Global Weather Data Research Articles

WRF 모형의 집중호우사상 시공간적 패턴 재현 능력 평가

본 연구는 대기 프로세스의 비정상성의 효과를 반영할 수 있는 물리적 기반의 지역 기후 모델을 이용하는 새로운 방법을 제시하기 위한 기반연구이다. 이를 위해 WRF를 이용하여 과거 호우사상을 재현하였고 모의능력을 평가하였다. 모형의 초기조건 및 경계조건을 설정하기 위해서 NCEP의 재분석 자료와 해수면 온도 자료, 지상관측 자료가 사용되었다. 미세물리 과정과 적운 모수화 과정을 변경해 가며 총 9개의 수치 실험이 실시되었다. 수치모의 결과는 강수량이 초기조건 및 경계조건과 적운 모수화에 영향을 받는 것으로 나타났다. 물리 옵션 중에서 WRF single-Moment 6-class 방안과 New Kain-Fritsch 방안은 강우의 공간적인 분포는 합리적으로 재현하였지만, 총 발생강수량이 과대 산정되었으며, 시간적인 분포는 재현하지 못했다. 이는 방재분야에 WRF를 적용하기 위해서는 새로운 방법론이 필요하다는 것을 나타낸다. This paper presented a base study for new methodology that uses a physical based regional climate model that can also incorporate the effect of the nonstationarity of atmospheric process. To this end, we examined the capability of the WRF in reproducing the selected historical heavy rainfall events over Korea. WRF used the NCEP FNL reanalysis data, RTG Sea Surface Temperature data and ADP Global Surface Observational Weather data for its initial and boundary conditions. Nine experiments are carried out by changing the physics option (microphysics processes and cumulus parameterization process). Numerical simulation results showed a big variation in rainfall according to initial and boundary condition and cumulus parameterization. In physics option, WRF single-Moment 6-class scheme and New Kain-Fritsch scheme were reasonably reproduced in spatial distribution of rainfall, but the amount was overestimated and dose not reproduce temporal distribution of rainfall. This indicates that a new methodology necessary to WRF for hazard mitigation.

Climate and Vegetation: An ERA-Interim and GIMMS NDVI Analysis

To complement geographical presentation of remote sensing vegetation information, the authors apply Budyko’s physical state space diagram to analyze functional climate relations. As an example, the authors use Interim ECMWF Re-Analysis (ERA-Interim) global weather data to provide the statistics (1982–2006) of climate states in a two-dimensional state space spanned by water demand (net radiation N) versus water/energy limitation (dryness ratio D of net radiation over precipitation). Embedding remote sensing–based Global Inventory Modeling and Mapping Studies (GIMMS) data [normalized difference vegetation index (NDVI) > 0.1] shows the following results: (i) A bimodal frequency distribution of unit areas (pixels) is aligned near D ~ 1 but separated meridionally, associated with higher and lower net radiation. (ii) Vegetation states are represented as (N, D, NDVI) triplets that reveal temperate and tropical forests crossing the border (D ~ 1) separating energy- and water-limited climates but unexpectedly show that they also exist in marginal regions (few pixels) of large dryness. (iii) Interannual variability of dryness is lowest where the largest climate mean NDVI values of greenness (forests) occur. The authors conclude that the combined (N, D, NDVI) analysis based on climate means has shown that tropical and temperate forests (NDVI > 0.6) are (i) not restricted to the energy-limited domain D < 1 (extending into the water-limited surface climate regime) and (ii) associated with low interannual variability of dryness. Thus, measures of interannual variability may be included in Budyko’s classical framework of geobotanic analysis of surface climates.

Impact of derived global weather data on simulated crop yields

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26–72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12–19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method.

The Analysis of Wind Power Potential in Sahara Site of Algeria-an Estimation Using the ‘Weibull’ Density Function

The wind energy is one of the most significant and rapidly developing renewable energy sources in the world and it provides a clean energy resource, which is a promising alternative in the short term in Algeria. The main purpose of this paper is to discuss the wind potential in Sahara site of Algeria and to perform an investigation on the wind power potential of desert of Algeria. The Weibull density function has been used to estimate the monthly power wind density and to determine the characteristics of monthly parameters of Weibull. A simulation model has been established to describe the characteristics of a particular wind turbine. The monthly power generated and the monthly operating hours by the wind turbine to be simulated. The simulation based on the data wind speed measured at the 10th meters and collected during 8760hours by a wind observation station web site weather underground (The global weather data could be obtained from internet).

Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data

Abstract. Lake Turkana, the largest desert lake in the world, is fed by ungauged or poorly gauged river systems. To meet the demand of electricity in the East African region, Ethiopia is currently building the Gibe III hydroelectric dam on the Omo River, which supplies more than 80% of the inflows to Lake Turkana. On completion, the Gibe III dam will be the tallest dam in Africa with a height of 241 m. However, the nature of interactions and potential impacts of regulated inflows to Lake Turkana are not well understood due to its remote location and unavailability of reliable in situ datasets. In this study, we used 12 yr (1998–2009) of existing multi-source satellite and model-assimilated global weather data. We used a calibrated multi-source satellite data-driven water balance model for Lake Turkana that takes into account model routed runoff, lake/reservoir evapotranspiration, direct rain on lakes/reservoirs and releases from the dam to compute lake water levels. The model evaluates the impact of the Gibe III dam using three different approaches – a historical approach, a rainfall based approach, and a statistical approach to generate rainfall-runoff scenarios. All the approaches provided comparable and consistent results. Model results indicated that the hydrological impact of the Gibe III dam on Lake Turkana would vary with the magnitude and distribution of rainfall post-dam commencement. On average, the reservoir would take up to 8–10 months, after commencement, to reach a minimum operation level of 201 m depth of water. During the dam filling period, the lake level would drop up to 1–2 m (95% confidence) compared to the lake level modeled without the dam. The lake level variability caused by regulated inflows after the dam commissioning were found to be within the natural variability of the lake of 4.8 m. Moreover, modeling results indicated that the hydrological impact of the Gibe III dam would depend on the initial lake level at the time of dam commencement. Areas along the Lake Turkana shoreline that are vulnerable to fluctuations in lake levels due to the Gibe III dam were also identified. This study demonstrates the effectiveness of using existing multi-source satellite data in a basic modeling framework to assess the potential hydrological impact of an upstream dam on a terminal downstream lake. The results obtained from this study could also be used to evaluate alternative dam-filling scenarios and assess the potential impact of the dam on Lake Turkana under different operational strategies.

지표수문해석모형을 활용한 동아시아 유출해석 및 평가

본 연구에서는 지표수문해석모형을 활용한 동아시아 지역의 유출해석을 수행하고 그 적용성을 평가하였다. 이에 전지구자료를 수집한 후 모형의 입력자료로 재구성하였으며, 모의 결과의 검증을 위해 GRDC에서 제공하는 국외 34개 지점의 관측유량자료를 수집하였다. 쾨펜의 기후대 구분을 통한 매개변수 전이 방법을 이용하여 미계측지역의 유출 매개변수를 결정하였으며, 동아시아지역에 유출해석을 수행하였다. 그 결과 미계측지역으로 가정한 17개 유역에서 모의치가 관측치와 유사하게 거동하는 것으로 나타나 결과의 신뢰성이 높음을 확인하였다. 최종 결정된 매개변수로부터 동아시아 전역에 수문성분을 산정하였으며, 대체로 동아시아 지역의 국가들의 수문성분 거동은 계절별로 유사한 것으로 확인되었다. 또한, 중국의 남부지역, 일본 및 대만은 동아시아 내에서도 유출의 발생이 가장 높은 반면, 몽골 및 중국 북부지역에서는 매우 낮은 것으로 분석되었다. The objective of this study is to evaluate the applicability of Land Surface Model (LSM) for estimating the runoff on East Asia. Global geographical and weather data are used as input for the model and for the model verification, the simulated runoff results are compared with observed data from 34 global observation stations provided by Global Runoff Data Center (GRDC). K<TEX>$\ddot{o}$</TEX>ppen's climate zone is used to calculate the model parameter for ungaged basins. As a result, the simulated runoff shows good performance comparing with observed data in 17 basins assumed as ungaged basins. The Hydrologic components on East Asia area are estimated from the model and the continental water balance components are seasonally similar to each country. Also, it reveals that runoffs from southern China, Japan and Taiwan are much higher than those from mongolian and northern China.

Dynamic weather forecaster: results of the testing of a collaborative, on-line educational platform for weather forecasting

The online Dynamic Weather Forecaster is an open, collaborative application available now to high-school and college instructors across the United States who would like to easily incorporate weather forecasting in their instruction. The application consists of a set of 13 questions that allow students to submit forecasts that cover most of the parameters used by professional weather forecasters. Submissions are automatically validated against weather parameters and graded. We tested the impact of the application on the learning of 199 undergraduate students in an introductory meteorology course in spring 2008. Students who begin forecasting early in the semester and continue to do so throughout the semester are statistically significantly more successful in the course than students who start late or complete a low number of forecasts. College, year in school, and gender were not significant predictors of success. Students found the application easy to use, and 92.3% of them found it at least somewhat helpful as they learned about the weather. Through the use of the DWF, students also experience first-hand that uncertainty is a critical part of weather forecasting and of scientific studies in general. With sufficient interest from potential users outside the USA, the DWF platform could easily be expanded to include global weather data.

RNCEP: global weather and climate data at your fingertips

Summary1. Atmospheric conditions strongly influence ecological systems, and tools that simplify the access and processing of atmospheric data can greatly facilitate ecological research.2. We have developed RNCEP, a package of functions in the open‐source R language, to access, organise and visualise freely available atmospheric data from two long‐term high‐quality data sets with global coverage.3. These functions retrieve data, via the Internet, for either a desired spatiotemporal extent or interpolated to a point in space and time. The package also contains functions to temporally aggregate data, producing user‐defined variables, and to visualise these data on a map.4. By making access to atmospheric data and integration with biological data easier and more flexible, we hope to facilitate and encourage the exploration of relationships between biological systems and atmospheric conditions.

Global‐scale river routing—an efficient time‐delay algorithm based on HydroSHEDS high‐resolution hydrography

AbstractCoupling of global hydrologic and atmospheric models is difficult because of the highly nonlinear hydrological processes to be integrated at large scales. Aggregation of high‐resolution data into low‐resolution spatial distribution functions is one way to preserve information and account for the nonlinearity. We used HydroSHEDS, presently the most highly resolved (3″) global hydrography available, to provide accurate control on global river routing through a computationally efficient algorithm. The high resolution of HydroSHEDS allowed discrimination of river‐channel pixels, and time‐delay distributions were calculated for all such pixels. The distributions were aggregated into network‐response functions (NRFs) for each low‐resolution cell using an algorithm originally developed for the 1‐km‐resolution HYDRO1k hydrography. The large size of HydroSHEDS required a modification in algorithm to maintain computational efficiency. The new algorithm was tested with a high‐quality local and a more uncertain global weather dataset to identify whether improved routing would provide a gain when weather data quality was limiting. The routing was coupled to the WASMOD‐M runoff‐generation model to evaluate discharge from the Dongjiang River and the Willamette River basins. The HydroSHEDS‐based routing, compared with the HYDRO1k‐based routing, provided a small gain in model efficiency, for local and global weather data and for both test basins. The HydroSHEDS‐based routing, contrary to the HYDRO1k‐based routing, provided physically realistic wave velocities. The most stable runoff‐generation parameter values were achieved when HydroSHEDS was used to derive the NRFs. Routing was computed in two steps: first, a preparatory calculation which was a one‐time effort and second, the routing during each simulation. The computational efficiency was four to five orders of magnitude better for the simulation step than that for the preparatory step. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Estimating reference evapotranspiration using numerical weather modelling

AbstractEvapotranspiration is an important hydrological process and its estimation usually needs measurements of many weather variables such as atmospheric pressure, wind speed, air temperature, net radiation and relative humidity. Those weather variables are not easily obtainable from in situ measurements in practical water resources projects. This study explored a potential application of downscaled global reanalysis weather data using mesoscale modelling system 5 (MM5). The MM5 is able to downscale the global data down to much finer resolutions in space and time for use in hydrological investigations. In this study, the ERA‐40 reanalysis data are downscaled to the Brue catchment in southwest England. The results are compared with the observation data. Among the studied weather variables, atmospheric pressure could be derived very accurately with less than 0·2% error. On the other hand, the error in wind speed is about 200–400%. The errors in other weather variables are air temperature (&lt;10%), relative humidity (5–21%) and net radiation (4–23%). The downscaling process generally improves the data quality (except wind speed) and provides higher data resolution in comparison with the original reanalysis data. The evapotranspiration values estimated from the downscaled data are significantly overestimated across all the seasons (27–46%) based on the FAO Penman–Monteith equation. The dominant weather variables are net radiation (during the warm period) and relative humidity (during the cold period). There are clear patterns among some weather variables and they could be used to correct the biases in the downscaled data from either short‐term in situ measurements or through regionalization from surrounding weather stations. Artificial intelligence tools could be used to map the downscaled data directly into evapotranspiration or even river runoff if rainfall data are available. This study provides hydrologists with valuable information on downscaled weather variables and further exploration of this potentially valuable data source by the hydrological community should be encouraged. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Variability and Climatology of PWV From Global 13-Year GPS Observations

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Water vapor plays the key role in the global hydrologic cycle and climate change. However, the distribution and variability of water vapor in the troposphere is not understood well in the globe, particularly the high-resolution variation. In this paper, 13-year 2-h precipitable water vapors (PWV) are derived from globally distributed 155 Global Positioning System sites observations and global three-hourly surface weather data and six-hourly National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis products, which are the first used to investigate multiscale water-vapor variability on a global scale. It has been found that the distinct seasonal cycles are in summer with a maximum water vapor and in winter with a minimum water vapor. The higher amplitudes of annual PWV variations are located in midlatitudes with about 10–20 <formula formulatype="inline"><tex Notation="TeX">$\pm$</tex></formula> 0.5 mm, and the lower amplitudes are found in high latitudes and equatorial areas with about 5 <formula formulatype="inline"><tex Notation="TeX">$\pm$</tex></formula> 0.5 mm. The larger differences of mean PWV between in summer and winter are located in midlatitudes with about 10–30 mm, particularly in the Northern Hemisphere. The semiannual variation amplitudes are relatively weaker with about 0.5 <formula formulatype="inline"><tex Notation="TeX">$\pm$</tex></formula> 0.2 mm. In addition, significant diurnal variations of PWV are found over most International Global Navigation Satellite Systems Service stations. The diurnal (24 h) cycle has amplitude of 0.2–1.2 <formula formulatype="inline"><tex Notation="TeX">$\pm$</tex></formula> 0.1 mm, and the peak time is from the noon to midnight. The semidiurnal (12 h) cycle is weaker, with amplitude of less than 0.3 mm. </para>

Beyond the ivory tower. "A vast machine": standards as social technology.

Universal standards for measuring, recording, and transmitting data are crucial components of the global meteorological observing system, allowing data collected at one place and time to be compared meaningfully with data collected elsewhere and/or at other times. Without these standards, we would be unable to detect global climate change. In his essay, Edwards charts the evolution of global weather data standards since the 1850s. Many standards have gradually been embodied in automatic instruments and computer programs, but enforcing standards nevertheless requires substantial discipline on the part of humans and institutions. Since the 1980s, climate politics have provoked much controversy over data quality, sometimes resurrecting debates that these standards were intended to settle.

Bound on the amplitude of the Earth's free core–nutation

We analyzed six years of very–long–baseline interferometry (VLBI) data and determined corrections to the coefficients of the seven terms with the largest amplitudes in the IAU 1980 nutation series. Our analysis yields results consistent with earlier analyses of smaller sets of VLBI data, within the uncertainties of the latter. Here, we restrict discussion to the freely excited core–nutation or “free core–nutation” (FCN). Our analysis yields an estimate of 0.33 ± 0.12 mas for an assumed constant amplitude of the FCN, which allows us to place an upper bound on it of 0.6 mas (99.5% confidence limit). We also studied possible temporal variations of the complex amplitude of the FCN by modeling it as a stochastic process with a white noise excitation. We detected no statistically significant variations of this amplitude for the six–year interval spanned by the VLBI data. However, in the neighborhood of one cycle per day, the power spectral density of the atmospheric surface loading is estimated from global weather data to be 0.24 (g cm−2)2 day, about five times larger than the largest such power spectral density that would be consistent with the upper bound on the amplitude of the FCN placed by the VLBI data. Thus, we conclude that this estimate is too high and that, if the FCN were excited by surface loads with frequencies near one cycle per day, then the power spectral density of these loads must be &lt;0.06 (g cm−2)2 day (99.9% confidence limit).

LACIE—An Application of Meteorology for United States and Foreign Wheat Assessment

The development of a critical world food situation during the early 1970's was the background leading to the Large Area Crop Inventory Experiment (LACIE). The need was to develop a capability for timely monitoring of crops on a global scale. Three U.S. Government agencies, NASA, NOAA and USDA, undertook the task of developing technology to extract the crop-related information available from the global weather-reporting network and the Landsat satellite. This paper describes the overall LACIE technical approach to make a quasi-operational application of existing research results and the accomplishments of this cooperative experiment in utilizing the weather information. Using available agrometeorological data, techniques were implemented to estimate crop development, assess relative crop vigor and estimate yield for wheat, the crop of principal interest to the experiment. Global weather data were utilized in preparing timely yield estimates for selected areas of the U.S. Great Plains, the U.S.S.R. and Canada. Additionally, wheat yield models were developed and pilot tested for Brazil, Australia, India and Argentina. The results of the work show that heading dates for wheat in North America can be predicted with an average absolute error of about 5 days for winter wheat and 4 days for spring wheat. Independent tests of wheat yield models over a 10-year period for the U.S. Great Plains produced a root-mean-square error of 1.12 quintals per hectare (q ha−1) while similar tests in the U.S.S.R. produced an error of 1.31 q ha−1. Research designed to improve the initial capability is described as is the rationale for further evolution of a capability to monitor global climate and assess its impact on world food supplies.

Sunspots, Geomagnetic Indices and the Weather: A Cross-Spectral Analysis between Sunspots, Geomagnetic Activity and Global Weather Data

Abstract Cross-spectral computations using the time series of Zurich sunspot numbers and seasonal mean temperature and precipitation totals indicate that these series are uncorrelated at individual stations and when grouped together into latitude bands. The same computations with the time series of the geomanetic index Aa and these meteorological series also show no correlation either at individual stations or when grouped together in latitude bands.

Satellite Satellites—A Conjecture on Future Atmospheric-Sounding Systems

The super-pressure balloon provides a vehicle for obtaining global horizontal soundings of meteorological parameters at all altitudes from 500 mb to 10 mb. The principal technical problems to be solved are reliable telemetering of data and obtaining of accurate positional data. The orbiting satellite, which of itself provides a poor sensing capability, is ideally suited to locate the balloons and serve as the communication link. The use of the super-pressure balloon as a satellite to the orbiting satellite promises a unique capability for obtaining global weather data on a continuous basis.