Climatic Effects on GPS PPP Accuracy

2021 ◽  
Author(s):  
Aziz Saraçoğlu ◽  
Doğan Uğur Şanlı
Keyword(s):  
Gps Data ◽  
Core Network ◽  
International Gnss Service ◽  
Climatic Effects ◽  
Climate Classification ◽  
Climate Zones ◽  
Climate Zone ◽  
Session Duration ◽  
Initial Impressions

<p>Recently researchers revealed that meteorological seasons have an effect on the accuracy of GPS. This modified the conventional prediction formulation in which the accuracy was dependent on observing session duration. However, the available accuracy model is from a major climate zone classification. In this study, we evaluate climatic effects on PPP accuracy from a different climate classification: the widely used Köppen Geiger climate zones. GPS data are obtained from SOPAC (Scripps Orbit and Permanent Array Centre) archives. Synthetic GPS campaigns are generated from the permanent stations of the IGS (International GNSS Service). The data are processed using the PPP module of the NASA/JPL's GipsyX software. The RMS values obtained from the processing solutions are used to determine the effect of climate on PPP accuracy. Eventually, we compare the two climate classifications and present our initial impressions from a core network across the new climate zones.</p><p><strong>Keywords:</strong> GPS, GNSS, accuracy, PPP, climatic effects</p>

scholarly journals CLIMATE CHANGES AND LANDSCAPE RESPONSES OF CHINA DURING THE PAST 40 YEARS (1979–2018) UNDER KÖPPEN-GEIGER CLIMATE CLASSIFICATION

2020 ◽  
Vol V-3-2020 ◽  
pp. 731-737
Author(s):  
Y. Feng ◽  
S. Du
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climate Changes ◽  
Southern China ◽  
Cold Climate ◽  
Climate Classification ◽  
Climate Type ◽  
Climate Zones ◽  
Climate Zone ◽  
The Past

Abstract. Under the background of global warming, China with diverse climate types is experiencing dramatic climate change. In this study, we produced a series of climate type map of China at 0.1° resolution from 1979 to 2018 using Köppen-Geiger climate classification, which provided continuous fine-scale decadal climate classification data for climate researches in China. Based on these climate maps, we divided China into four main climate zones: arid climate zone located on the north of Tibetan Plateau and west of Inner Mongolian Plateau, temperate climate zones in southern China, cold climate zone occupied most of Northeast Plain and North China Plain, and polar climate zone on Tibetan Plateau. The distribution of main climate classes in China have not changed significantly over 40 years, while the climate change mainly occurs at the levels of climate type and subtype changes. The frequency of climate changes shows the climate sensitivity of the region, and we identified the transition areas of climate zones with a high sensitivity to climate change. The change of climate types shows an obvious trend of rising temperature in all climate zones of China and increasing precipitation in most climate zones of China (the cold climate zone shows no significant dry or wet change). Overall, the climate in China is generally getting warmer and wetter in the past 40 years. Furthermore, we analysed the landscape responses on climate change with land cover data, e.g. the vegetation type variations in southern China and the snow cover fluctuations on Tibetan Plateau.

scholarly journals Determinants of Electrical and Thermal Energy Consumption in Hospitals According to Climate Zones in Poland

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7585
Author(s):  
Małgorzata Cygańska ◽  
Magdalena Kludacz-Alessandri
Keyword(s):  
Energy Consumption ◽  
Thermal Energy ◽  
Health Sector ◽  
Integrated Approach ◽  
Climatic Zone ◽  
Energy Costs ◽  
Work Intensity ◽  
Climate Zones ◽  
Climate Zone ◽  
Hospital Size

Energy use in hospitals is higher than in other public buildings, so improving energy efficiency in healthcare buildings is a significant challenge in this sector of engineering. For this, it is necessary to know the various determinants of energy consumption. Until now, the main factor affecting energy consumption in healthcare facilities studied in the literature was hospital capacity. However, the commonly used variables connected with hospital size and the number of beds do not take into account the medical activities carried out in these buildings. Assuming that energy consumption in hospitals is multiple and shaped by many factors that overlap, not only on an individual level but also on a higher scale level, this study devises a more integrated approach to its determinants. This study aims to investigate the determinants of electrical energy costs (EEC) and thermal energy costs (TEC) in Polish hospitals with regard to factors related to their size, work intensity and climate zones. The analysis was carried out using financial and resource data from all Polish hospitals for the years 2010–2019. The study used a multivariate backward stepwise regression analysis. In order to use climate as a moderating variable, a sample of Polish hospitals from 16 Polish NUTS 2 was divided into four climate zones. This article provides new empirical evidence on the determinants of electricity consumption in Polish hospitals related to their size and medical activity, taking into account climate zone as a moderating variable. The results of the analysis show that both electricity and heat consumption in hospitals are positively related to the number of doctors, beds and the number of medical operations performed. As expected, larger hospitals seem to use more energy. Moreover, there is regional heterogeneity in energy consumption in hospitals related to the climatic zone in which they operate. The conducted analysis shows that Polish hospitals located in the warmest climatic zone are characterized by higher energy consumption than hospitals in the coldest zone. It especially regards EEC in surgery hospitals. The warmer the climate zones, the higher intensity in terms of the number of surgeries, the higher EEC. In terms of nonsurgical hospitals, the influence of climate zone on EEC was not observed. Knowing the factors influencing energy consumption in hospitals can facilitate the correct adoption of an energy-saving strategy in the health sector, which is a reasonable response to climate change and supports a healthy and sustainable future.

scholarly journals Tropospheric NO<sub>2</sub> concentrations over West Africa are influenced by climate zone and soil moisture variability

2017 ◽  
Author(s):  
Ajoke R. Onojeghuo ◽  
Heiko Balzter ◽  
Paul S. Monks
Keyword(s):  
Soil Moisture ◽  
West Africa ◽  
Linear Regression Models ◽  
Climate Zones ◽  
Climate Zone ◽  
Annual Cycles ◽  
Causality Tests ◽  
Arid Desert ◽  
Soil Moisture Variability ◽  
Moisture Variability

Abstract. The annual cycles of soil moisture and NO2 have been analysed across the climate zones of West Africa using two satellite data sets (OMI on AURA and ASCAT on MetOp-A). Exploring the sources and sinks for NO2 it is clear that the densely populated urban cities including Lagos and Abuja had the highest mean NO2 concentrations (> 1.8 × 1015 molecules cm−2) indicative of the anthropogenic urban emissions. The data analysis shows that rising soil moisture levels may influence the sink of NO2 concentrations after the biomass burning. The results also show significant soil moisture changes in areas of high humidity especially in the east equatorial monsoon climate zone where most of the Niger delta is located (4 %/yr.). A decline in NO2 (0.9 %/yr.) was also observed in this climate zone. Beyond seasonal linear regression models, climate based Granger’s causality tests show that tropospheric NO2 concentrations from soil emissions in the arid steppe (Sahel) and arid desert climate zones of West Africa are significantly affected by soil moisture variability (F > 10, p  0.8 %/yr). The results demonstrate the critical sensitivity of the West African emissions of NO2 on soil moisture and climate zone.

Shifts of climate zones in multi-model climate change experiments using the Köppen climate classification

2012 ◽  
Vol 21 (2) ◽  
pp. 111-123 ◽  
Author(s):  
Franziska Hanf ◽  
Janina Körper ◽  
Thomas Spangehl ◽  
Ulrich Cubasch
Keyword(s):  
Climate Change ◽  
Climate Classification ◽  
Climate Zones ◽  
Köppen Climate Classification

scholarly journals REVISITING THE ROLE OF OBSERVATION SESSION DURATION ON PRECISE POINT POSITIONING ACCURACY USING GIPSY/OASIS II SOFTWARE

2016 ◽  
Vol 22 (3) ◽  
pp. 405-419 ◽  
Author(s):  
Adem G. Hayal ◽  
D. Ugur Sanli
Keyword(s):  
Precise Point Positioning ◽  
Accuracy Assessment ◽  
Relative Positioning ◽  
International Gnss Service ◽  
Session Duration ◽  
Previous Formulation ◽  
Single Station ◽  
Analysis Strategies ◽  
Point Positioning

The accuracy of GPS precise point positioning (PPP) was previously modelled as a function of the observing session duration T. The NASA, JPL's software GIPSY OASIS II (GOA-II) along with the legacy products was used to process the GPS data. The original accuracy model is not applicable anymore because JPL started releasing its products using new modelling and analysis strategies as of August 2007, and the legacy products are no longer available. The developments mainly comprise the new orbit and clock determination strategy, second order ionosphere modelling, and single station ambiguity resolution. Previously, the PPP accuracy was studied using v 4.0 of the GOA-II. The accuracy model showed coarser results compared to that of the relative positioning. Here, we processed the data of the International GNSS Service (IGS) stations to refine the accuracy of GOA-II PPP from version 6.3. Considering the above changes we refined the accuracy of PPP. First we modified the previous model used for the accuracy assessment. Then we tested out this model using straightforward polynomial and logarithmic models. The tests indicate the previous formulation still satisfactorily models the accuracy using refined coefficient values Sn = 7.8 mm , Se = 6.8 mm , Sv = 29.9 mm for T ≥ 2 h.

scholarly journals Germination rates of four Chilean forest trees seeds: Quillaja saponaria, Prosopis chilensis, Vachellia caven, and Caesalpinia spinosa

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1446
Author(s):  
Âlvaro Plaza ◽  
Miguel Castillo
Keyword(s):  
Tree Species ◽  
Mediterranean Climate ◽  
Broad Sense ◽  
Native Forest ◽  
Forest Trees ◽  
Forest Research ◽  
Climate Zones ◽  
Climate Zone ◽  
Quillaja Saponaria ◽  
Prosopis Chilensis

Data on the germination rates of four tree species, natively founded in the Chilean Mediterranean-climate zone, were determined by germination in crop chambers. The obtained data were used to interpolate or extrapolate the time taken for 50% of seeds to germinate in each case. These results are useful for regional native forest research and, in a broad sense, for its use in models to study germination dynamics in Mediterranean-climate zones.

Long-term dynamics of thermal comfort in the territories of the Krasnoyarsk region climate belts

2021 ◽  
pp. 38-45
Author(s):  
Rofail Salykhovich Rakhmanov ◽  
Denis Alekseevich Narutdinov ◽  
Elena Sergeevna Bogomolova ◽  
Natalya Nikolaevna Potekhina ◽  
Sergey Aleksandrovich Razgulin
Keyword(s):  
Risk Assessment ◽  
General Population ◽  
Health Risk ◽  
Thermal Comfort ◽  
Effective Temperature ◽  
Climate Zones ◽  
Climate Zone ◽  
Subarctic Climate ◽  
Continental Climate

Health risk assessment in the general population in different climate zones of the Krasnoyarsk Territory by the equivalent effective temperature (EET). The average monthly EET according to Missenard was calculated, their dynamics and health risk were assessed within two periods of determining climate norms for the last 10 years of each period (1961–1990 and 1991–2020). Within the period of 1991–2020 compared with the previous period in the subarctic climate in the summer months, EET had positive values (in opposition of 2 months in 1961–1990), increased in April by 7.87 °С (p = 0.0004), in June by 5.56 °С (p = 0.019) and October by 3.2 °С (p = 0.038); in continental climate zone — in April at 5.23 °С (p = 0.0001), in June at 3.88 °С (p = 0.0009) and in August at 1.32 °С (p = 0.023). Living conditions of the population have become more favorable, the nature of the health risk has changed. In the subarctic climate, the changes in uncomfortable conditions occurred according to the criteria of «frostbite threat» — «cold» (5 months against 6 months in the first period), «cool» — «moderately cool» (2 months against 3 months), «comfort, moderately warm. «In the continental climate zone, the changes were noted according to the criteria of «moderately warm» — «very cool» (7 months against 5 months). In both climate zones, positive changes have caused a decrease in health risk according to two criteria («the threat of frostbite»; «very cold»); there was a shift from the risk assessed as «cold»towards «comfort, moderately warm».

Defining Climate Zone of Borneo based on Cluster Analysis

2021 ◽  
Author(s):  
Zulfaqar Sa'adi ◽  
Shamsuddin Shahid ◽  
Mohammed Sanusi Shiru
Keyword(s):  
Regional Climate ◽  
Development Planning ◽  
Climate Classification ◽  
Climate Zones ◽  
Local Climate ◽  
Climate Conditions ◽  
Tropical Regions ◽  
Related Development ◽  
Climatic Characteristic

Abstract Although Borneo Island is one of the most vulnerable tropical regions to climate change, maps depicting the local climate conditions employing climate classification are still not well defined. The present study attempted regional climate classification to divide the Borneo region into several homogenous groups based on long-term average climate behavior. Daily gridded rainfall and temperature (Tavg, Tmax, and Tmin) data at 0.25o resolution spanning 56-years (1960−2016) was used. The classification was done using non-hierarchical k-mean and several hierarchical methods, namely, Single, Complete, McQuitty, Average, Centroid, Median, and two algorithms of Ward's method, wardD, and wardD2. The results showed that k-mean, wardD, and wardD2 were able to classify the climate of Borneo into four zones, namely 'Dry and hot' (DH), 'Wet and hot' (WH), 'Wet' (W), and 'Wet and cold' (WC) with a considerable difference at the boundaries. Spatial relevancy, stability, and variability of the clusters based on correlation and compromise programming showed that the wardD method was the most likely to yield acceptable results with optimum 4-cluster to partition the area into four principal climate zones. The constructed cluster plot, centroid plot, and probability distribution function (PDF) showed a distinct climatic characteristic between the climate zones in terms of rainfall, temperature, and seasonality. The proposed climate zonation for Borneo can help in better understanding climate regionality and climate-related development planning.

scholarly journals Identifying a Transition Climate Zone in an Arid River Basin using a Hydrological Drought Index

2018 ◽  
Author(s):  
Libo Zhang ◽  
Yongqiang Liu ◽  
Lu Hao ◽  
Decheng Zhou ◽  
Cen Pan ◽  
...  
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Heihe River Basin ◽  
Heihe River ◽  
Climate Classification ◽  
Climate Zone ◽  
Annual Variability ◽  
Hydrological Drought Index

Abstract. Drought indices have been widely used in climate classification. However, there is not enough evidence for their ability in identifying the multiple climate types in areas with complex topography and landscape, especially in those areas with a transition climate. This study compares a meteorological drought index, the aridity index (AI) defined as the ratio of precipitation (P) to potential evapotranspiration (PET), with a hydrological drought index, the evaporative stress index (ESI) defined as the ratio of actual evapotranspiration (AET) to PET. We conducted this study using modeled high resolution climate data for period of 1980–2010 in the Heihe River Basin (HRB) in the arid northwestern China. PET was estimated using the Penman–Monteith and Hamon methods. The climate classified by AI shows two distinct climate types for the upper and the middle and lower basin reaches, while three types were found if ESI was used. This difference indicates that only ESI is able to identify a transition climate zone in the middle basin. This contrast between the two indices is also seen in the inter-annual variability and extreme dry/wet events. The magnitude of variability in the middle basin is close to that in the lower basin for AI, but different for ESI. AI has larger magnitude of the relative inter-annual variability and greater decreasing rate from 1980–2010 than ESI, suggesting the role of local hydrological processes in moderating extreme climate events. Thus, the hydrological drought index is better than the meteorological drought index for climate classification in the arid Heihe River Basin where local climate is largely determined by topography and landscape. We conclude that the land–surface processes and human disturbances play an important role in altering hydrological drought conditions and their spatial and temporal variability.

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