 1983: 700 mb winds. Monterey, Calif: Naval Postgraduate School, 1986.

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National Research Council (U.S.). Panel to Review CCSP Draft Synthesis and Assessment Product 5.3: Decision-Support Experiments and Evaluations Using Seasonal to Interannual Forecasts and Observational Data. Review of CCSP draft synthesis and assessment product 5.3: Decison- support experiments and evaluations using seasonal to interannual forecasts and observational data. Washington, D.C: National Academies Press, 2008.

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Assel, Raymond A. Lake Superior cooling season temperature climatology. Ann Arbor, Mich: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1985.

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Book chapters on the topic "Seasonal climatology"

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Garinger, Linda Pickett, and Kevin R. Knupp. "Seasonal tornado climatology for the southeastern United States." In Geophysical Monograph Series, 445–52. Washington, D. C.: American Geophysical Union, 1993. http://dx.doi.org/10.1029/gm079p0445.

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Aubrey, David G., and Carl T. Friedrichs. "Seasonal Climatology of Tidal Non-Linearities in a Shallow Estuary." In Hydrodynamics and Sediment Dynamics of Tidal Inlets, 103–24. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4757-4057-8_6.

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Aubrey, David G., and Carl T. Friedrichs. "Seasonal climatology of tidal non-linearities in a shallow estuary." In Hydrodynamics and Sediment Dynamics of Tidal Inlets, 103–24. Washington, D. C.: American Geophysical Union, 1988. http://dx.doi.org/10.1029/ln029p0103.

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Katsafados, P., E. Papadopoulou, A. Papadopoulos, and E. Mavromatidis. "Seasonal Forecasts for the 2010 Russian Heat Wave Using an Atmospheric General Circulation Model." In Advances in Meteorology, Climatology and Atmospheric Physics, 187–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29172-2_27.

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Hátún, Hjalmar, Anne Britt Sandø, Helge Drange, and Mats Bentsen. "Seasonal to decadal temperature variations in the Faroe—Shetland inflow waters." In The Nordic Seas: An Integrated Perspective Oceanography, Climatology, Biogeochemistry, and Modeling, 239–50. Washington, D. C.: American Geophysical Union, 2005. http://dx.doi.org/10.1029/158gm16.

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Kozar, Michael E., and Vasubandhu Misra. "Integrated Kinetic Energy in North Atlantic Tropical Cyclones: Climatology, Analysis, and Seasonal Applications." In Hurricane Risk, 43–69. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02402-4_3.

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Kervalishvili, Guram N., and Hermann Lühr. "Climatology of Air Upwelling and Vertical Plasma Flow in the Terrestrial Cusp Region: Seasonal and IMF-Dependent Processes." In Magnetic Fields in the Solar System, 293–329. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-64292-5_11.

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Koufos, G., T. Mavromatis, S. Koundouras, and N. M. Fyllas. "Viticulture: Climate Relationships in Greece and Impacts of Recent Climate Trends: Sensitivity to “Effective” Growing Season Definitions." In Advances in Meteorology, Climatology and Atmospheric Physics, 555–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29172-2_79.

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Mavromatis, T. "Climate-Cereal Crop Relationships in Greece and the Impacts of Recent Climate Trends: The Role of the Effective “Growing Season” Definition." In Advances in Meteorology, Climatology and Atmospheric Physics, 605–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29172-2_86.

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François, R., C. H. Pilskaln, and M. A. Altabet. "Seasonal Variation in the Nitrogen Isotopic Composition of Sediment Trap Materials Collected in Lake Malawi." In The Limnology, Climatology and Paleoclimatology of the East African Lakes, 241–50. Routledge, 2019. http://dx.doi.org/10.1201/9780203748978-13.

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Conference papers on the topic "Seasonal climatology"

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Kaestner, Martina, and Karl T. Kriebel. "Alpine cloud climatology: seasonal changes." In Satellite Remote Sensing, edited by David K. Lynch. SPIE, 1994. http://dx.doi.org/10.1117/12.196661.

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Golestani, Maziar, Palle Martin Jensen, and Henrik Kofoed-Hansen. "On the Influence of Atmospheric Stability on the Wave Climate in a Warm and Saline Water Body." In ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/omae2015-41766.

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Abstract:
This paper presents some of the challenges faced during a project aimed at preparing long-term wave climatology in the Persian/Arabian Gulf. Using the hourly CFSR wind fields as forcing, an attempt was made to produce a comprehensive hydrodynamic and sea state conditions data set. By comparing the wave results to various in-situ and satellite measurements, an obvious seasonal difference was observed. Wave conditions were well reproduced during winter while the wave height was generally overestimated and scattered during the summer period. After comparing the wind fields against measurements it was believed that other sources were playing an important role in wave growth and propagation. Based on available measurements, it was shown that in the summer period, where the air temperature is higher than the sea temperature, wave growth rate is lower than in the winter period. Similar real cases have been reported in some lakes, but the influence of atmospheric stability on wave climate in a relatively large sea like The Gulf has not been documented yet to the authors’ knowledge. This paper focuses on the importance of including atmospheric stability effects into wave modelling. In order to account for the stability effects, the friction velocity and surface roughness were modified in the 3rd generation wind-wave model, MIKE 21 SW, using the Monin-Obukhov similarity theory. Improvements were seen in the quality of modelled wave heights in the summer period. The Gulf is also highly affected by changes in the sea water density. The effects of varying water density on wave climate were also studied in this paper. In order to reproduce the best quality wave climatology in The Gulf, it was concluded that seasonal modelling is required and the effects of atmospheric stability should be included.
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