scholarly journals Monitoring Climate Changes on Small Scale Networks Using Ground Based GPS and Meteorological Data

2014 ◽  
Vol 49 (3) ◽  
pp. 125-135 ◽  
Author(s):  
C. Pikridas
Keyword(s):  
Climate Model ◽  
Meteorological Data ◽  
Water Vapor Pressure ◽  
Small Scale ◽  
Tropospheric Delay ◽  
Time Interval ◽  
Data Set ◽  
Multiple Stepwise Regression Analysis ◽  
Delay Variations ◽  
Gps Station

Abstract The total zenith tropospheric delay (ZTD) and its components, hydrostatic and wet parts are important parameters of the atmosphere and directly or indirectly reflect climate processes. This possibility can be more adaptive when meteorological data are combined to co-located meteorological sensors with GPS stations. In this paper eighteen months with one hour time interval ZTD estimates of a permanent GPS station are analyzed with the associated atmospheric parameters provided from a co-located meteorological sensor. The mathematical relationship through the multiple stepwise regression analysis reflects the plausible physical link of temperature and relative humidity values with ZTD’s. This regression equation is assessed by a second data set performed by a small GPS baseline few months later for the same study area. It was found that mainly due to the zenith wet delay variations and with the help of fundamental meteorological equations the behavior of water vapor pressure can be monitored and estimated. This is possible when an appropriate setup of GPS stations and a co-located meteorological sensor exist and if the GPS stations sound the same part of atmosphere. Therefore, the GPS tropospheric products are good indicators for a climate monitoring tool and can help address the physics of a climate model.

scholarly journals Establishment of a Real-Time Local Tropospheric Fusion Model

2019 ◽  
Vol 11 (11) ◽  
pp. 1321 ◽  
Author(s):  
Yibin Yao ◽  
Xingyu Xu ◽  
Chaoqian Xu ◽  
Wenjie Peng ◽  
Yangyang Wan
Keyword(s):  
Real Time ◽  
Meteorological Data ◽  
Rapid Development ◽  
Water Vapor Pressure ◽  
Auxiliary Information ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Navigation Systems ◽  
Delay Model ◽  
Fusion Model

The tropospheric delay is one major error source affecting the precise positioning provided by the global navigation satellite system (GNSS). This error occurs because the GNSS signals are refracted while travelling through the troposphere layer. Nowadays, various types of model can produce the tropospheric delay. Among them, the globally distributed GNSS permanent stations can resolve the tropospheric delay with the highest accuracy and the best continuity. Meteorological models, such as the Saastamoinen model, provide formulae to calculate temperature, pressure, water vapor pressure and subsequently the tropospheric delay. Some grid-based empirical tropospheric delay models directly provide tropospheric parameters at a global scale and in real time without any auxiliary information. However, the spatial resolution of the GNSS tropospheric delay is not sufficient, and the accuracy of the meteorological and empirical models is relatively poor. With the rapid development of satellite navigation systems around the globe, the demand for real-time high-precision GNSS positioning services has been growing dramatically, requiring real-time and high-accuracy troposphere models as a critical prerequisite. Therefore, this paper proposes a multi-source real-time local tropospheric delay model that uses polynomial fitting of ground-based GNSS observations, meteorological data, and empirical GPT2w models. The results show that the accuracy in the zenith tropospheric delay (ZTD) of the proposed tropospheric delay model has been verified with a RMS (root mean square) of 1.48 cm in active troposphere conditions, and 1.45 cm in stable troposphere conditions, which is significantly better than the conventional tropospheric GPT2w and Saastamoinen models.

scholarly journals Simulations of future changes in thermal structure of Lake Erken: Proof of concept for ISIMIP2b lake sector local simulation strategy

2019 ◽  
Author(s):  
Ana I. Ayala ◽  
Simone Moras ◽  
Don C. Pierson
Keyword(s):  
Water Temperature ◽  
Climate Model ◽  
Thermal Structure ◽  
Meteorological Data ◽  
Time Step ◽  
Data Set ◽  
Lake Model ◽  
Hourly Data ◽  
Daily Time Step ◽  
Daily Time

Abstract. This paper, as a part of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b), assesses the impacts of different levels of global warming on the thermal structure of Lake Erken (Sweden). The GOTM one-dimensional hydrodynamic model was used to simulate water temperature when using ISIMIP2b bias-corrected climate model projections as input. These projections have a daily time step, while lake model simulations are often forced at hourly or shorter time steps. Therefore, it was necessary to first test the ability of GOTM to simulate Lake Erken water temperature using daily vs hourly meteorological forcing data. In order to do this three data sets were used to force the model: (1) hourly measured data; (2) daily average data derived from the first data set and; (3) synthetic hourly data created from the daily data set using Generalized Regression Artificial Neural Network methods. This last data set is developed using a method that could also be applied to the daily time step ISIMIP scenarios to obtain hourly model input if needed. The lake model was shown to accurately simulate Lake Erken water temperature when forced with either daily or synthetic hourly data. Long-term simulations forced with daily or synthetic hourly meteorological data suggest that by 2099 the lake will undergo clear changes in thermal structure, for RCP 2.6 surface water temperature was projected to increase from 0.87 to 1.48 °C and from 0.69 to 1.20 °C when the lake model was forced at daily and hourly resolutions respectively, and for RCP 6.0 these increases were projected to range from 1.58 to 3.58 °C and from 1.19 to 2.65 °C when the lake model was also forced at daily and hourly resolutions. Changes in lake stability were projected to increase significantly and the stratification duration was projected to be longer by 9 to 16 days and from 7 to 13 days under RCP 2.6 scenario and from 20 to 33 days and from 17 to 27 under RCP 6.0 scenario for daily and hourly resolutions. Model trends were very similar when using either the daily or synthetic hourly forcing, suggesting that the original climate model projections at a daily time step can be sufficient for the purpose of simulating water temperature in the lake sector in ISIMIP.

scholarly journals Simulations of future changes in thermal structure of Lake Erken: proof of concept for ISIMIP2b lake sector local simulation strategy

2020 ◽  
Vol 24 (6) ◽  
pp. 3311-3330 ◽  
Author(s):  
Ana I. Ayala ◽  
Simone Moras ◽  
Donald C. Pierson
Keyword(s):  
Water Temperature ◽  
Climate Model ◽  
Thermal Structure ◽  
Meteorological Data ◽  
Time Step ◽  
Data Set ◽  
Lake Model ◽  
Hourly Data ◽  
Daily Time Step ◽  
Daily Time

Abstract. This paper, as a part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b), assesses the impacts of different levels of global warming on the thermal structure of Lake Erken (Sweden). The General Ocean Turbulence Model (GOTM) one-dimensional hydrodynamic model was used to simulate water temperature when using ISIMIP2b bias-corrected climate model projections as input. These projections have a daily time step, while lake model simulations are often forced at hourly or shorter time steps. Therefore, it was necessary to first test the ability of GOTM to simulate Lake Erken water temperature using daily vs hourly meteorological forcing data. In order to do this, three data sets were used to force the model as follows: (1) hourly measured data, (2) daily average data derived from the first data set, and (3) synthetic hourly data created from the daily data set using generalised regression artificial neural network methods. This last data set is developed using a method that could also be applied to the daily time step ISIMIP scenarios to obtain hourly model input if needed. The lake model was shown to accurately simulate Lake Erken water temperature when forced with either daily or synthetic hourly data. Long-term simulations forced with daily or synthetic hourly meteorological data suggest that by the late 21st century the lake will undergo clear changes in thermal structure. For the representative concentration pathway (RCP) scenario, namely RCP2.6, surface water temperature was projected to increase by 1.79 and 1.36 ∘C when the lake model was forced at daily and hourly resolutions respectively, and for RCP6.0 these increases were projected to be 3.08 and 2.31 ∘C. Changes in lake stability were projected to increase, and the stratification duration was projected to be longer by 13 and 11 d under RCP2.6 scenario and 22 and 18 d under RCP6.0 scenario for daily and hourly resolutions. Model changes in thermal indices were very similar when using either the daily or synthetic hourly forcing, suggesting that the original ISIMIP climate model projections at a daily time step can be sufficient for the purpose of simulating lake water temperature.

scholarly journals Modeling and Analysis of the Variability of the Water Cycle in the Upper Rio Grande Basin at High Resolution

2007 ◽  
Vol 8 (4) ◽  
pp. 805-824 ◽  
Author(s):  
J. Li ◽  
X. Gao ◽  
S. Sorooshian
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Mesoscale Model ◽  
Meteorological Data ◽  
Rio Grande ◽  
Small Scale ◽  
Infiltration Capacity ◽  
Mountain Areas ◽  
Rio Grande Basin ◽  
Upper Rio Grande

Abstract Estimating the water budgets in a small-scale basin is a challenge, especially in the mountainous western United States, where the terrain is complex and observational data in the mountain areas are sparse. This manuscript reports on research that downscaled 5-yr (1999–2004) hydrometeorological fields over the upper Rio Grande basin from a 2.5° NCEP–NCAR reanalysis to a 4-km local scale using a regional climate model [fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3]. The model can reproduce the terrain-related precipitation distribution—the trend of diurnal, seasonal, and interannual precipitation variability—although poor snow simulation caused it to overestimate precipitation and evapotranspiration in the cold season. The outcomes from the coupled model are also comparable to offline Variable Infiltration Capacity (VIC) and Land Data Assimilation System (LDAS)/Mosaic land surface simulations that are driven by observed and/or analyzed surface meteorological data.

scholarly journals Effect of the Assimilation Frequency of Radar Reflectivity on Rain Storm Prediction by Using WRF-3DVAR

2021 ◽  
Vol 13 (11) ◽  
pp. 2103
Author(s):  
Yuchen Liu ◽  
Jia Liu ◽  
Chuanzhe Li ◽  
Fuliang Yu ◽  
Wei Wang
Keyword(s):  
Data Assimilation ◽  
Northern China ◽  
Horizontal Resolution ◽  
Radar Reflectivity ◽  
Small Scale ◽  
Time Interval ◽  
Outer Domain ◽  
Storm Prediction ◽  
The Impact ◽  
Assimilation Time

An attempt was made to evaluate the impact of assimilating Doppler Weather Radar (DWR) reflectivity together with Global Telecommunication System (GTS) data in the three-dimensional variational data assimilation (3DVAR) system of the Weather Research Forecast (WRF) model on rain storm prediction in Daqinghe basin of northern China. The aim of this study was to explore the potential effects of data assimilation frequency and to evaluate the outputs from different domain resolutions in improving the meso-scale NWP rainfall products. In this study, four numerical experiments (no assimilation, 1 and 6 h assimilation time interval with DWR and GTS at 1 km horizontal resolution, 6 h assimilation time interval with radar reflectivity, and GTS data at 3 km horizontal resolution) are carried out to evaluate the impact of data assimilation on prediction of convective rain storms. The results show that the assimilation of radar reflectivity and GTS data collectively enhanced the performance of the WRF-3DVAR system over the Beijing-Tianjin-Hebei region of northern China. It is indicated by the experimental results that the rapid update assimilation has a positive impact on the prediction of the location, tendency, and development of rain storms associated with the study area. In order to explore the influence of data assimilation in the outer domain on the output of the inner domain, the rainfall outputs of 3 and 1 km resolution are compared. The results show that the data assimilation in the outer domain has a positive effect on the output of the inner domain. Since the 3DVAR system is able to analyze certain small-scale and convective-scale features through the incorporation of radar observations, hourly assimilation time interval does not always significantly improve precipitation forecasts because of the inaccurate radar reflectivity observations. Therefore, before data assimilation, the validity of assimilation data should be judged as far as possible in advance, which can not only improve the prediction accuracy, but also improve the assimilation efficiency.

scholarly journals Dark energy survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions

2021 ◽  
Vol 503 (2) ◽  
pp. 2688-2705
Author(s):  
C Doux ◽  
E Baxter ◽  
P Lemos ◽  
C Chang ◽  
A Alarcon ◽  
...  
Keyword(s):  
Dark Energy ◽  
Internal Consistency ◽  
Goodness Of Fit ◽  
Small Scale ◽  
P Value ◽  
Posterior Predictive Distribution ◽  
Data Set ◽  
Dark Energy Survey ◽  
Data Vector ◽  
Energy Survey

ABSTRACT Beyond ΛCDM, physics or systematic errors may cause subsets of a cosmological data set to appear inconsistent when analysed assuming ΛCDM. We present an application of internal consistency tests to measurements from the Dark Energy Survey Year 1 (DES Y1) joint probes analysis. Our analysis relies on computing the posterior predictive distribution (PPD) for these data under the assumption of ΛCDM. We find that the DES Y1 data have an acceptable goodness of fit to ΛCDM, with a probability of finding a worse fit by random chance of p = 0.046. Using numerical PPD tests, supplemented by graphical checks, we show that most of the data vector appears completely consistent with expectations, although we observe a small tension between large- and small-scale measurements. A small part (roughly 1.5 per cent) of the data vector shows an unusually large departure from expectations; excluding this part of the data has negligible impact on cosmological constraints, but does significantly improve the p-value to 0.10. The methodology developed here will be applied to test the consistency of DES Year 3 joint probes data sets.

scholarly journals Diurnal variations in middle-atmospheric water vapor by ground-based microwave radiometry

2013 ◽  
Vol 13 (14) ◽  
pp. 6877-6886 ◽  
Author(s):  
D. Scheiben ◽  
A. Schanz ◽  
B. Tschanz ◽  
N. Kämpfer
Keyword(s):  
Water Vapor ◽  
Observational Data ◽  
Climate Model ◽  
Correlation Coefficients ◽  
Diurnal Variations ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Data Set ◽  
Diurnal Variability ◽  
Time Periods

Abstract. In this paper, we compare the diurnal variations in middle-atmospheric water vapor as measured by two ground-based microwave radiometers in the Alpine region near Bern, Switzerland. The observational data set is also compared to data from the chemistry–climate model WACCM. Due to the small diurnal variations of usually less than 1%, averages over extended time periods are required. Therefore, two time periods of five months each, December to April and June to October, were taken for the comparison. The diurnal variations from the observational data agree well with each other in amplitude and phase. The linear correlation coefficients range from 0.8 in the upper stratosphere to 0.5 in the upper mesosphere. The observed diurnal variability is significant at all pressure levels within the sensitivity of the instruments. Comparing our observations with WACCM, we find that the agreement of the phase of the diurnal cycle between observations and model is better from December to April than from June to October. The amplitudes of the diurnal variations for both time periods increase with altitude in WACCM, but remain approximately constant at 0.05 ppm in the observations. The WACCM data are used to separate the processes that lead to diurnal variations in middle-atmospheric water vapor above Bern. The dominating processes were found to be meridional advection below 0.1 hPa, vertical advection between 0.1 and 0.02 hPa and (photo-)chemistry above 0.02 hPa. The contribution of zonal advection is small. The highest diurnal variations in water vapor as seen in the WACCM data are found in the mesopause region during the time period from June to October with diurnal amplitudes of 0.2 ppm (approximately 5% in relative units).

scholarly journals The definition of an atmospheric database for Aeolus

2011 ◽  
Vol 4 (1) ◽  
pp. 67-88 ◽  
Author(s):  
G. J. Marseille ◽  
K. Houchi ◽  
J. de Kloe ◽  
A. Stoffelen
Keyword(s):  
High Resolution ◽  
Meteorological Data ◽  
Sampling Strategy ◽  
Laser Wavelength ◽  
Geographic Region ◽  
Atmospheric Dynamics ◽  
Specific Humidity ◽  
Small Scale ◽  
Horizontal Line ◽  
Definition Of

Abstract. The definition of an atmospheric database is an important component of simulation studies in preparation of future earth observing remote sensing satellites. The Aeolus mission, formerly denoted Atmospheric Dynamics Mission (ADM) or ADM-Aeolus, is scheduled for launch end of 2013 and aims at measuring profiles of single horizontal line-of-sight (HLOS) wind components from the surface up to about 32 km with a global coverage. The vertical profile resolution is limited but may be changed during in-orbit operation. This provides the opportunity of a targeted sampling strategy, e.g., as a function of geographic region. Optimization of the vertical (and horizontal) sampling strategy requires a characterization of the atmosphere optical and dynamical properties, more in particular the distribution of atmospheric particles and their correlation with the atmospheric dynamics. The Aeolus atmospheric database combines meteorological data from the ECMWF model with atmosphere optical properties data from CALIPSO. An inverse algorithm to retrieve high-resolution particle backscatter from the CALIPSO level-1 attenuated backscatter product is presented. Global weather models tend to underestimate atmospheric wind variability. A procedure is described to ensure compatibility of the characteristics of the database winds with those from high-resolution radiosondes. The result is a high-resolution database of zonal, meridional and vertical wind, temperature, specific humidity and particle and molecular backscatter and extinction at 355 nm laser wavelength. This allows the simulation of small-scale atmospheric processes within the Aeolus observation sampling volume and their impact on the quality of the retrieved HLOS wind profiles. The database extends over four months covering all seasons. This allows a statistical evaluation of the mission components under investigation. The database is currently used for the development of the Aeolus wind processing, the definition of wind calibration strategies and the optimization of the Aeolus sampling strategy.

scholarly journals Validation of the HIRHAM-Simulated Indian Summer Monsoon Circulation

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Stefan Polanski ◽  
Annette Rinke ◽  
Klaus Dethloff
Keyword(s):  
Summer Monsoon ◽  
Climate Model ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Monsoon Circulation ◽  
Data Sets ◽  
Data Set ◽  
Topographic Features ◽  
Temperature And Precipitation ◽  
Simulated Precipitation

The regional climate model HIRHAM has been applied over the Asian continent to simulate the Indian monsoon circulation under present-day conditions. The model is driven at the lateral and lower boundaries by European reanalysis (ERA40) data for the period from 1958 to 2001. Simulations with a horizontal resolution of 50 km are carried out to analyze the regional monsoon patterns. The focus in this paper is on the validation of the long-term summer monsoon climatology and its variability concerning circulation, temperature, and precipitation. Additionally, the monsoonal behavior in simulations for wet and dry years has been investigated and compared against several observational data sets. The results successfully reproduce the observations due to a realistic reproduction of topographic features. The simulated precipitation shows a better agreement with a high-resolution gridded precipitation data set over the central land areas of India and in the higher elevated Tibetan and Himalayan regions than ERA40.

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