Nowcasting with Data Assimilation: A Case of Global Satellite Mapping of Precipitation

2016 ◽  
Vol 31 (5) ◽  
pp. 1409-1416 ◽  
Author(s):  
Shigenori Otsuka ◽  
Shunji Kotsuki ◽  
Takemasa Miyoshi
Keyword(s):  
Data Assimilation ◽  
Space Time ◽  
Motion Vectors ◽  
The Past ◽  
Variational Techniques ◽  
Alternative Approach ◽  
Ensemble Transform Kalman Filter ◽  
Global Precipitation ◽  
Time Extrapolation ◽  
Satellite Mapping

Abstract Space–time extrapolation is a key technique in precipitation nowcasting. Motions of patterns are estimated using two or more consecutive images, and the patterns are extrapolated in space and time to obtain their future patterns. Applying space–time extrapolation to satellite-based global precipitation data will provide valuable information for regions where ground-based precipitation nowcasts are not available. However, this technique is sensitive to the accuracy of the motion vectors, and over the past few decades, previous studies have investigated methods for obtaining reliable motion vectors such as variational techniques. In this paper, an alternative approach applying data assimilation to precipitation nowcasting is proposed. A prototype extrapolation system is implemented with the local ensemble transform Kalman filter and is tested with the Japan Aerospace Exploration Agency’s Global Satellite Mapping of Precipitation (GSMaP) product. Data assimilation successfully improved the global precipitation nowcasting with the real-case GSMaP data.

The Kalam Cosmological Argument

2018 ◽  
Author(s):  
William Lane Craig
Keyword(s):  
Space Time ◽  
Cosmological Argument ◽  
Philosophical Literature ◽  
The Past ◽  
Classical Space ◽  
Kalam Cosmological Argument ◽  
Kalām Cosmological Argument ◽  
The Universe

A survey of recent philosophical literature on the kalam cosmological argument reveals that arguments for the finitude of the past and, hence, the beginning of the universe remain robust. Plantinga’s brief criticisms of Kant’s argument in his First Antinomy concerning time are shown not to be problematic for the kalam argument. This chapter addresses, one by one, the two premises of the kalam, focusing on their philosophical aspects. The notion of infinity, both actual and potential, is discussed in relation to the coming into being of the universe. In addition, the scientific aspects of the two premises are also, briefly, addressed. Among these are the Borde-Guth-Vilenkin theorem, which proves that classical space-time cannot be extended to past infinity but must reach a boundary at some time in the finite past. This, among other factors, lends credence to the kalam argument’s second premise.

Islamic International Relations Towards a Theoretical Framework

2015 ◽  
Vol 1 ◽  
Author(s):  
Gubara Hassan
Keyword(s):  
Social Sciences ◽  
International Relations ◽  
Modern Society ◽  
Theoretical Framework ◽  
World Politics ◽  
Muslim World ◽  
The West ◽  
The Past ◽  
Alternative Approach ◽  
The World

The Western originators of the multi-disciplinary social sciences and their successors, including most major Western social intellectuals, excluded religion as an explanation for the world and its affairs. They held that religion had no role to play in modern society or in rational elucidations for the way world politics or/and relations work. Expectedly, they also focused most of their studies on the West, where religion’s effect was least apparent and argued that its influence in the non-West was a primitive residue that would vanish with its modernization, the Muslim world in particular. Paradoxically, modernity has caused a resurgence or a revival of religion, including Islam. As an alternative approach to this Western-centric stance and while focusing on Islam, the paper argues that religion is not a thing of the past and that Islam has its visions of international relations between Muslim and non-Muslim states or abodes: peace, war, truce or treaty, and preaching (da’wah).

Spatiotemporal pattern mining of drought in the last 40 years in China based on the SPEI index and space-time cube

2021 ◽  
Author(s):  
Dehe Xu ◽  
Qi Zhang ◽  
Yan Ding ◽  
De Zhang
Keyword(s):  
North China ◽  
Pattern Mining ◽  
Space Time ◽  
Central China ◽  
Spatiotemporal Pattern ◽  
Severe Drought ◽  
Monthly Precipitation ◽  
Hotspot Analysis ◽  
The Past ◽  
Significant Difference

AbstractDrought is a common natural disaster that greatly affects the crop yield and water supply in China. However, the spatiotemporal characteristics of drought in China are not well understood. This paper explores the spatial and temporal distributions of droughts in China over the past 40 years using multiscale standardized precipitation evapotranspiration index (SPEI) values calculated by monthly precipitation and temperature data from 612 meteorological stations in China from 1980 to 2019 and combines the space-time cube (STC), Mann-Kendall (M-K) test, emerging spatiotemporal hotspot analysis, spatiotemporal clustering and local outliers for the analysis. The results were as follows: 1) the drought frequency and STC show that there is a significant difference in the spatiotemporal distribution of drought in China, with the most severe drought in Northwest China, followed by the western part of Southwest China and the northern part of North China. 2) The emerging spatiotemporal hotspot analysis of SPEI6 over the past 40 years reveals two cold spots in subregion 4, indicating that future droughts in the region will be more severe. 3) A local outlier analysis of the multiscale SPEI yields a low-low outlier in western North China, indicating relatively more severe year-round drought in this area than in other areas. The low-high outlier in central China indicates that this region was not dry in the past and that drought will become more severe in this region in the future.

scholarly journals Frequency of deep convective clouds in the tropical zone from 10 years of AIRS data

2013 ◽  
Vol 13 (21) ◽  
pp. 10795-10806 ◽  
Author(s):  
H. H. Aumann ◽  
A. Ruzmaikin
Keyword(s):  
Brightness Temperature ◽  
Frequency Of Occurrence ◽  
Tropical Zone ◽  
Convective Clouds ◽  
The Past ◽  
Atmospheric Window ◽  
Deep Convective Clouds ◽  
Sst Anomaly ◽  
The Difference ◽  
Global Precipitation

Abstract. Deep convective clouds (DCCs) have been widely studied because of their association with heavy precipitation and severe weather events. Changes in the properties of DCCs are likely in a changing climate. Ten years of data collected by Atmospheric Infrared Sounder (AIRS) allow us to identify decadal trends in frequency of occurrence of DCCs over land and ocean. In the past, DCCs have been identified in the thermal infrared by three methods: (1) thresholds based on the absolute value of an atmospheric window channel brightness temperature; (2) thresholds based on the difference between the brightness temperature in an atmospheric window channel and the brightness temperature centered on a strong water vapor absorption line; and (3) a threshold using the difference between the window channel brightness temperature and the tropopause temperature based on climatology. Simultaneous observations of these infrared identified DCCs with the Advanced Microwave Sounding Unit–Humidity Sounder for Brazil (AMSU-HSB) using 183 GHz water channels provide a statistical correlation with microwave deep convection and overshooting convection. In the past 10 years, the frequency of occurrence of DCCs has decreased for the tropical ocean, while it has increased for tropical land. The area of the tropical zone associated with DCCs is typically much less than 1%. We find that the least frequent, more extreme DCCs show the largest trend in frequency of occurrence, increasing over land and decreasing over ocean. The trends for land and ocean closely balance, such that the DCC frequency changed at an insignificant rate for the entire tropical zone. This pattern of essentially zero trend for the tropical zone, but opposite land/ocean trends, is consistent with measurements of global precipitation. The changes in frequency of occurrence of the DCCs are correlated with the Niño34 index, which defines the sea surface temperature (SST) anomaly in the east-central Pacific. This is also consistent with patterns seen in global precipitation. This suggests that the observed changes in the frequency are part of a decadal variability characterized by shifts in the main tropical circulation patterns, which does not fully balance in the 10-year AIRS data record. The regional correlations and anti-correlations of the DCC frequency anomaly with the Multivariate ENSO Index (MEI) provide a new perspective for the regional analysis of past events, since the SST anomaly in the Nino34 region is available in the form of the extended MEI from 1871.

scholarly journals Gain Form of the Ensemble Transform Kalman Filter and Its Relevance to Satellite Data Assimilation with Model Space Ensemble Covariance Localization

2017 ◽  
Vol 145 (11) ◽  
pp. 4575-4592 ◽  
Author(s):  
Craig H. Bishop ◽  
Jeffrey S. Whitaker ◽  
Lili Lei
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Satellite Data ◽  
Localization Length ◽  
Model Space ◽  
Ensemble Size ◽  
Length Scales ◽  
Ensemble Transform Kalman Filter ◽  
Ensemble Transform ◽  
Expanded Ensemble

To ameliorate suboptimality in ensemble data assimilation, methods have been introduced that involve expanding the ensemble size. Such expansions can incorporate model space covariance localization and/or estimates of climatological or model error covariances. Model space covariance localization in the vertical overcomes problematic aspects of ensemble-based satellite data assimilation. In the case of the ensemble transform Kalman filter (ETKF), the expanded ensemble size associated with vertical covariance localization would also enable the simultaneous update of entire vertical columns of model variables from hyperspectral and multispectral satellite sounders. However, if the original formulation of the ETKF were applied to an expanded ensemble, it would produce an analysis ensemble that was the same size as the expanded forecast ensemble. This article describes a variation on the ETKF called the gain ETKF (GETKF) that takes advantage of covariances from the expanded ensemble, while producing an analysis ensemble that has the required size of the unexpanded forecast ensemble. The approach also yields an inflation factor that depends on the localization length scale that causes the GETKF to perform differently to an ensemble square root filter (EnSRF) using the same expanded ensemble. Experimentation described herein shows that the GETKF outperforms a range of alternative ETKF-based solutions to the aforementioned problems. In cycling data assimilation experiments with a newly developed storm-track version of the Lorenz-96 model, the GETKF analysis root-mean-square error (RMSE) matches the EnSRF RMSE at shorter than optimal localization length scales but is superior in that it yields smaller RMSEs for longer localization length scales.

scholarly journals Alternative Approach to Infinity

1974 ◽  
Vol 64 ◽  
pp. 99-99
Author(s):  
Peter G. Bergmann
Keyword(s):  
Large Class ◽  
Riemannian Manifolds ◽  
Quotient Space ◽  
Three Dimensional ◽  
Cauchy Data ◽  
Space Time ◽  
Equivalence Classes ◽  
Null Infinity ◽  
Alternative Approach ◽  
Dimensional Domain

Following Penrose's construction of space-time infinity by means of a conformal construction, in which null-infinity is a three-dimensional domain, whereas time- and space-infinities are points, Geroch has recently endowed space-infinity with a somewhat richer structure. An approach that might work with a large class of pseudo-Riemannian manifolds is to induce a topology on the set of all geodesics (whether complete or incomplete) by subjecting their Cauchy data to (small) displacements in space-time and Lorentz rotations, and to group the geodesics all of whose neighborhoods intersect into equivalence classes. The quotient space of geodesics over equivalence classes is to represent infinity. In the case of Minkowski, null-infinity has the usual structure, but I0, I+, and I- each become three-dimensional as well.

scholarly journals Impact of Four-Dimensional Variational Data Assimilation of Atmospheric Motion Vectors on Tropical Cyclone Track Forecasts

2006 ◽  
Vol 21 (4) ◽  
pp. 663-669 ◽  
Author(s):  
Dongliang Wang ◽  
Xudong Liang ◽  
Yihong Duan ◽  
Johnny C. L. Chan
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Mesoscale Model ◽  
State University ◽  
Motion Vectors ◽  
Geostationary Meteorological Satellite ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Data Assimilation Technique ◽  
The Impact

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.

Investigation of the impact of thermodynamic profiles of ground based lidar systems on short-range forecast skill by means of ETKF-hybrid 3DVAR data assimilation

2021 ◽  
Author(s):  
Rohith Thundathil ◽  
Thomas Schwitalla ◽  
Andreas Behrendt ◽  
Diego Lange ◽  
Florian Späth ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Wrf Model ◽  
Absolute Humidity ◽  
Raman Lidar ◽  
High Definition ◽  
Background Error ◽  
Ground Based Lidar ◽  
Ensemble Transform Kalman Filter ◽  
Definition Of ◽  
The Impact

<p>Ground based active remote-sensing instruments have proved its potential through its high quality observations of thermodynamic profiles. In this study, thermodynamic profiles obtained from the temperature Raman lidar (TRL) and the water-vapour differential absorption lidar (DIAL) of the University of Hohenheim (UHOH) are assimilated into the Weather Research and Forecasting model data assimilation (WRFDA) system through a new forward operator for absolute humidity and mixing ratio developed in-house.<br>Thermodynamic DA was performed either with the deterministic 3-dimensional variational (3DVAR) DA system or with the hybrid 3DVAR-Ensemble Transform Kalman Filter (ETKF) approach. We used data of the High Definition of Clouds and Precipitation for advancing Climate Prediction (HD(CP)2 project Observation Prototype Experiment (HOPE). The WRF model was configured for a central European domain at a convection permitting resolution of 2.5 km spatial grid increment and 100 levels in the vertical with fine resolution in the planetary boundary layer (PBL). The assimilation experiments were conducted in a rapid update cycle (RUC) mode with an hourly update frequency. The hybrid 3DVAR-ETKF DA system was incorporated with an adaptive inflation scheme using a set of 10 ensemble members each with the same configuration as the previous experiments for the 3DVAR.  We will present the results of three DA experiments. In the first experiment (CONV_DA), or the control run, only assimilation of the conventional observations was carried out with 3DVAR DA. The second experiment (QT_DA) was a 3DVAR DA assimilating WVMR and temperature together in addition to the conventional dataset. The third experiment (QT_HYB_DA) assimilated WVMR and temperature together in addition to the conventional dataset with Hybrid DA.<br>The WVMR RMSE with respect to the WVDIAL reduced by 41 % in 3DVAR and still reduced to 51 % in QT_HYB_DA compared to CONV_DA. Although temperature RMSE with respect to TRL increased by 5 % in QT_DA, RMSE significantly reduced to 47 % in QT_HYB_DA compared to CONV_DA. The correlation between the temperature and WVMR variables in the background error covariance matrix of the 3DVAR, which is static and not flow-dependent, limited the improvement in temperature. Flow-dependency in Hybrid DA improved the error correlations.<br>We also present results of a collaborative effort with the Raman lidar for meteorological observation (RALMO) from the MeteoSwiss and the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) using even finer model resolution. The initial results of the new study will also be presented here.</p>

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