scholarly journals Surface Temperature Variations in East Africa and Possible Causes

2009 ◽  
Vol 22 (12) ◽  
pp. 3342-3356 ◽  
Author(s):  
John R. Christy ◽  
William B. Norris ◽  
Richard T. McNider
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
East Africa ◽  
Mount Kilimanjaro ◽  
Uncertainty Estimates ◽  
Break Points ◽  
The Difference ◽  
Boundary Layer Dynamics ◽  
Climate Analysis

Abstract Surface temperatures have been observed in East Africa for more than 100 yr, but heretofore have not been subject to a rigorous climate analysis. To pursue this goal monthly averages of maximum (TMax), minimum (TMin), and mean (TMean) temperatures were obtained for Kenya and Tanzania from several sources. After the data were organized into time series for specific sites (60 in Kenya and 58 in Tanzania), the series were adjusted for break points and merged into individual gridcell squares of 1.25°, 2.5°, and 5.0°. Results for the most data-rich 5° cell, which includes Nairobi, Mount Kilimanjaro, and Mount Kenya, indicate that since 1905, and even recently, the trend of TMax is not significantly different from zero. However, TMin results suggest an accelerating temperature rise. Uncertainty estimates indicate that the trend of the difference time series (TMax − TMin) is significantly less than zero for 1946–2004, the period with the highest density of observations. This trend difference continues in the most recent period (1979–2004), in contrast with findings in recent periods for global datasets, which generally have sparse coverage of East Africa. The differences between TMax and TMin trends, especially recently, may reflect a response to complex changes in the boundary layer dynamics; TMax represents the significantly greater daytime vertical connection to the deep atmosphere, whereas TMin often represents only a shallow layer whose temperature is more dependent on the turbulent state than on the temperature aloft. Because the turbulent state in the stable boundary layer is highly dependent on local land use and perhaps locally produced aerosols, the significant human development of the surface may be responsible for the rising TMin while having little impact on TMax in East Africa. This indicates that time series of TMax and TMin should become separate variables in the study of long-term changes.

scholarly journals Comparison of aerosol properties from the Indian Himalayas and the Indo-Gangetic plains

2011 ◽  
Vol 11 (4) ◽  
pp. 11417-11453 ◽  
Author(s):  
T. Raatikainen ◽  
A.-P. Hyvärinen ◽  
J. Hatakka ◽  
T. S. Panwar ◽  
R. K. Hooda ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Monsoon Season ◽  
Data Sets ◽  
New Delhi ◽  
Gangetic Plains ◽  
Diurnal Cycles ◽  
Measurement Site ◽  
Background Measurement ◽  
The Difference ◽  
Boundary Layer Dynamics

Abstract. Gual Pahari is a polluted semi-urban background measurement site at the Indo-Gangetic plains close to New Delhi and Mukteshwar is a relatively clean background measurement site at the foothills of the Himalayas about 270 km NE from Gual Pahari and about 2 km above the nearby plains. Two years long data sets including aerosol and meteorological parameters as well as modeled backward trajectories and boundary layer heights were compared. The purpose was to see how aerosol concentrations vary between clean and polluted sites not very far from each other. Specifically, we were exploring the effect of boundary layer evolution on aerosol concentrations. The measurements showed that especially during the coldest winter months, aerosol concentrations are significantly lower in Mukteshwar. On the other hand, the difference is smaller and also the concentration trends are quite similar from April to October. With the exception of the monsoon season, when rains are affecting on aerosol concentrations, clear but practically opposite diurnal cycles are observed. When the lowest daily aerosol concentrations are seen during afternoon hours in Gual Pahari, there is a peak in Mukteshwar aerosol concentrations. In addition to local sources and long-range transport of dust, boundary layer dynamics can explain the observed differences and similarities. When mixing of air masses is limited during the relatively cool winter months, aerosol pollutions are accumulated to the plains, but Mukteshwar is above the pollution layer. When mixing increases in the spring, aerosol concentrations are increased in Mukteshwar and decreased in Gual Pahari. The effect of mixing is also clear in the diurnal concentration cycles. When daytime mixing decreases aerosol concentrations in Gual Pahari, those are increased in Mukteshwar.

scholarly journals A Nonparametric Approach to the Removal of Documented Inhomogeneities in Climate Time Series

2013 ◽  
Vol 52 (5) ◽  
pp. 1139-1146 ◽  
Author(s):  
Chiara Ambrosino ◽  
Richard E. Chandler
Keyword(s):  
Time Series ◽  
Reanalysis Data ◽  
Climate Data ◽  
Nonparametric Approach ◽  
Satellite Technology ◽  
Abrupt Changes ◽  
Regression Framework ◽  
Climate Time Series ◽  
Climate Analysis

AbstractClimate data often suffer from artificial inhomogeneities, resulting from documented or undocumented events. For a time series to be used with confidence in climate analysis, it should only be characterized by variations intrinsic to the climate system. Many methods (e.g., direct or indirect) have been proposed according to the data characteristics (e.g., location, variable, or data completeness). This paper is focused on the abrupt-changes problem (when the properties of a time series change abruptly), when their timing is known, and suggests that a nonparametric regression framework provides an appealing way to correct for discontinuities in such a way as to recognize and allow for the existence of other structures such as seasonality and long-term smooth trends. The approach is illustrated by using reanalysis data for southern Africa, for which discontinuities are present because of the introduction of satellite technology in 1979.

The FDR4ATMOS Project

2020 ◽  
Author(s):  
Günter Lichtenberg ◽  
Sander Slijkhuis ◽  
Mourad Hamidouche ◽  
Melanie Coldewey-Egbers ◽  
Bernd Aberle ◽  
...  
Keyword(s):  
Time Series ◽  
Phase 1 ◽  
Atmospheric Composition ◽  
Data Preservation ◽  
Uncertainty Estimates ◽  
Data Record ◽  
Level 1 ◽  
Level 2 ◽  
Total Column

<p>The Fundamental Data Record for ATMOSpheric Composition (FDR4ATMOS) project is part of the ESA Long Term Data Preservation (LTDP) programme aimed at the preservation and valorization of data assets from ESA’s Earth Observation (EO) Heritage Missions. It has two objectives. The first one is to update the SCIAMACHY processing chain for better Ozone total column data. After the full re-processing of the SCIAMACHY mission with the updated processor versions 9 (Level 1) and version 7 (Level 2), ground-based validation showed that the total Ozone column drifted downward by nearly 2% over the mission lifetime. This drift is likely caused by changes in the degradation correction in the Level 1 processor, that led to subtle changes in the spectral structures. These are misinterpreted as an atmospheric signature. FDR4ATMOS will update the Level 0-1 processor accordingly with the final aim of a mission re-processing.</p><p>The main objective of the FDR4ATMOS project is to develop a cross-instrument Level 1 product for GOME-1 and SCIAMACHY for the UV, VIS and NIR spectral range, with focus on the spectral windows used for O3, SO2, NO2 total column retrieval and the determination of cloud properties. Contrary to other projects, FDR4ATMOS does not aim to build harmonised time series based on Level 2 products (geophysical parameters) but to build a Fundamental Data Record (FDR) of Level 1 products, i.e. radiances and reflectances. The GOME-1 and SCIAMACHY instruments together span 17 years of spectrally highly resolved data essential for air quality, climate, ozone trend and UV radiation applications. The goal of the FDR4ATMOS project is to generate harmonised data sets that allow the user to use it directly in long-term trend analysis, independently of the instrument. Since this was never done for highly resolved spectrometers, new methods have to be developed that e.g. take into account the different observation geometries and observation times of the instrument without impacting the spectral structures that are used for the retrieval of the atmospheric species. The resulting algorithms and the processor should also be as generic as possible to be able to easily transfer the methodology to other instruments (e.g. GOME-2 and Sentinel-5p) for a future extension of the time series. The project will support new applications and services and will enhance traceability of satellite-derived data with improved uncertainty estimates based on rigorous metrological principles.</p><p>FDR4ATMOS started in October 2019 and is currently in phase 1. We will present the motivation, goals and first results of the project.</p><p><br><br></p>

scholarly journals Turbulent transport of energy across a forest and a semiarid shrubland

2018 ◽  
Vol 18 (13) ◽  
pp. 10025-10038 ◽  
Author(s):  
Tirtha Banerjee ◽  
Peter Brugger ◽  
Frederik De Roo ◽  
Konstantin Kröniger ◽  
Dan Yakir ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Turbulent Transport ◽  
Surface Heterogeneity ◽  
Flux Divergence ◽  
Diurnal Cycles ◽  
Turbulent Statistics ◽  
Secondary Circulations ◽  
The Difference ◽  
Boundary Layer Dynamics

Abstract. The role of secondary circulations has recently been studied in the context of well-defined surface heterogeneity in a semiarid ecosystem where it was found that energy balance closure over a desert–forest system and the structure of the boundary layer was impacted by advection and flux divergence. As a part of the CliFF (“Climate feedbacks and benefits of semi-arid forests”, a collaboration between KIT, Germany, and the Weizmann Institute, Israel) campaign, we studied the boundary layer dynamics and turbulent transport of energy corresponding to this effect in Yatir Forest situated in the Negev Desert in Israel. The forest surrounded by small shrubs presents a distinct feature of surface heterogeneity, allowing us to study the differences between their interactions with the atmosphere above by conducting measurements with two eddy covariance (EC) stations and two Doppler lidars. As expected, the turbulence intensity and vertical fluxes of momentum and sensible heat are found to be higher above the forest compared to the shrubland. Turbulent statistics indicative of nonlocal motions are also found to differ over the forest and shrubland and also display a strong diurnal cycle. The production of turbulent kinetic energy (TKE) over the forest is strongly mechanical, while buoyancy effects generate most of the TKE over the shrubland. Overall TKE production is much higher above the forest compared to the shrubland. The forest is also found to be more efficient in dissipating TKE. The TKE budget appears to be balanced on average both for the forest and shrubland, although the imbalance of the TKE budget, which includes the role of TKE transport, is found to be quite different in terms of diurnal cycles for the forest and shrubland. The difference in turbulent quantities and the relationships between the components of TKE budget are used to infer the characteristics of the turbulent transport of energy between the desert and the forest.

scholarly journals Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1842 ◽  
Author(s):  
Christof Lorenz ◽  
Carsten Montzka ◽  
Thomas Jagdhuber ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
High Resolution ◽  
Brightness Temperature ◽  
Spatial Resolution ◽  
Prediction Models ◽  
Weather Prediction ◽  
Brightness Temperatures ◽  
Climate Analysis

Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture satellite missions SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) are able to provide soil moisture estimates on global scales and in kilometer accuracy. However, the SMOS data record has an appropriate length of 7.5 years since late 2009, but with a coarse resolution of ∼25 km only. In contrast, a spatially-enhanced SMAP product is available at a higher resolution of 9 km, but for a shorter time period (since March 2015 only). Being the fundamental observable from passive microwave sensors, reliable brightness temperatures (Tbs) are a mandatory precondition for satellite-based soil moisture products. We therefore develop, evaluate and apply a copula-based data fusion approach for combining SMAP Enhanced (SMAP_E) and SMOS brightness Temperature (Tb) data. The approach exploits both linear and non-linear dependencies between the two satellite-based Tb products and allows one to generate conditional SMAP_E-like random samples during the pre-SMAP period. Our resulting global Copula-combined SMOS-SMAP_E (CoSMOP) Tbs are statistically consistent with SMAP_E brightness temperatures, have a spatial resolution of 9 km and cover the period from 2010 to 2018. A comparison with Service Soil Climate Analysis Network (SCAN)-sites over the Contiguous United States (CONUS) domain shows that the approach successfully reduces the average RMSE of the original SMOS data by 15%. At certain locations, improvements of 40% and more can be observed. Moreover, the median NSE can be enhanced from zero to almost 0.5. Hence, CoSMOP, which will be made freely available to the public, provides a first step towards a global, long-term, high-resolution and multi-sensor brightness temperature product, and thereby, also soil moisture.

scholarly journals Long-Term Performance Evaluation of Main Cable for Large Span Suspension Bridge Based on ARIMA Model

2021 ◽  
Author(s):  
Shiqiao Xu ◽  
Rujin Ma ◽  
Chuanjie Cui
Keyword(s):  
Time Series ◽  
Performance Evaluation ◽  
Arima Model ◽  
Engineering Research ◽  
Large Span ◽  
Main Cable ◽  
The Difference ◽  
Long Term Performance ◽  
Term Performance

Main cables are major load-bearing components and play a decisive role in the long-term performance of suspension bridges. In particular, the wide application of health monitoring systems in large-span bridges facilitates a new channel for the performance evaluation of bridges. Under this context, Xihoumen Bridge is taken as the engineering research background. The long-term performance of the bridge’s main cable was evaluated by analyzing the main cable strand force data from January 2015 to October 2020, which was collected by the anchor rope meter. Firstly, the difference calculation was performed on the basis of the modeling theory of stationary time series to realize the stationary process of the original time series. Then, the Autoregressive Integrated Moving Average (ARIMA) model is established to predict the main cable strand force of the Xihoumen Bridge by model order estimation and parameter identification. Finally, the load degree index is defined in the discussion part to evaluate the long-term performance and determine the performance grading of the main cable.

Techniques for the Study of Long-Term Dynamics: Analyzing Time Series

2021 ◽  
pp. 458-486
Author(s):  
Peter A. Henderson
Keyword(s):  
Time Series ◽  
Generation Time ◽  
Analytical Techniques ◽  
Population Number ◽  
Long Term Study ◽  
Scale Population ◽  
Annual Population ◽  
Break Points ◽  
Definition Of

The definition of ‘long-term’ requires reference to the generation time and the scale over which environmental variation of interest operates. A long-term (large temporal scale) population study of an annually reproducing insect would be expected to include annual population estimates over at least ten years. An equivalent study of an amoeba, which can reproduce daily, might be completed in a few weeks. However, if the focus of a long-term study is the role of seasonal variation in determining population number, then it is likely that a study will need at least twenty-five years of data, irrespective of the size of the organism and the generation time. This chapter reviews a range of time series analytical techniques and presents R code listings for measuring synchrony and species associations, detecting break-points in time series and measuring community stability. Statistical methods to assess if a species has gone extinct are described. Techniques for detecting density dependence in time series are reviewed. Temporal β‎-diversity is defined as the shift in the identities and/or the abundances of named taxa in a specified assemblage over two or more time points. The measurement of temporal β‎-diversity is discussed. Numerous R code listings are presented.

scholarly journals Northeast Atlantic Storm Activity and Its Uncertainty from the Late Nineteenth to the Twenty-First Century

2019 ◽  
Vol 32 (6) ◽  
pp. 1919-1931 ◽  
Author(s):  
Oliver Krueger ◽  
Frauke Feser ◽  
Ralf Weisse
Keyword(s):  
Time Series ◽  
Geostrophic Wind ◽  
Late Nineteenth Century ◽  
Activity Data ◽  
Storm Activity ◽  
Northeast Atlantic ◽  
The North ◽  
Uncertainty Estimates ◽  
Late Nineteenth

Geostrophic wind speeds calculated from mean sea level pressure readings are used to derive time series of northeast Atlantic storminess. The technique of geostrophic wind speed triangles provides relatively homogeneous long-term storm activity data and is thus suited for statistical analyses. This study makes use of historical air pressure data available from the International Surface Pressure Databank (ISPD) complemented with data from the Danish and Norwegian Meteorological Institutes. For the first time, the time series of northeast Atlantic storminess is extended until the most recent year available, that is, 2016. A multidecadal increasing trend in storm activity starting in the mid-1960s and lasting until the 1990s, whose high storminess levels are comparable to those found in the late nineteenth century, initiated debate over whether this would already be a sign of climate change. This study confirms that long-term storminess levels have returned to average values in recent years and that the multidecadal increase is part of an extended interdecadal oscillation. In addition, new storm activity uncertainty estimates were developed and novel insights into the connection with the North Atlantic Oscillation (NAO) are provided.

scholarly journals Latitudinal variation of <I>fo</I>F2 hysteresis of solar cycles 20, 21 and 22 and its application to the analysis of long-term trends

2008 ◽  
Vol 26 (5) ◽  
pp. 1269-1273 ◽  
Author(s):  
N. Ortiz de Adler ◽  
A. G. Elias
Keyword(s):  
Time Series ◽  
Solar Cycle ◽  
Geomagnetic Latitude ◽  
Activity Levels ◽  
Solar Cycles ◽  
Long Term Trends ◽  
The Difference ◽  
Long Term Trend ◽  
Term Data

Abstract. Noon foF2 monthly median values for equinoctial months of solar cycles 20, 21 and 22, were analyzed for 37 worldwide stations. For each solar cycle and for a given Rz, the difference between foF2 in the falling branch of the cycle and the corresponding value of the rising branch is evaluated. The maximum difference, considered as the hysteresis magnitude, varies systematically with geomagnetic latitude. The pattern is similar for every cycle, with greater hysteresis magnitudes for stronger solar cycles. It is positive between 45° S and 45° N, with minimum values at equatorial latitudes and maximum at around 25°–30° on either side of the equator. For latitudes greater than 50° negative values are observed. At around 25°–30° and at high latitudes the hysteresis magnitude reaches 2 MHz for solar cycle with high activity levels, which represents around 20% of foF2. The effects of foF2 hysteresis on the analysis of long-term data sequences is analyzed. In the case of long-term trend analysis, the hysteresis behavior may induce spurious trends as a consequence of the filtering processes applied to foF2 time series previous to trend values estimation. This problem may be solved by considering time series covering several solar cycles.

scholarly journals PENGARUH SUKU BUNGA, PRODUK DOMESTIK BRUTO DAN NILAI TUKAR TERHADAP EKSPOR DI INDONESIA

2019 ◽  
Vol 4 (2) ◽  
pp. 300-317
Author(s):  
Okta Rabiana Risma ◽  
T. Zulham ◽  
Taufiq C. Dawood
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Gross Domestic Product ◽  
Interest Rates ◽  
Time Series Data ◽  
Domestic Product ◽  
Series Data ◽  
Auto Regressive ◽  
The Difference

This research aims to analyze the level of exports in Indonesia by using Time Series data from the year 1990 to 2015 against a variable interest rate loands, gross domestic product, and the exchange rate. Methods of analysis used i.e, Auto Regressive Distributed Lagged (ARDL). The results showed that the three variables have no Granger which is caused by the difference of the order on the test stasioner. Based on a test of wald for the short term that gained and the long-term gross domestic product, exchange rates and interest rates significantly influential credit toward export.Keywords:ARDL, export, interest rate loands, gross domestic product, exchange rates.AbstrakPenelitian ini bertujuan untuk menganalisis tingkat ekspor di Indonesia dengan menggunakan data Time Series dari tahun 1990 sampai 2015 terhadap variabel suku bunga kredit, produk domestik bruto, dan nilai tukar. Metode analisis yang digunakan yaitu AutoRegressive Distributed Lagged (ARDL).Hasil penelitian menunjukkan bahwa ketiga variabel tidak memiliki kointegrasi yang disebabkan oleh perbedaan ordo pada uji stasionernya. Berdasarkan uji wald didapat bahwa untuk jangka pendek dan jangka panjang produk domestik bruto, nilai tukar dan suku bunga kredit berpengaruh secara signifikan terhadap ekspor.

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