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1

Trends in mean maximum temperature, mean minimum temperature and mean relative humidity for Lautoka, Fiji during 2003-2013

Ghani S. S., Iqubal M. A., Prasad R., Deo A.

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2017

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Vol. 26, No. 4

415--422

EN

The current work observes the trends in Lautoka’s temperature and relative humidity during the period 2003–2013, which were analyzed using the recently updated data obtained from Fiji Meteorological Services (FMS). Four elements, mean maximum temperature, mean minimum temperature along with diurnal temperature range (DTR) and mean relative humidity are investigated. From 2003–2013, the annual mean temperature has been enhanced between 0.02 and 0.08°C. The heating is more in minimum temperature than in maximum temperature, resulting in a decrease of diurnal temperature range. The statistically significant increase was mostly seen during the summer months of December and January. Mean Relative Humidity has also increased from 3% to 8%. The bases of abnormal climate conditions are also studied. These bases were defined with temperature or humidity anomalies in their appropriate time sequences. These established the observed findings and exhibited that climate has been becoming gradually damper and heater throughout Lautoka during this period. While we are only at an initial phase in the probable inclinations of temperature changes, ecological reactions to recent climate change are already evidently noticeable. So it is proposed that it would be easier to identify climate alteration in a small island nation like Fiji.

2

The application of probability density function in modeling of wind speed on the Polish Batlic Coast

Czernecki B.

Meteorology Hydrology and Water Management. Research and Operational Applications

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2014

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Vol. 2, Iss. 2

23--33

EN

The aim of the research was to identify the potential for the use of probability density functions (PDF) in modeling of near-surface wind speed. The approaches of Empirical Orthogonal Functions (EOF) and Canonical Correlation Analysis (CCA) are used in combination with 2-parametric Weibull distribution. The downscaling model was built using a diagnosed relationship between sea level pressure (SLP) patterns over Europe and the Northern Atlantic and estimated monthly values of Weibull parameters at 9 stations along the Polish Baltic Coast. The obtained scale (A) and shape (k) parameters make it possible to describe temporal variations of wind fields and their theoretical probability values. This may have further application in the modeling of extreme wind speeds for seasonal forecasting, climate prediction or in historical reconstructions. The model evaluation was done separately for the calibration (1971-2000) and validation periods (2001-2010). The scale parameter was reconstructed reasonably, while there were some problematic issues with the shape parameter, especially in the validation period. The quality of the developed models is generally higher for the winter season, due to larger SLP gradients, whereas the results for the spring and summer seasons were less satisfactory. Despite this, the 99th percentile of theoretical wind speeds are in most cases satisfactory, due to the lesser importance of the shape parameter for typical distributions in the analyzed region.

3

Statistical downscaling of probability density function of daily precipitation on the Polish coast

Wójcik R., Pilarski M., Miętus M.

Meteorology Hydrology and Water Management. Research and Operational Applications

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2014

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Vol. 2, Iss. 1

27--36

EN

The aim of this study was to recognize the possibility of downscaling probability density function (PDF) of daily precipitation by means of canonical correlation analysis (CCA). Sea level pressure (SLP) over Europe and the North Atlantic was used as a predictor. A skilful statistical model could be used to generate projections of future changes of precipitation PDF driven by GCM (General Circulation Model) simulations. Daily precipitation totals from 8 stations located on the Polish coast of the Baltic Sea covering the period 1961-2010 were used to estimate the gamma distribution parameters, and only wet days (i.e. ≥0.1mm) were taken in the analysis. The results of the Kolmogorov-Smirnov test and comparison of empirical and theoretical (gamma-distributed) quantiles proved that gamma distribution gives a reliable description of daily precipitation totals. The validation of CCA models applied to gamma parameters revealed that the reliable reconstruction of precipitation PDF is possible only for average long-term conditions. In the case of individual months/seasons the agreement between empirical and reconstructed quantiles is poor. This study shows the potential of modelling of precipitation PDF, however efforts should be made to improve model performance by establishing more reliable links between regional forcing and the variability of the gamma parameters.

4

Zastosowanie metody statystycznego downscalingu do analizy prędkości wiatru na polskich stacjach brzegowych

Pilarski M., Jakusik E., Marosz M., Owczarek M., Miętus M.

Przegląd Geofizyczny

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2012

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Z. 1

59-71

PL

Celem analizy była ocena przydatności metod statystycznego downscalingu do opisu warunków anemometrycznych na polskim wybrzeżu. Za pomocą metod kanonicznych korelacji (Canonical Correlation Analysis - CCA) i analizy redundancyjnej RDA (Redundancy Analysis - RDA) skonstruowano 3 modele (z 3, 5 i 7 parami map) na podstawie okresu referencyjnego 1971-2000. Modele te opierają się na założeniu, w którym wybrany predyktor (regionalne pole baryczne) wymusza odpowiedź analizowanego elementu lokalnego (pola prędkości wiatru na polskich stacjach brzegowych). Skoncentrowano się na wybraniu spośród wymienionych modelu optymalnego, w którym warunki cyrkulacyjne determinują największą część zmienności pola prędkości wiatru. Ponadto do oceny modeli wzięto pod uwagę wartość współczynnika korelacji między serią pomiarową i zrekonstruowaną. Wyniki analizy wskazują, że modelem, który najlepiej identyfikuje relacje analizowanego elementu z regionalnym polem barycznym, jest model skonstruowany za pomocą metody CCA z 5 parami map kanonicznych. Model ten wyjaśnia największą część wariancji pola regionalnego spośród wszystkich opracowanych modeli (ok. 75%), a ilość tłumaczonej wariancji pola lokalnego jest jeszcze wyższa i wynosi 95%. Średni (ze wszystkich stacji) współczynnik korelacji między serią pomiarową a odtworzoną mówiący o wiarygodności modelu, wynosi ponad 0,30. Tak mała wartość współczynnika jest spowodowana brakiem dobrego odtwarzania przez model wysokich dobowych prędkości wiatru, co skutkuje znacznym niedoszacowaniem wariancji odtwarzanych serii. Ze względu na fakt, że w analizie spodziewanych zmian elementów meteorologicznych standardowym trybem postępowania jest integracja informacji w ogólniejszej skali czasowej, przeprowadzono agregację wartości dobowych do charakterystyk miesięcznych (średniej i kwantyla 90%). Wartości współczynników korelacji obliczone w skali miesięcznej w wartości średnich i ekstremalnych są zadowalające i na niektórych stacjach przekraczają 0,70.

EN

The aim of the analysis was the assessment of the applicability of the statistical-empirical down-scaling methods in the analysis of the anemometric conditions on the Polish coast. With the usage of Canonical Correlation Analysis (CCA) and Redundancy Analysis (RDA) three models were constructed (with 3, 5 and 7 pairs of maps) for 1971-2000 period. The models base on the assumption that chosen predictor (regional pressure field - SLP) triggers an answer of the analyzed variable (wind speed at Polish coastal stations). From those 3 models the focus was placed on the selection of the optimal one in which the circulation conditions determine most of the local field variability and also the correlation between the observed and reconstructed time series of analyzed elements are at reasonable level. The results confirm that the optimal model which identifies the relations between the regional and local variables was the model constructed with CCA method (5 canonical correlation maps used). This model explains most of the regional field (75%) and the amount of wind speed's explained variance exceeds 95%. The average (for all the stations) correlation coefficient exceeds Q.3Q. Such low values of coefficients is the result of weak ability to reconstruct high speed wind values. However the standard time scale in the future climate change scenarios is the integration of information on longer timescales. Such analysis was added and it seems that the correlation between averages and extremes of wind speed in monthly scale are much better and for some stations exceed Q.7Q.