Monthly Dataset Research Articles

Analyzing bias in prominent climatic data sets

The majority of documented climatic data set biases can be divided into two categories: physical biases and calendar biases. Factors affecting the consistency and accuracy of the variable measurement (physical bias) throughout the data record include systematic measurement error and changes in instrumentation, time of observation, measurement site location, observation methods, and surrounding land use/land cover. Factors influencing data aggregated from shorter temporal scales to longer temporal scales (i.e. days to years or days to months) are calendar biases and have been studied to a much lesser extent than physical biases. Previous homogenization efforts for prominent temperature and precipitation data sets are detailed in this review. Numerous physical biases are accounted for in these homogenization efforts and a debate exists in the literature regarding the effectiveness of these bias adjustment methods, leading some investigators to question the suitability of these adjusted data sets for the identification of large-scale climate change signals. Calendar biases are not addressed in previous homogenization efforts. After a brief analysis, a calendar bias known to exist in homogenized data sets (the leap year bias) is identified in the CRUTEM3v, an important global monthly near-surface air temperature data set.

Research of upper-level wind for astronomical site survey

By using the monthly data sets for the period of 1951-2008 from upper-air stations, the upper-level wind was studied. The spatial distribution and seasonal variation of 200 hPa wind were presented, and the characteristics of wind profiles at representative stations analyzed. The results indicate that Nenjiang and Beitashan, on behalf of the north of Northeast China and north of Northwest China, respectively, have the best upper-level wind conditions for astronomical observations, comparable with the first-rank astronomical observatories in the world; the wind conditions above Simao of Yunnan province, Kashi of west Xinjiang and Dingri of south Tibet Plateau, are just all right; South of Yangzi River and South China, which locate nearby the upper-level jet stream, have worse conditions due to strong upper air wind.

Oil price and stock market index in exporting and importing countries: evidence from MENA

In the empirical literature, only few studies have focused on the relationship between oil prices and stock markets in both exporting and importing countries. Previous studies have focused almost exclusively on oil exporting countries; in this paper we encounter this issue through implementing new panel unit-root tests to examine the long-term relationship between variables and the convergence across these variables. As a further safeguard, Granger Causality and the Johansen maximum likelihood co-integration technique have been employed. Using monthly datasets covering the period from June 2007 to December 2009, we show solid statistical evidence that the causal relationship is consistently bi-directional. Furthermore, we find evidence to indicate that there are long run relationships across all the variables in our study. The findings from our research are important; however, we believe that further research based on our findings is necessary.

THE EFFECTS OF ALTERNATIVE EXCHANGE RATE REGIMES ON REAL EXCHANGE RATE VOLATILITY: EVIDENCE BASED ON A NEW DATASET

Do alternative exchange rate regimes affect short‐term real exchange rate volatility differently? The existing empirical evidence is quite mixed with slightly more papers supporting that they do. We show that such lack of consensus is mainly due to current literature limitations regarding the measurement of real exchange rates (RERs), the identification of exchange rate regimes (ERRs), and the control for the incidence of real and nominal shocks. To address these limitations, we construct a novel monthly dataset for 63 countries over the period 1946–2007, which includes market‐determined multilateral RER and a proxy for terms of trade. We find that ERRs indeed affect short‐term real exchange rate volatility differently. While the evidence is generally consistent with Mussa's sticky prices argument, we find that for nonadvanced countries in post‐Bretton Woods there exists a “U‐shape nominal flexibility puzzle of RER.” We also find evidence of a “short‐run RER volatility puzzle.” Having controlled for the incidence of real and nominal shocks, nonadvanced countries' RER volatility remains between 25% and 150% greater than that of the advanced economies. Moreover, the key literature finding that short‐term RER volatility is higher in Bretton Woods (BW) than in post‐Bretton Woods (PBW) for industrialized countries vanishes when using market‐determined multilateral RER instead of official bilateral RER. (JEL F31, F33, F41)

Estimating recharge distribution using remote sensing: A case study from the West Bank

Summary Estimating groundwater recharge to the aquifer system is a very important element in assessing the water resources in regions of the world with poorly developed hydrological measurement stations such as the West Bank. Previous studies have developed analytical recharge models that are based on the long-term annual rainfall data. These models have been shown to be inadequate and changes over shorter periods, e.g. monthly estimates, must be known in order to study the temporal distribution of recharge. The approach used in this research integrates data derived from satellite images (e.g. land cover, evapotranspiration, precipitation, and digital elevation model) with hydrogeological data in a Geographic Information System (GIS) model to identify surface recharge areas on a pixel-by-pixel basis. The Surface Energy Balance Algorithm for Land (SEBAL) is applied to time series of MODerate Resolution Imaging Spectroradiometer (MODIS) Level 3 data of reflectance and surface temperature measurements to estimate monthly evapotranspiration; precipitation is derived from the monthly data sets of the Tropical Rainfall Measuring Mission (TRMM); runoff is given assumed values of 1.0 mm month −1 and 0.5 mm month −1 for the months of January and February, respectively. Recharge is quantified from November until March by applying the water balance method where evapotranspiration estimates and runoff are subtracted from precipitation. Results show good agreement between available numbers reported in literature and the remote sensing-based analysis. Empirical models that are based on long term rainfall measurements result values between 800 and 836 MCM yr −1 while the remote sensing based model results a recharge estimate of between 650 and 750 MCM yr −1 .

An Empirical Analysis of Relative Oil Price Shocks and Chinese Net Processing Exports

This paper studies the effects of Chinese relative domestic oil prices on net processing exports. Using a set of monthly data ranging from 2002 to 2008, we identify a long-run equilibrium cointegrating relationship between the two inflationary series. The unidirectional short-run Granger causality is running from relative oil prices to net processing exports, while in the long-run, the Granger causality is bidirectional. What is noteworthy is that relative oil price shocks have long-run positive effects on Chinese net processing exports, indicating the existence of an energy cost-driven mechanism of endogenous technological change.

Innovations in Mobile Broadband in Japan and its Implications to Developing Countries

Japan has experienced two developmental stages in the mobile telephony innovation since 1979 when the first mobile phone was commercially launched. The stages can be identified as traditional mobile phone with only voice function and mobile phone with IP (Internet Protocol). This paper discusses how mobile phone with IP function offers diversified services, influences people’s daily lives by changing their ways of communication, and interaction by adopting mobile broadband. The paper examines key economic, technology and policy factors based on monthly datasets from 2000-2007 in the provision of both second (2G) and third generation (3G) mobile phones adoption. Particularly, the study uses a linear regression model and presents extended and reduced models using the Pearson correlation method. The results of the empirical study examine how innovations in services contribute to the mobile broadband deployment in Japan. Main findings of this study suggest policy and strategy implications for developing countries which are adopting IP functionality in mobile phones. The paper also presents brief recommendations for India’s 3G mobile phone adoptions in terms of opportunities, challenges, and policies which drive on growth.

Validation of TRMM Data in the Black Volta Basin of Ghana

AbstractThis study was conducted in the Black Volta basin, Ghana, to determine how Tropical Rainfall Measuring Mission (TRMM) satellite-derived rainfall compares with ground-measured values and the possibility of using it to complement ground-measured rainfall. Bilinear interpolation was used to resample 0.25°×0.25° TRMM 3B42V6 monthly rainfall grids to determine site-specific rainfall of the basin based on rain gauge locations and analyzed statistically. The study showed that the correlation between the monthly datasets ranged from 0.73 to 0.88. A plot of the average monthly data of all the stations gave a correlation coefficient (R) of 0.94. The overall catchment rainfall was well represented by TRMM data. However, the annual station rainfalls were either underestimated or overestimated. The underestimations and overestimations were mostly below 20% and 10%, respectively, of the raingauge measurements. Although the TRMM rainfall data did not perfectly match with the ground measurements, it can still be ...

Analysis of a 4 year radiosonde data set at Dome C for characterizing temperature and moisture conditions of the Antarctic atmosphere

[1] A 4 year set of vertical profiles of pressure, temperature and relative humidity derived from 1113 radiosounding measurements performed at Dome C (Antarctica) at 12:00 UTC of each day, from late March 2005 to March 2009, were analyzed using an updated procedure for removing the most important temperature and humidity errors and dry biases. The monthly mean vertical profiles of pressure, temperature, and moisture parameters were determined, providing evidence of the strong seasonal variations in temperature occurring within the ground layer and in the tropopause region. The results are presented for use in the analysis of the ground-based measurements of both short- and long-wave radiation budget terms routinely performed at this site, and to better investigate the water vapor role in the Antarctic Plateau surface-atmosphere system. The evaluation of atmospheric water vapor content W (precipitable water) is of great relevance for astronomical studies, to verify that high atmospheric transmission conditions exist, especially in the submillimeter and millimeter range, for the exceptionally dry air characteristics of the Dome C atmosphere. The monthly mean data sets of moisture parameters were analyzed to determine the monthly mean vertical profiles of absolute humidity, and to evaluate the daily values of W, varying from less than 0.30 mm (from June to October) to more than 0.60 mm in January, on average. The monthly mean percentiles of W indicate that this parameter is expected to be lower than 0.20 mm on at least 25% of days from May to October, indicating that very high atmospheric transparency conditions should occur in the infrared-millimeter spectral range on at least 40 days during austral autumn and winter.

Variability and trends of mean maximum and mean minimum air temperature in Greece from ground-based observations and NCEP–NCAR reanalysis gridded data

In this study, the variability and trends of the mean annual and seasonal maximum and minimum surface air temperature in Greece are examined, using monthly data sets of 26 meteorological stations from the Hellenic National Meteorological Service (HNMS) and gridded data from the National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) Reanalysis project for the period 1955–2001. NCEP–NCAR reanalysis data sets are created by assimilating climate observations from different sources, including ships, satellites, ground stations, radiosonde observations and radar. The general purpose of conducting reanalyses is to produce multi-year global state-of-the-art gridded representations of atmospheric states, generated by a constant model and a constant data-assimilation system. The trends of the mean extreme air temperatures were evaluated, using the Mann–Kendall criterion, and, in the process, factor analysis was applied to both the stations' and the NCEP–NCAR grid points time series. Regarding the mean maximum air temperature, the first main factor, which explains a high percentage of the total variance, presents a statistically significant (CL = 95%) negative trend only during the winter. The first main factor of the mean minimum air temperature manifests a statistically significant (CL = 95%) positive trend during the summer and the year, and a statistically significant (CL = 95%) negative trend in autumn and winter. These findings were compared to the respective ones of the NCEP–NCAR reanalysis data and significant differences in the spatial distribution and temporal variability of the extracted new factors were found. These differences between the two examined data sets could be attributed to topographical factors such orography and land–sea distribution, which could not be represented properly by the reanalysis model.

Are small employers more cyclically sensitive? Evidence from Brazil

An important issue facing policymakers is the degree to which fluctuations in economic activity affect employment in large and small businesses across sectors and regions. This issue is particularly relevant for developing countries as it matters for the understanding of the labour market dynamics, and for devising national, sectoral, and regional labour policies that aim at dampening employment fluctuations, particularly during recessions. Using a unique monthly dataset of 27 states and eight industries from 2000:1 to 2009:7, this paper evaluates the sensitivity of businesses of different sizes to business cycle conditions in Brazil. The behaviour of the difference in employment growth rates between large and small firms is counter-cyclical and suggests that small firms are more sensitive to business cycle conditions. In addition, the SVAR impulse response analysis suggests the existence of the effect of small firms hiring cheaply from unemployment proportionally more than large ones. On the other hand, credit constraints seem to hit small firms harder and help to explain the empirical regularity that small firms are more cyclically sensitive than large ones for the Brazilian case.

Time variation of astro-climate conditions in China

The time variation of astroclimate conditions in China was analyzed in terms of cloud cover,air temperature,wind speed,water vapor pressure,and precipitation.The databases from ground meteorological stations over China were employed with the yearly and monthly data sets for the period of 1951-2008.According to the climate regionalization for astronomical observations,21 stations were selected based on their advantages for astronomical observations,the locations nearby existing/candidate observatories,or the climatologically representative of local regions.The long-term trend,annual and diurnal variability of the relevant meteorological factors were summarized and compared for the 21 local regions,providing ground-truth evidence for selecting and further evaluating an astronomical site.This study serves as a further demonstration towards astroclimate regionalization,and provides with essential database for astronomical site survey in China.

ASSESSING LAND DEGRADATION RISK THROUGH THE LONG‐TERM ANALYSIS OF EROSIVITY: A CASE STUDY IN SOUTHERN SPAIN

ABSTRACTDespite the high variability of the precipitation regime characterizing the Mediterranean area, the records of rainfall depth are usually not appropriate for long‐term calculations of erosivity and soil losses, because they do not reveal details of short lengths or long durations (daily, monthly). In this work, we present a simple approach to calculate annual erosivity through monthly precipitation records. The study area (olive groves on steep slopes) has a high erosion risk associated to the main soil land use, combined with an irregular and erosive rainfall regime. The relationships between rainfall data at intervals of 10 min for a period of 3 years, daily rainfall records over 10 years and a long‐term monthly dataset of 60 years were checked to calculate the annual erosivity values through daily data, Fourier's index and modified Fourier's index values. A good, adjusted linear relationship between modified Fourier's index and the erosivity was found, which allowed us to optimize the use of the 60‐year monthly data series and to carry out a long‐term analysis of the erosivity quantiles in the study area. The estimated mean erosivity showed a return period of between 2 and 5 years and a variation coefficient of over 50 per cent, which illustrate its high variability and frequency. This approach to calculate erosivity and the use of quantiles could be applied in other areas with month‐long data series in order to study and model the erosion risk using suitable temporal periods. Copyright © 2011 John Wiley & Sons, Ltd.

A Global Model of International Yield Curves: No-Arbitrage Term Structure Approach

This paper extends a popular no-arbitrage affine term structure model to model jointly bond markets and exchange rates across the United Kingdom, United States and euro area. Using a monthly data set of forward rates from 1992, we first demonstrate that two global factors account for a significant proportion in the variation of bond yields across countries. We also show that, in order to explain country-specific movements in yield curves, local factors are required. Although we implement a very general factor structure, we find that our global factors are related to global inflation and global economic activity, while local factors are closely linked to monetary policy rates. In this respect our results are similar to previous work. But an important advantage of our joint international model is that we are able to decompose interest rates into risk-free rates and risk premia. Additionally, we are able to study the implications for exchange rates. We show that while differences in risk-free rates matter, to a large extent changes in the exchange rate are determined by time-varying exchange rate risk premia.

Purchasing power parity in LDCs: An empirical investigation

Using the real effective exchange rate (REER) data of sixty-six developing countries and a more extensive monthly dataset from 1980:1 through 2009:10 (i.e., 358 observations), this study examines whether the REER is stationary, using two approaches. The two tests are the KPSS and the KSS test. In contrast to previous studies, we found overwhelming support for the long-run purchasing power parity (PPP) hypothesis; thus, the PPP is a suitable guide for exchange rate determination and exchange rate policy reform in LDCs. We attribute our finding to using REER data as well as linear and nonlinear tests with different null hypotheses.

Satellite altimeter‐derived monthly discharge of the Ganga‐Brahmaputra River and its seasonal to interannual variations from 1993 to 2008

The Ganga‐Brahmaputra accounts for ∼25% of the total amount of freshwater received by the Bay of Bengal. Using daily in situ river discharge data along with altimetry‐derived river heights, the present study aims to produce a monthly data set of altimetry‐derived Ganga‐Brahmaputra River discharge at the river mouths for 1993–2008. First, we estimate the standard error of ENVISAT‐derived water levels over the Ganga to be 0.26 m, much smaller than the range of variability of ∼7 m, and consistent with the accuracy of altimeter measurements over large rivers. We then establish rating curves between altimetry‐derived water levels and in situ river discharges and show that TOPEX‐Poseidon, ERS‐2, and ENVISAT data can successfully be used to infer Ganga and Brahmaputra discharge. The mean error on the estimated daily discharge derived from altimetry ranges from ∼15% (∼4700 m3/s) using TOPEX‐Poseidon over the Brahmaputra to ∼36% (∼9000 m3/s) using ERS‐2 over the Ganga. Combined Ganga‐Brahmaputra monthly discharges for 1993–2008 are presented, showing a mean error of ∼17% (∼2700 m3/s), within the range (15%–20%) of acceptable accuracy for discharge measurements. During 2004–2008, we assess the variability of the estimate against precipitation and river heights records. Finally, we present a basic approach to infer Ganga‐Brahmaputra monthly discharge at the river mouths. The upscaled discharge exhibits a marked interannual variability with a standard deviation in excess of ∼12,500 m3/s, much larger than the data set uncertainty. This new data set represents an unprecedented source of information to quantify continental freshwater forcing flux into Indian Ocean circulation models.

The Money-prices Nexus for Malaysia: New Empirical Evidence from the Time-varying Cointegration and Causality Tests

The main objective of this study is to empirically re-investigate the money-prices nexus for Malaysia through the Johansen multivariate cointegration and the modified Wald (MWALD) causality techniques. This study covered the monthly dataset from 1971:M1 to 2008:M11. The Johansen cointegration test suggests that the variables under investigation are co-move in the long run. Furthermore, the MWALD causality test shows a bidirectional causal relationship between money supply (M2) and aggregate prices, meaning that both the monetarist's and also the structuralists' views are vindicated in the Malaysian economy. However, the time-varying cointegration and causality tests indicate that the cointegrating and also the causal relationships are not stable over the analysis period. These results suggest that inflation in Malaysia is not purely a monetary phenomenon. Therefore, implementing a tighter monetary policy may not be an effective macro-economic instrument in managing the inflationary behaviour in the Malaysian economy.

A gridded monthly upper-air data set from 1918 to 1957

Significant efforts have been devoted in recent years towards extending observation-based three-dimensional atmospheric data sets back in time. Such data sets form an important basis for a better understanding of the climate system. Here we present a new monthly three-dimensional global data set that is based on historical upper-air data and surface data. We use statistical reconstruction techniques, calibrated using ERA-40 data, to obtain gridded data from the numerous, but scattered and heterogeneous historical upper-air observations. In contrast to previous work, in which we used hemispheric principal components on both the predictor and the predictand side to reconstruct spatially complete fields back to 1880, we restrict the procedure to places and times where upper-air observations are available. Each grid column (consisting of four variables at six levels) is then reconstructed independently using only predictor variables in the vicinity (i.e., only local stationarity is required rather than stationary large-scale patterns). The product, termed REC2, is a gridded, global monthly data set of geopotential height, temperature, and u and v wind from 850 to 100 hPa back to 1918. The data set is sparse (i.e., many grid cells are empty), but provides an alternative to large-scale reconstructions as it allows for non-stationary teleconnections. We show the results of several validation experiments, compare our new data set with a number of existing data sets, and demonstrate that it is suitable for analysing large-scale climate variability on interannual time-scales.

Assessing the groundwater dynamics and impacts of water saving in the Hetao Irrigation District, Yellow River basin

Abstract Water resources allocated to the agricultural sector in the Yellow River basin are being reduced due to severe water scarcity and increased demand by the non-agricultural sectors. In large-scale irrigation districts, the application of water-saving practices, e.g., improving the canal system, using water-saving irrigation technology and adjusting cropping patterns, is required for the sustainable agricultural development and the river basin environmental equilibrium. Adopting water-saving practices leads to lowering the groundwater table and to controlling salinity impacts related to excessive irrigation. However, assessing the effects of water-saving practices on the groundwater system requires further investigation. The Jiefangzha Irrigation Scheme of the Hetao Irrigation District is used as a case study for analyzing the temporal and spatial dynamics of the groundwater table. A lumped parameter groundwater balance model has been developed with this purpose and to assess impacts of various water-saving practices. The model was calibrated with monthly datasets relative to the non-frozen periods of 1997–1999 and validated with datasets from 2000 to 2002. Results indicate that canal seepage and deep percolation account for respectively 48% and 44% of the annual groundwater recharge. Groundwater discharge by direct evaporation and plant roots uptake represents 82% of the total annual groundwater discharge. After validation, the model was applied to assess the impacts of various canal and farm irrigation water-saving practices. It was observed that improvements in the canal system (e.g., canal lining, upgrading the hydraulic regulation and control structures, improving delivery schedules) might lower the groundwater table by 0.28–0.48 m, depending upon the level of implementation of these measures. Higher declines of the groundwater table are predicted when water-saving technologies are applied at both the canal and the farm systems. That decline of the water table favours salinity control and reduces capillary rise, thus reducing the groundwater evaporation and uptake by plant roots; that reduction may attain 128 mm. However, predictions may change depending on the way how water-saving measures are applied, which may be different of assumptions made; therefore, there is the need to perform a follow-up of the interventions in order to update predictions. Results indicate the need for appropriate research leading to improved irrigation management when the decline of the groundwater level will reduce groundwater contribution to vegetation growth.

Seasonal variability and source apportionment of metals in the atmospheric deposition in Belgrade

The primary objective of this study is to assess anthropogenic impacts on the environment by determination of element atmospheric depositions. Bulk depositions were collected monthly, from June 2002 to December 2006, at three urban locations in Belgrade. Concentrations of Al, V, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb were analyzed by atomic absorption spectrometry and the current deposition fluxes of atmospheric metals were established. Fourier analysis was applied in order to investigate seasonal variation of the monthly data set. Nickel, V, Fe and Al showed pronounced seasonal dependence, while seasonal variation of the other elements was not evident. The enrichment factors of Pb, Zn, Cd and Cu were obviously above those who could have been caused by natural processes, indicating a mainly anthropogenic origin. Nickel was intermediately enriched suggesting participation of both natural and anthropogenic sources. The multivariate receptor model, Unmix, was used to analyze a 5-yr element atmospheric depositions data set. Three main source profiles (mixed road dust, oil combustion and metal processing) were identified and the overall average percentage source contributions determined.