Zeitschriftenartikel: „Monthly Anomalies“

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Betts, Alan K., Ahmed B. Tawfik und Raymond L. Desjardins. „Revisiting Hydrometeorology Using Cloud and Climate Observations“. Journal of Hydrometeorology 18, Nr. 4 (16.03.2017): 939–55. http://dx.doi.org/10.1175/jhm-d-16-0203.1.

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Abstract This paper uses 620 station years of hourly Canadian Prairie climate data to analyze the coupling of monthly near-surface climate with opaque cloud, a surrogate for radiation, and precipitation anomalies. While the cloud–climate coupling is strong, precipitation anomalies impact monthly climate for as long as 5 months. The April climate has memory of precipitation anomalies back to freeze-up in November, mostly stored in the snowpack. The summer climate has memory of precipitation anomalies back to the beginning of snowmelt in March. In the warm season, mean temperature is strongly correlated to opaque cloud anomalies, but only weakly to precipitation anomalies. Mixing ratio anomalies are correlated to precipitation, but only weakly to cloud. The diurnal cycle of mixing ratio shifts upward with increasing precipitation anomalies. Positive precipitation anomalies are coupled to a lower afternoon lifting condensation level and a higher afternoon equivalent potential temperature; both favor increased convection and precipitation. Regression coefficients on precipitation increase from wet to dry conditions. This is consistent with increased uptake of soil water when monthly precipitation is low, until drought conditions are reached, and also consistent with gravity satellite observations. Regression analysis shows monthly opaque cloud cover is tightly correlated to three climate variables that are routinely observed: diurnal temperature range, mean temperature, and mean relative humidity. The set of correlation coefficients, derived from cloud and climate observations, could be used to evaluate the representation of the land–cloud–atmosphere system in both forecast and climate models.

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Plastun, Alex, Xolani Sibande, Rangan Gupta und Mark E. Wohar. „Historical evolution of monthly anomalies in international stock markets“. Research in International Business and Finance 52 (April 2020): 101127. http://dx.doi.org/10.1016/j.ribaf.2019.101127.

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3

Klein, William H., und Runhua Yang. „Specification of monthly mean surface temperature anomalies in Europe and Asia from concurrent 700 mb monthly mean height anomalies over the Northern Hemisphere“. Journal of Climatology 6, Nr. 5 (1986): 463–84. http://dx.doi.org/10.1002/joc.3370060503.

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4

Taylor, Patrick C. „Variability of Monthly Diurnal Cycle Composites of TOA Radiative Fluxes in the Tropics“. Journal of the Atmospheric Sciences 71, Nr. 2 (01.02.2013): 754–66. http://dx.doi.org/10.1175/jas-d-13-0112.1.

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Abstract Earth system variability is generated by a number of different sources and time scales. Understanding sources of atmospheric variability is critical to reducing the uncertainty in climate models and to understanding the impacts of sampling on observational datasets. The diurnal cycle is a fundamental variability evident in many geophysical variables—including top-of-the-atmosphere (TOA) radiative fluxes. This study considers aspects of the TOA flux diurnal cycle not previously analyzed: namely, deseasonalized variations in the monthly diurnal cycle composites, termed monthly diurnal cycle variability. Significant variability in the monthly diurnal cycle composites is found in both outgoing longwave radiation (OLR) and reflected shortwave (RSW). OLR and RSW monthly diurnal cycle variability exhibits a regional structure that follows traditional, climatological diurnal cycle categorization by prevailing cloud and surface types. The results attribute monthly TOA flux diurnal cycle variability to variations in the diurnal cloud evolution, which is sensitive to monthly atmospheric dynamic- and thermodynamic-state anomalies. The results also suggest that monthly diurnal cycle variability can amplify or buffer monthly TOA flux anomalies, depending on the region. Considering the impact of monthly diurnal cycle variability on monthly TOA flux anomalies, the results suggest that monthly TOA flux diurnal cycle variability must be considered when constructing a TOA flux dataset from sun-synchronous orbit. The magnitude of monthly diurnal composite variability in OLR and RSW is regionally dependent—1–7 W m−2 and 10%–80% relative to interannual TOA flux variability. The largest (4–7 W m−2; 40%–80%) and smallest (1–3 W m−2; 10%–30%) TOA flux uncertainties occur in convective and nonconvective regions, respectively, over both land and ocean.

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Borges, A. V., B. Tilbrook, N. Metzl, A. Lenton und B. Delille. „Inter-annual variability of the carbon dioxide oceanic sink south of Tasmania“. Biogeosciences 5, Nr. 1 (06.02.2008): 141–55. http://dx.doi.org/10.5194/bg-5-141-2008.

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Abstract. We compiled a large data-set from 22 cruises spanning from 1991 to 2003, of the partial pressure of CO2 (pCO2) in surface waters over the continental shelf (CS) and adjacent open ocean (43° to 46° S; 145° to 150° E), south of Tasmania. Climatological seasonal cycles of pCO2 in the CS, the subtropical zone (STZ) and the subAntarctic zone (SAZ) are described and used to determine monthly pCO2 anomalies. These are used in combination with monthly anomalies of sea surface temperature (SST) to investigate inter-annual variations of SST and pCO2. Monthly anomalies of SST (as intense as 2°C) are apparent in the CS, STZ and SAZ, and are indicative of strong inter-annual variability that seems to be related to large-scale coupled atmosphere-ocean oscillations. Anomalies of pCO2 normalized to a constant temperature are negatively related to SST anomalies. A reduced winter-time vertical input of dissolved inorganic carbon (DIC) during phases of positive SST anomalies, related to a poleward shift of westerly winds, and a concomitant local decrease in wind stress is the likely cause of the negative relationship between pCO2 and SST anomalies. The observed pattern is an increase of the sink for atmospheric CO2 associated with positive SST anomalies, although strongly modulated by inter-annual variability of wind speed. Assuming that phases of positive SST anomalies are indicative of the future evolution of regional ocean biogeochemistry under global warming, we show using a purely observational based approach that some provinces of the Southern Ocean could provide a potential negative feedback on increasing atmospheric CO2.

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Lagos, P., Y. Silva, E. Nickl und K. Mosquera. „El Niño – related precipitation variability in Perú“. Advances in Geosciences 14 (10.04.2008): 231–37. http://dx.doi.org/10.5194/adgeo-14-231-2008.

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Abstract. The relationship between monthly mean sea surface temperature (SST) anomalies in the commonly used El Niño regions and precipitation for 44 stations in Perú is documented for 1950–2002. Linear lag correlation analysis is employed to establish the potential for statistical precipitation forecasts from SSTs. Useful monthly mean precipitation anomaly forecasts are possible for several locations and calendar months if SST anomalies in El Niño 1+2, Niño 3.4, and Niño 4 regions are available. Prediction of SST anomalies in El Niño regions is routinely available from Climate Prediction Center, NOAA, with reasonable skill in the El Niño 3.4 region, but the prediction in El Niño 1+2 region is less reliable. The feasibility of using predicted SST anomalies in the El Niño 3.4 region to predict SST anomalies in El Niño 1+2 region is discussed.

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7

Kossowska-Cezak, Urszula. „Monthly thermal and precipitation anomalies in Warsaw and their causes“. Miscellanea Geographica 7, Nr. 1 (01.03.1996): 71–76. http://dx.doi.org/10.2478/mgrsd-1996-070110.

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CASTILLA, EDUARDO E., IEDA M. ORIOLI, REGINA LUGARINHO, GRACA P. DUTRA, JORGE S. LOPEZ-CAMELO, HEBE E. CAMPANA, AMEDEO SPAGNOLO und PIERPAOLO MASTROIACOVO. „Monthly and Seasonal Variations in the Frequency of Congenital Anomalies“. International Journal of Epidemiology 19, Nr. 2 (1990): 399–404. http://dx.doi.org/10.1093/ije/19.2.399.

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9

Smith, Thomas M., Phillip A. Arkin, Mathew R. P. Sapiano und Ching-Yee Chang. „Merged Statistical Analyses of Historical Monthly Precipitation Anomalies Beginning 1900“. Journal of Climate 23, Nr. 21 (01.11.2010): 5755–70. http://dx.doi.org/10.1175/2010jcli3530.1.

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Abstract A monthly reconstruction of precipitation beginning in 1900 is presented. The reconstruction resolves interannual and longer time scales and spatial scales larger than 5° over both land and oceans. Because of different land and ocean data availability, the reconstruction combines two separate historical reconstructions. One analyzes interannual variations directly by fitting gauge-based anomalies to large-scale spatial modes. This direct reconstruction is used for land anomalies and interannual oceanic anomalies. The other analyzes annual and longer variations indirectly from correlations with analyzed sea surface temperature and sea level pressure. This indirect reconstruction is used for oceanic variations with time scales longer than interannual. In addition, a method of estimating reconstruction errors is also presented. Over land the reconstruction is a filtered representation of the gauge data with data gaps filled. Over oceans the reconstruction gives an estimate of the atmospheric response to changing temperature and pressure, combined with interannual variations. The reconstruction makes it possible to evaluate global precipitation variations for periods much longer than the satellite period, which begins in 1979. Evaluations show some large-scale similarities with coupled model precipitation variations over the twentieth century, including an increasing tendency over the century. The reconstructed land and sea trends tend to be out of phase at low latitudes, similar to the out-of-phase relationship for interannual variations. This reconstruction may be used for climate monitoring, for statistical climate studies of the twentieth century, and for helping to evaluate dynamic climate models. In the future the possibility of improving the reconstruction will be explored by further improving the analysis methods and including additional data.

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Krokhin, V. V., und W. M. J. Luxemburg. „Temperatures and precipitation totals over the Russian Far East and Eastern Siberia: long-term variability and its links to teleconnection indices“. Hydrology and Earth System Sciences 11, Nr. 6 (27.11.2007): 1831–41. http://dx.doi.org/10.5194/hess-11-1831-2007.

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Abstract. The present study examines the spatial-temporal regime of the mean monthly temperature (MMT) and monthly precipitation (MPT) anomalies over the Russian Far East and Eastern Siberia for the period 1949–2003. The original data were analyzed spatially by means of complex principal component analysis and temporally by means of the maximum entropy method and traditional Fourier spectral analysis. The interannual variability in these anomalies can be represented by the single dominant modes. These dominant modes oscillate with periods of about 2–3 yr and 6–8 yr that are accompanied by statistically significant changes in such monthly teleconnection indices, as the Arctic and North Pacific Oscillations.

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Krokhin, V. V., und W. M. J. Luxemburg. „Temperatures and precipitation totals over the Russian Far East and Eastern Siberia: long-term variability and its links to teleconnection indices“. Hydrology and Earth System Sciences Discussions 3, Nr. 4 (26.07.2006): 1915–42. http://dx.doi.org/10.5194/hessd-3-1915-2006.

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Abstract. The present study examines the spatial-temporal regime of the mean monthly temperature (MMT) and monthly precipitation (MPT) anomalies over the Russian Far East and Eastern Siberia for the period 1949–2003. The original data were analyzed spatially by means of complex principal component analysis and temporally by means of the maximum entropy method and traditional Fourier spectral analysis. The interannual variability in these anomalies can be represented by the single dominant modes. These dominant modes oscillate with periods of about 2–3 yr and 6–8 yr that are accompanied by statistically significant changes in such monthly teleconnection indices, as the Arctic and North Pacific Oscillations.

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Ewen, Tracy, Andrea Grant und Stefan Brönnimann. „A Monthly Upper-Air Dataset for North America Back to 1922 from the Monthly Weather Review“. Monthly Weather Review 136, Nr. 5 (01.05.2008): 1792–805. http://dx.doi.org/10.1175/2007mwr2202.1.

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Abstract Upper-air observations with kites, aircraft, and radiosondes were performed in the United States operationally since the 1890s. In this paper, the authors present a reevaluation of newly digitized monthly mean values from the Monthly Weather Review back to 1922. Data from 46 U.S. weather stations are presented with a focus on early kite and aircraft observations during the 1922–38 period. A quality assessment of the data, based on reconstructed reference series, is carried out and the quality of the monthly mean data is found to be sufficient for analysis of variability in upper-level circulation. Anomalies of upper-level temperatures from the reevaluated station data, together with surface fields, are shown for selected periods.

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Krikken, F., und W. Hazeleger. „Arctic Energy Budget in Relation to Sea Ice Variability on Monthly-to-Annual Time Scales“. Journal of Climate 28, Nr. 16 (10.08.2015): 6335–50. http://dx.doi.org/10.1175/jcli-d-15-0002.1.

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Abstract The large decrease in Arctic sea ice in recent years has triggered a strong interest in Arctic sea ice predictions on seasonal-to-decadal time scales. Hence, it is important to understand physical processes that provide enhanced predictability beyond persistence of sea ice anomalies. This study analyzes the natural variability of Arctic sea ice from an energy budget perspective, using 15 climate models from phase 5 of CMIP (CMIP5), and compares these results to reanalysis data. The authors quantify the persistence of sea ice anomalies and the cross correlation with the surface and top-of-atmosphere energy budget components. The Arctic energy balance components primarily indicate the important role of the seasonal ice–albedo feedback, through which sea ice anomalies in the melt season reemerge in the growth season. This is a robust anomaly reemergence mechanism among all 15 climate models. The role of the ocean lies mainly in storing heat content anomalies in spring and releasing them in autumn. Ocean heat flux variations play only a minor role. Confirming a previous (observational) study, the authors demonstrate that there is no direct atmospheric response of clouds to spring sea ice anomalies, but a delayed response is evident in autumn. Hence, there is no cloud–ice feedback in late spring and summer, but there is a cloud–ice feedback in autumn, which strengthens the ice–albedo feedback. Anomalies in insolation are positively correlated with sea ice variability. This is primarily a result of reduced multiple reflection of insolation due to an albedo decrease. This effect counteracts the ice-albedo effect up to 50%. ERA-Interim and Ocean Reanalysis System 4 (ORAS4) confirm the main findings from the climate models.

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Navarra, A. „Simulation of monthly mean circulation anomalies using a linear anomay model“. Il Nuovo Cimento C 15, Nr. 3 (Mai 1992): 253–63. http://dx.doi.org/10.1007/bf02533650.

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Murata, Akihiko M. „Monthly-mean temperature anomalies in relation to spatial scale in Japan“. International Journal of Climatology 13, Nr. 3 (April 1993): 329–41. http://dx.doi.org/10.1002/joc.3370130308.

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16

Kato, Seiji. „Interannual Variability of the Global Radiation Budget“. Journal of Climate 22, Nr. 18 (15.09.2009): 4893–907. http://dx.doi.org/10.1175/2009jcli2795.1.

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Abstract Interannual variability of the global radiation budget, regions that contribute to its variability, and what limits albedo variability are investigated using Clouds and the Earth’s Radiant Energy System (CERES) data taken from March 2000 through February 2004. Area-weighted mean top-of-atmosphere (TOA) reflected shortwave, longwave, and net irradiance standard deviations computed from monthly anomalies over a 1° × 1° region are 9.6, 7.6, and 7.6 W m−2, respectively. When standard deviations are computed from global monthly anomalies, they drop to 0.5, 0.4, and 0.4 W m−2, respectively. Clouds are mostly responsible for the variation. Regions with a large standard deviation of TOA shortwave and longwave irradiance at TOA are the tropical western and central Pacific, which is caused by shifting from La Niña to El Niño during this period. However, a larger standard deviation of 300–1000-hPa thickness anomalies occurs in the polar region instead of the tropics. The correlation coefficient between atmospheric net irradiance anomalies and 300–1000-hPa thickness anomalies is negative. These indicate that temperature anomalies in the atmosphere are mostly a result of anomalies in longwave and dynamical processes that transport energy poleward, instead of albedo anomalies by clouds directly affecting temperature anomalies in the atmosphere. With simple zonal-mean thermodynamic energy equations it is demonstrated that temperature anomalies decay exponentially with time by longwave emission and by dynamical processes. As a result, the mean meridional temperature gradient is maintained. Therefore, mean meridional circulations are not greatly altered by albedo anomalies on an annual time scale, which in turn provides small interannual variability of the global mean albedo.

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Nakamura, Mototaka, und Shozo Yamane. „Dominant Anomaly Patterns in the Near-Surface Baroclinicity and Accompanying Anomalies in the Atmosphere and Oceans. Part I: North Atlantic Basin“. Journal of Climate 22, Nr. 4 (15.02.2009): 880–904. http://dx.doi.org/10.1175/2008jcli2297.1.

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Abstract Variability in the monthly mean flow and storm track in the North Atlantic basin is examined with a focus on the near-surface baroclinicity, B = Bxi + Byj. Dominant patterns of anomalous B found from empirical orthogonal function (EOF) analyses generally show patterns of shift and changes in the strength of B. Composited anomalies in the monthly mean wind at various pressure levels based on the signals in the EOFs display robust accompanying anomalies in the mean flow up to 50 hPa in the winter and up to 100 hPa in other seasons. Anomalous eddy fields accompanying the anomalous Bx patterns exhibit, broadly speaking, structures anticipated from linear theories of baroclinic instabilities and suggest a tendency for anomalous wave fluxes to accelerate/decelerate the surface westerly accordingly. Atmospheric anomalies accompanying By anomalies have patterns different from those that accompany Bx anomalies but are as large as those found for Bx. Anomalies in the sea surface temperature (SST) found for the anomalous patterns of Bx often show large values of small spatial scales along the Gulf Stream (GS), indicating that a meridional shift in the position of the GS and/or changes in the heat transport by the GS may be responsible for the anomalous Bx and concomitant tropospheric and lower-stratospheric anomalies. Anomalies in the net surface heat flux, SST in preceding months, and meridional eddy heat flux in the lower troposphere support this interpretation.

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Zhou, Xinyao, Yongqiang Zhang, Yonghui Yang, Yanmin Yang und Shumin Han. „Evaluation of anomalies in GLDAS-1996 dataset“. Water Science and Technology 67, Nr. 8 (01.04.2013): 1718–27. http://dx.doi.org/10.2166/wst.2013.043.

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Global Land Data Assimilation System (GLDAS) data are widely used for land-surface flux simulations. Therefore, the simulation accuracy using GLDAS dataset is largely contingent upon the accuracy of the GLDAS dataset. It is found that GLDAS land-surface model simulated runoff exhibits strong anomalies for 1996. These anomalies are investigated by evaluating four GLDAS meteorological forcing data (precipitation, air temperature, downward shortwave radiation and downward longwave radiation) in six large basins across the world (Danube, Mississippi, Yangtze, Congo, Amazon and Murray-Darling basins). Precipitation data from the Global Precipitation Climatology Centre (GPCC) are also compared with GLDAS forcing precipitation data. Large errors and lack of monthly variability in GLDAS-1996 precipitation data are the main sources for the anomalies in the simulated runoff. The impact of the precipitation data on simulated runoff for 1996 is investigated with the Community Atmosphere Biosphere Land Exchange (CABLE) land-surface model in the Yangtze basin, for which area high-quality local precipitation data are obtained from the China Meteorological Administration (CMA). The CABLE model is driven by GLDAS daily precipitation data and CMA daily precipitation, respectively. The simulated daily and monthly runoffs obtained from CMA data are noticeably better than those obtained from GLDAS data, suggesting that GLDAS-1996 precipitation data are not so reliable for land-surface flux simulations.

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Varotsos, C. A., und M. N. Efstathiou. „On the scaling effect in global surface air temperature anomalies“. Atmospheric Chemistry and Physics Discussions 12, Nr. 6 (08.06.2012): 14727–46. http://dx.doi.org/10.5194/acpd-12-14727-2012.

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Abstract. The annual and the monthly mean values of the land-surface air temperature anomalies during 1880–2011, over both hemispheres, are used to investigate the existence of long-range correlations in their temporal march. The analytical tool employed is the detrended fluctuation analysis which eliminates the noise of the non-stationarities that characterize the land-surface air temperature anomalies in both hemispheres. The main result obtained is that deviations of one sign of the land-surface air temperature anomalies in both hemispheres are generally followed by deviations with the same sign at different time intervals. In other words the land-surface air temperature anomalies exhibit persistent behaviour i.e., deviations tend to keep the same sign. Specifically, the scaling exponents of the annual (monthly) mean land-surface air temperature anomalies, α = 0.65 (0.73–0.75), are roughly equal in both hemispheres approaching to that of the global annual (monthly) mean land-surface air temperature anomalies, α =0.68 (0.80). Taking into account our earlier study according to which the land and sea surface temperature anomalies obey scaling exponents α =0.78 and α = 0.89 in the Northern and Southern Hemisphere, respectively, we conclude that the difference between the scaling exponents in both sea and land contributions to the surface air temperature stems mainly from the sea surface temperature, which exhibits stronger memory in the Southern than in the Northern Hemisphere. This conclusion may be attributed to the fact that oceans have the greatest capacity to store heat, being thus able to regulate the temperature on land with less pronounced persistence. Moreover, the variability of the scaling-exponents of the annual mean values of the land-surface air temperature anomalies versus latitude shows an increasing trend from the low to polar regions starting from the classical random walk (white noise) over tropics. The gradual increase of the scaling exponent from the low to high latitudes (which is stronger over the Southern Hemisphere) could be associated with the poleward increase in climate sensitivity predicted by the global climate models. In this context, the persistence in the land-surface air temperature enhances the feasibility of its reliable long-term forecast, which is very important for various climate applications.

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Canchala, Teresita, Wilfredo Alfonso-Morales, Yesid Carvajal-Escobar, Wilmar L. Cerón und Eduardo Caicedo-Bravo. „Monthly Rainfall Anomalies Forecasting for Southwestern Colombia Using Artificial Neural Networks Approaches“. Water 12, Nr. 9 (20.09.2020): 2628. http://dx.doi.org/10.3390/w12092628.

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Improving the accuracy of rainfall forecasting is relevant for adequate water resources planning and management. This research project evaluated the performance of the combination of three Artificial Neural Networks (ANN) approaches in the forecasting of the monthly rainfall anomalies for Southwestern Colombia. For this purpose, we applied the Non-linear Principal Component Analysis (NLPCA) approach to get the main modes, a Neural Network Autoregressive Moving Average with eXogenous variables (NNARMAX) as a model, and an Inverse NLPCA approach for reconstructing the monthly rainfall anomalies forecasting in the Andean Region (AR) and the Pacific Region (PR) of Southwestern Colombia, respectively. For the model, we used monthly rainfall lagged values of the eight large-scale climate indices linked to the El Niño Southern Oscillation (ENSO) phenomenon as exogenous variables. They were cross-correlated with the main modes of the rainfall variability of AR and PR obtained using NLPCA. Subsequently, both NNARMAX models were trained from 1983 to 2014 and tested for two years (2015–2016). Finally, the reconstructed outputs from the NNARMAX models were used as inputs for the Inverse NLPCA approach. The performance of the ANN approaches was measured using three different performance metrics: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Pearson’s correlation (r). The results showed suitable forecasting performance for AR and PR, and the combination of these ANN approaches demonstrated the possibility of rainfall forecasting in these sub-regions five months in advance and provided useful information for the decision-makers in Southwestern Colombia.

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Ferrone, Alfonso, Daniele Mastrangelo und Piero Malguzzi. „Multimodel probabilistic prediction of 2 m-temperature anomalies on the monthly timescale“. Advances in Science and Research 14 (08.05.2017): 123–29. http://dx.doi.org/10.5194/asr-14-123-2017.

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Abstract. The 2 m-temperature anomalies from the reforecasts of the CNR-ISAC and ECMWF monthly prediction systems have been combined in a multimodel super-ensemble. Tercile probability predictions obtained from the multimodel have been constructed using direct model outputs (DMO) and model output statistics (MOS), like logistic and nonhomogeneous Gaussian regression, for the 1990–2010 winter seasons. Verification with ERA-Interim reanalyses indicates that logistic regression gives the best results in terms of ranked probability skill scores (RPSS) and reliability diagrams for low–medium forecast probabilities. Also, it is argued that the logistic regression would not yield further improvements if a larger dataset was used.

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Robertson, Andrew W. „Diagnosis of Regional Monthly Anomalies Using the Adjoint Method. Part I: Temperature“. Journal of the Atmospheric Sciences 49, Nr. 11 (Juni 1992): 885–905. http://dx.doi.org/10.1175/1520-0469(1992)049<0885:dormau>2.0.co;2.

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Mo, Kingtse C., und Eugenia Kalnay. „Impact of Sea Surface Temperature Anomalies on the Skill of Monthly Forecasts“. Monthly Weather Review 119, Nr. 12 (Dezember 1991): 2771–93. http://dx.doi.org/10.1175/1520-0493(1991)119<2771:iossta>2.0.co;2.

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Klein, William H., und Ying Dai. „Reconstruction of Monthly Mean 700-mb Heights from Surface Data by Reverse Specification“. Journal of Climate 11, Nr. 8 (01.08.1998): 2136–46. http://dx.doi.org/10.1175/1520-0442-11.8.2136.

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Abstract This paper demonstrates an objective method of computing monthly mean 700-mb height anomalies (H) at 108 grid points in the Western Hemisphere for a 40-yr period as a function of concurrent anomalies of monthly mean sea level pressure (P), at the same 108 points used for H, and monthly mean surface air temperature (T) averaged over 112 areas in North America. The authors applied a forward stepwise program to derive linear multiple regression equations that explained 81% of the variance of H by means of only 3.5 variables, averaged over all months and grid points. The stability of these equations held up well on 6 yr of independent data in terms of explained variance, root-mean-square error, and the spatial anomaly correlation coefficient. Therefore, it seems feasible to reconstruct maps of H for the first half of the twentieth century as a function of data on P and T only.

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Shrestha, Prabhakar. „Clouds and Vegetation Modulate Shallow Groundwater Table Depth“. Journal of Hydrometeorology 22, Nr. 4 (April 2021): 753–63. http://dx.doi.org/10.1175/jhm-d-20-0171.1.

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AbstractA 10-yr simulation of shallow groundwater table (GWT) depth over a temperate region in northwestern Europe, using a physics-based integrated hydrological model at kilometer scale, exhibits a strong seasonal cycle. This is also well captured in terms of near-surface soil moisture anomalies, terrestrial water storage anomalies, and shallow GWT depth anomalies from observations over the region. The modeled monthly anomaly of GWT depth exhibits a statistically significant (p < 0.05) moderate positive/negative correlation with non-rain- and rain-affected monthly anomalies of incoming solar radiation. The vegetation cover also produces a strong local control on the variability of shallow GWT depth. Thus, much of the variability in the simulated seasonal cycle of shallow GWT depth could be linked to the distribution of clouds and vegetation. The spatiotemporal distribution of clouds, partly influenced by the Rhine Massif, modulates the seasonal variability of incoming solar radiation and precipitation over the region. Particularly, the southwestern and northern part of the Rhine Massif divided by the Rhine Valley exhibits a dipole behavior with relatively high (low) shallow GWT depth fluctuations, associated with positive (negative) anomaly of incoming solar radiation and negative (positive) anomaly of precipitation.

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Gulseven, Osman. „Multidimensional Analysis of Monthly Stock Market Returns“. Annals of the Alexandru Ioan Cuza University - Economics 61, Nr. 2 (01.12.2014): 181–96. http://dx.doi.org/10.2478/aicue-2014-0013.

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Abstract This study examines the monthly returns in Turkish and American stock market indices to investigate whether these markets experience abnormal returns during some months of the calendar year. The data used in this research includes 212 observations between January 1996 and August 2014. I apply statistical summary analysis, decomposition technique, dummy variable estimation, and binary logistic regression to check for the monthly market anomalies. The multidimensional methods used in this article suggest weak evidence against the efficient market hypothesis on monthly returns. While some months tend to show abnormal returns, there is no absolute unanimity in the applied approaches. Nevertheless, there is a strikingly negative May effect on the Turkish stocks following a positive return in April. Stocks tend to be bullish in December in both markets, yet we do not observe anya significant January effect is not observed.

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Klein, William H. „Specification of monthly mean anomalies of surface air temperature in Canada and Alaska“. Atmosphere-Ocean 23, Nr. 2 (Juni 1985): 155–76. http://dx.doi.org/10.1080/07055900.1985.9649220.

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Robertson, Andrew W. „Diagnosis of Regional Monthly Anomalies Using the Adjoint Method. Part II: Potential Vorticity“. Journal of the Atmospheric Sciences 49, Nr. 11 (Juni 1992): 906–18. http://dx.doi.org/10.1175/1520-0469(1992)049<0906:dormau>2.0.co;2.

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Maryon, R. H., und A. M. Storey. „A multivariate statistical model for forecasting anomalies of half-monthly mean surface pressure“. Journal of Climatology 5, Nr. 5 (September 1985): 561–78. http://dx.doi.org/10.1002/joc.3370050509.

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Evtimov, S., und M. Ivanov. „Intraannual dissimilarities between monthly mean Northern Hemisphere temperature anomalies during the twentieth century“. Theoretical and Applied Climatology 90, Nr. 3-4 (09.07.2007): 161–68. http://dx.doi.org/10.1007/s00704-007-0307-3.

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Selvam, A. M. „Signatures of universal characteristics of fractal fluctuations in global mean monthly temperature anomalies“. Journal of Systems Science and Complexity 24, Nr. 1 (Februar 2011): 14–38. http://dx.doi.org/10.1007/s11424-011-9020-5.

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Klein, William H., und Bruce T. Whistler. „Specification of monthly mean anomalies of fire weather elements in the United States“. Agricultural and Forest Meteorology 56, Nr. 1-2 (Juli 1991): 145–72. http://dx.doi.org/10.1016/0168-1923(91)90109-4.

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Wu, Qigang, und Xiangdong Zhang. „Observed Evidence of an Impact of the Antarctic Sea Ice Dipole on the Antarctic Oscillation“. Journal of Climate 24, Nr. 16 (15.08.2011): 4508–18. http://dx.doi.org/10.1175/2011jcli3965.1.

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Abstract A lagged maximum covariance analysis (MCA) is applied to investigate the linear covariability between monthly sea ice concentration (SIC) and 500-mb geopotential height (Z500) in the Southern Hemisphere (SH). The dominant signal is the atmospheric forcing of SIC anomalies throughout the year, but statistically significant covariances are also found between austral springtime Z500 and prior SIC anomalies up to four months earlier. The MCA pattern is characterized by an Antarctic dipole (ADP)-like pattern in SIC and a positively polarized Antarctic Oscillation (AAO) in Z500. Such long lead-time covariance suggests the forcing of the AAO by persistent ADP-like SIC anomalies. The leading time of SIC anomalies provides an implication for skillful predictability of springtime atmospheric variability.

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Camiolo, M. D., E. Cozzolino und A. J. Jaureguizar. „Material Particulado en Suspensión en el Río de la Plata: importancia del río Bermejo en su variabilidad espacio-temporal“. Revista de Teledetección, Nr. 51 (29.06.2018): 1. http://dx.doi.org/10.4995/raet.2018.9864.

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<p>Spatio-temporal variability of Suspended Particulate Matter (SPM) in the Río de la Plata (RdlP) is analyzed from 2002-2014 of MODIS (Moderate Resolution Imaging Spectroradiometer) data and explained in terms of its main tributaries flows. The monthly mean showed maximum during late summer to mid-autumn, and minimum in mid-winter to early summer. The Bermejo river (BeR), is the tributary that more sediment in suspension brings. This situation was reflected in the significant relationship between the mean monthly concentrations of SPM with the average monthly flow of BeR. Seasonal variation in SPM concentration, showed maximum values in fall, followed by summer, and minimum values in winter and spring, reflecting the monthly pattern of discharge of the BeR with one and two months of delay. The pattern of spatial variation differentiated threes regions: the inner, central and outer. The annual variability evidenced a marked seasonality in the spatial coverage pattern of the waters with the highest SPM. The pattern of the anomalies, appeared to be related to the influence of river discharge, what it showed the temporal pattern of SPM anomalies did not related to the ENSO (El Niño – Sourthen Oscillation) cycle. These results allowed us to denote the importance of BeR (not ENSO dependent) to explain the pattern of observed SPM anomaly in the RdlP region.</p>

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de Boisséson, E., M. A. Balmaseda, F. Vitart und K. Mogensen. „Impact of the sea surface temperature forcing on hindcasts of Madden-Julian Oscillation events using the ECMWF model“. Ocean Science Discussions 9, Nr. 4 (23.07.2012): 2535–59. http://dx.doi.org/10.5194/osd-9-2535-2012.

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Abstract. This paper explores the sensitivity of the prediction of Madden Julian Oscillation (MJO) events to different aspects of the sea surface temperature (SST) in the European Centre for Medium-range Weather Forecasts (ECMWF) model. The impact of temporal resolution of SST on the MJO is first evaluated via a set of monthly hindcast experiments. The experiments are conducted with an atmosphere forced by persisted SST anomalies, monthly and weekly SSTs. Skill scores are clearly degraded when weekly SSTs are replaced by monthly values or persisted anomalies. The new high resolution OSTIA SST daily reanalysis would in principle allow to establish the impact of daily versus weekly SST values on the MJO prediction. It is found however that OSTIA SSTs provide lower skill scores than the weekly product. Further experiments show that this loss of skill cannot be attributed to either the mean state or the daily frequency of OSTIA SSTs. Additional diagnostics show that the phase relationship between OSTIA SSTs and tropical convection is not optimal with repspect to observations. Such result suggests that capturing the correct SST-convection phase relationship is a major challenge for the MJO predictions.

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Lin, Jyh-Woei. „Latitude-Time Total Electron Content Anomalies as Precursors to Japan's Large Earthquakes Associated with Principal Component Analysis“. International Journal of Geophysics 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/763527.

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The goal of this study is to determine whether principal component analysis (PCA) can be used to process latitude-time ionospheric TEC data on a monthly basis to identify earthquake associated TEC anomalies. PCA is applied to latitude-time (mean-of-a-month) ionospheric total electron content (TEC) records collected from the Japan GEONET network to detect TEC anomalies associated with 18 earthquakes in Japan () from 2000 to 2005. According to the results, PCA was able to discriminate clear TEC anomalies in the months when all 18 earthquakes occurred. After reviewing months when no earthquakes occurred but geomagnetic storm activity was present, it is possible that the maximal principal eigenvalues PCA returned for these 18 earthquakes indicate earthquake associated TEC anomalies. Previously PCA has been used to discriminate earthquake-associated TEC anomalies recognized by other researchers, who found that statistical association between large earthquakes and TEC anomalies could be established in the 5 days before earthquake nucleation; however, since PCA uses the characteristics of principal eigenvalues to determine earthquake related TEC anomalies, it is possible to show that such anomalies existed earlier than this 5-day statistical window.

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Gu, X., und J. Jiang. „A complex autoregressive model and application to monthly temperature forecasts“. Annales Geophysicae 23, Nr. 10 (30.11.2005): 3229–35. http://dx.doi.org/10.5194/angeo-23-3229-2005.

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Abstract. A complex autoregressive model was established based on the mathematic derivation of the least squares for the complex number domain which is referred to as the complex least squares. The model is different from the conventional way that the real number and the imaginary number are separately calculated. An application of this new model shows a better forecast than forecasts from other conventional statistical models, in predicting monthly temperature anomalies in July at 160 meteorological stations in mainland China. The conventional statistical models include an autoregressive model, where the real number and the imaginary number are separately disposed, an autoregressive model in the real number domain, and a persistence-forecast model.

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Wu, Qigang, Haibo Hu und Lujun Zhang. „Observed Influences of Autumn–Early Winter Eurasian Snow Cover Anomalies on the Hemispheric PNA-like Variability in Winter“. Journal of Climate 24, Nr. 7 (01.04.2011): 2017–23. http://dx.doi.org/10.1175/2011jcli4236.1.

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Abstract The impact of the Eurasian snow cover extent on the Northern Hemisphere (NH) circulation is investigated by applying a lagged maximum covariance analysis (MCA) to monthly satellite-derived snow cover and NCEP reanalysis data. Wintertime atmospheric signals significantly correlated with persistently autumn–early winter snow cover anomalies are found in the leading two MCA modes. The first MCA mode indicates the effect of Eurasian snow cover anomalies on the Arctic Oscillation/North Atlantic Oscillation (AO/NAO). The second MCA mode corresponds with the forcing of Eurasian snow cover anomalies on the hemispheric Pacific–North America (PNA)-like atmospheric variations. This snow–atmosphere relationship may present a significant potential for wintertime predictability.

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B., Shakila, Prakash Pinto und Iqbal Thonse Hawaldar. „Semi-monthly effect in stock returns: new evidence from Bombay Stock Exchange“. Investment Management and Financial Innovations 14, Nr. 3 (25.10.2017): 160–72. http://dx.doi.org/10.21511/imfi.14(3-1).2017.01.

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Semi-monthly effect is a kind of calendar anomalies which is less explored in the financial literature. The main objective of this paper to investigate the presence of semi-monthly effect in selected sectoral indices of Bombay Stock Exchange (BSE). The study uses the daily stock returns of five sectoral indices viz S&amp;P BSE Auto Index, S&amp;P BSE Bankex, S&amp;P BSE Consumer Durables Index, S&amp;P BSE FMCG Index and S&amp;P BSE Health Care Index for the period of 10 years starting from 1st April 2007 to 31st March 2017. The data were analyzed using two approaches namely calendar days approach and trading days approach. To test the equality of mean returns for the two halves of the month, Mann-Whitney U test is used. The empirical results of the study did not provide any evidence for the presence of semi-monthly effect in the selected sectoral indices. Nevertheless, BSE Auto Index showed significant difference in the mean returns of first half and second half of trading month during the study period.

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Ma, Yueling, Carsten Montzka, Bagher Bayat und Stefan Kollet. „Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe“. Hydrology and Earth System Sciences 25, Nr. 6 (23.06.2021): 3555–75. http://dx.doi.org/10.5194/hess-25-3555-2021.

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Abstract. Many European countries rely on groundwater for public and industrial water supply. Due to a scarcity of near-real-time water table depth (wtd) observations, establishing a spatially consistent groundwater monitoring system at the continental scale is a challenge. Hence, it is necessary to develop alternative methods for estimating wtd anomalies (wtda) using other hydrometeorological observations routinely available near real time. In this work, we explore the potential of Long Short-Term Memory (LSTM) networks for producing monthly wtda using monthly precipitation anomalies (pra) as input. LSTM networks are a special category of artificial neural networks that are useful for detecting a long-term dependency within sequences, in our case time series, which is expected in the relationship between pra and wtda. In the proposed methodology, spatiotemporally continuous data were obtained from daily terrestrial simulations of the Terrestrial Systems Modeling Platform (TSMP) over Europe (hereafter termed the TSMP-G2A data set), with a spatial resolution of 0.11∘, ranging from the years 1996 to 2016. The data were separated into a training set (1996–2012), a validation set (2013–2014), and a test set (2015–2016) to establish local networks at selected pixels across Europe. The modeled wtda maps from LSTM networks agreed well with TSMP-G2A wtda maps on spatially distributed dry and wet events, with 2003 and 2015 constituting drought years over Europe. Moreover, we categorized the test performances of the networks based on intervals of yearly averaged wtd, evapotranspiration (ET), soil moisture (θ), snow water equivalent (Sw), soil type (St), and dominant plant functional type (PFT). Superior test performance was found at the pixels with wtd < 3 m, ET > 200 mm, θ>0.15 m3 m−3, and Sw<10 mm, revealing a significant impact of the local factors on the ability of the networks to process information. Furthermore, results of the cross-wavelet transform (XWT) showed a change in the temporal pattern between TSMP-G2A pra and wtda at some selected pixels, which can be a reason for undesired network behavior. Our results demonstrate that LSTM networks are useful for producing high-quality wtda based on other hydrometeorological data measured and predicted at large scales, such as pra. This contribution may facilitate the establishment of an effective groundwater monitoring system over Europe that is relevant to water management.

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Kinnard, Christophe, Christian M. Zdanowicz, David A. Fisher, Bea Alt und Steve Mccourt. „Climatic analysis of Sea-ice variability in the Canadian Arctic from operational charts, 1980–2004“. Annals of Glaciology 44 (2006): 391–402. http://dx.doi.org/10.3189/172756406781811123.

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AbstractWe present a complete climatic analysis of Sea-ice conditions in the Canadian Arctic based on digitized operational charts from the Canadian Ice Service for the period 1980–2004. The Seasonal climatology, Spatial variance and linear trends in total ice concentrations (CT) were calculated. The maximum reduction rate in CT was found in the Beaufort Sea (>24% decade–1) and in the Davis Strait/Labrador Sea region (>18% decade–1) during Spring and Summer. Empirical orthogonal function (EOF) analysis performed on monthly CT deviations yielded four Significant EOF modes explaining 32% of the total variance. The Spatial pattern, temporal behaviour and Seasonality of these four EOF modes are discussed and correlated with fields of Sea-level pressure, Surface winds, Surface air temperature and Sea-surface temperature monthly anomalies. These results point to the dominant influence of the North Atlantic Oscillation on CT decadal anomalies during the cold Season, while climate variability in the Pacific influences CT variations in the Beaufort Sea region during Spring–summer.

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Adem, Julián. „On the seasonal effect of orbital variations on the climates of the next 4000 years“. Annales Geophysicae 14, Nr. 11 (30.11.1996): 1198–206. http://dx.doi.org/10.1007/s00585-996-1198-9.

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Abstract. A northern hemisphere thermodynamic climate model is used to compute the effect of the insolation anomalies due to orbital variations in the climates for the next 4000 years. Berger's mean monthly anomalies of insolation are used in the computations, which are carried out for 1000, 2000, 3000 and 4000 years after present (kyears AP). The numerical simulations show that in the climates of the next 4000 years, due to the effect of the orbital variations, springs and summers will be increasingly dryer and falls and winters wetter than the present climate.

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Chelliah, Muthuvel, und Phillip Arkin. „Large-Scale Interannual Variability of Monthly Outgoing Longwave Radiation Anomalies over the Global Tropics“. Journal of Climate 5, Nr. 4 (April 1992): 371–89. http://dx.doi.org/10.1175/1520-0442(1992)005<0371:lsivom>2.0.co;2.

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Villanueva, E. E., V. M. Mendoza und J. Adem. „Monthly and seasonal prediction of sea surface temperature anomalies in the Gulf of Mexico“. Journal of Marine Systems 26, Nr. 3-4 (November 2000): 289–302. http://dx.doi.org/10.1016/s0924-7963(00)00040-3.

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Sankarasubramanian, A., Upmanu Lall und Susan Espinueva. „Role of Retrospective Forecasts of GCMs Forced with Persisted SST Anomalies in Operational Streamflow Forecasts Development“. Journal of Hydrometeorology 9, Nr. 2 (01.04.2008): 212–27. http://dx.doi.org/10.1175/2007jhm842.1.

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Abstract Seasonal streamflow forecasts contingent on climate information are essential for water resources planning and management as well as for setting up contingency measures during extreme years. In this study, operational streamflow forecasts are developed for a reservoir system in the Philippines using ECHAM4.5 precipitation forecasts (EPF) obtained using persisted sea surface temperature (SST) scenarios. Diagnostic analyses on SST conditions show that the tropical SSTs influence the streamflow during extreme years, whereas the local SSTs (0°–25°N, 115°–130°E) account for streamflow variability during normal years. Given that the EPF, local, and tropical SST conditions are spatially correlated, principal components regression (PCR) is employed to downscale the GCM-predicted precipitation fields and SST anomalies to monthly streamflow forecasts and to update them every month within the season using the updated EPF and SST conditions. These updated forecasts improve the prediction of monthly streamflows within the season in comparison to the skill of the monthly streamflow forecasts issued at the beginning of the season. It is also shown that the streamflow forecasting model developed using EPF under persisted SST conditions performs well upon employing EPF obtained under predicted SSTs as predictor. This has potential implications in the development of operational streamflow forecasts and statistical downscaling, which requires adequate years of retrospective GCM forecasts for recalibration. Finally, the study also shows that predicting the seasonal streamflow using the monthly precipitation forecasts reproduces the observed seasonal total better than the conventional approach of using seasonal precipitation forecasts to predict the seasonal streamflow.

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Legg, T. P. „Determining the accuracy of gridded climate data and how this varies with observing-network density“. Advances in Science and Research 6, Nr. 1 (22.07.2011): 195–98. http://dx.doi.org/10.5194/asr-6-195-2011.

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Abstract. The Met Office National Climate Information Centre regularly produces assessments of mean monthly, seasonal and annual values of weather parameters and their anomalies over the UK. However the gridded values, and corresponding areal-average values, are subject to error. Experiments have been done in an attempt to quantify the mean errors in gridded monthly values and monthly areal averages of temperature and rainfall, and how these errors vary when we artificially thin out the observation network. But there are two additional reasons for this work: firstly we wish to determine how far back we can realistically extend the historical areal series, and secondly, we want to estimate the size of error bars on the historical values. For the UK as a whole, we estimate that error bars of around 0.1 °C would arise for monthly-mean temperatures.

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G. Nascimento, Jéssica, Daniel Althoff, Helizani C. Bazame, Christopher M. U. Neale, Sergio N. Duarte, Anderson L. Ruhoff und Ivo Z. Gonçalves. „Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil“. Remote Sensing 13, Nr. 5 (28.02.2021): 906. http://dx.doi.org/10.3390/rs13050906.

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The lack of measurement of precipitation in large areas using fine-resolution data is a limitation in water management, particularly in developing countries. However, Version 6 of the Integrated Multi-satellitE Retrievals for GPM (IMERG) has provided a new source of precipitation information with high spatial and temporal resolution. In this study, the performance of the GPM products (Final run) in the state of Paraná, located in the southern region of Brazil, from June 2000 to December 2018 was evaluated. The daily and monthly products of IMERG were compared to the gauge data spatially distributed across the study area. Quantitative and qualitative metrics were used to analyze the performance of IMERG products to detect precipitation events and anomalies. In general, the products performed positively in the estimation of monthly rainfall events, both in volume and spatial distribution, and demonstrated limited performance for daily events and anomalies, mainly in mountainous regions (coast and southwest). This may be related to the orographic rainfall in these regions, associating the intensity of the rain, and the topography. IMERG products can be considered as a source of precipitation data, especially on a monthly scale. Product calibrations are suggested for use on a daily scale and for time-series analysis.

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Belenguer-Plomer, M. A. „Análisis de series temporales de precipitación y vegetación para la detección de anomalías en la producción de alimentos en el Cuerno de África. El caso de Lower Shabelle (Somalia)“. Revista de Teledetección, Nr. 47 (27.12.2016): 41. http://dx.doi.org/10.4995/raet.2016.6690.

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<p align="justify">The Horn of Africa is one of the most food-insecure locations around the world due to the continuous increase of its population and the practice of the subsistence agriculture. This causes that much of the population cannot take the minimum nutritional needs for a healthy life. Moreover, this situation of food vulnerability may be seriously affected in the coming years due to the effects of climate change. The aim of this work is combine the information about the state of the vegetation that offers the NDVI with rainfall data to detect negative anomalies in food production. This work has been used the monthly products of NDVI MOD13A3 of MODIS and the rainfall estimation product TAMSAT, both during the period 2001-2015. With these products we have calculated the average of the entire time period selected and we have detected the years whose NDVI values were further away from the average, being these 2010, 2011 and 2014. Once detected the years with major anomalies in NDVI, there has been an exclusive monthly analysis of those years, where we have analysed the relationships between the value of NDVI and monthly rainfall, obtaining a direct relationship between the two values. It also has been used crop calendar to focus the analysis in the months of agricultural production and finding that the main cause of anomalies in vegetation is a decrease in the registration of rainfall during the months of agricultural production. This reason explains the origin of the food shortages that occurred in 2010 and 2011 that generated an enormous humanitarian crisis in this area.</p>

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Yasui, Soichiro, und Masahiro Watanabe. „Forcing Processes of the Summertime Circumglobal Teleconnection Pattern in a Dry AGCM“. Journal of Climate 23, Nr. 8 (15.04.2010): 2093–114. http://dx.doi.org/10.1175/2009jcli3323.1.

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Abstract To better understand the predictability of the wavelike circumglobal teleconnection (CGT) pattern prevailing during boreal summer, two sets of experiments are performed using a nonlinear dry atmospheric model. Each experiment consists of a 10-member ensemble of 26-yr integrations driven by the diabatic heating derived from reanalysis data: one with the monthly climatological mean heating (CLIM) and the other with the monthly heating for 1979–2004 (HIST). Both do well in reproducing the observed summer mean state, as well as the low-frequency variance distribution. The CGT pattern identified in the monthly meridional wind anomalies at 200 hPa shows zonally oriented wave packets over Eurasia. The simulated CGT has a nearly identical phase structure with the observations and indicates little difference between the CLIM and HIST results. While this indicates that the origin of CGT lies in the internal dry dynamics, the ensemble mean of the CGT in HIST is partly controlled by the slow variation in the heating field, as indicated by the high potential predictability of the simulated CGT pattern. Diagnoses using the linearized model demonstrate that the heating anomaly most responsible for the CGT-like steady response is located over the eastern Mediterranean region, where the heating may be coupled with the CGT pattern. In addition to the heating near the CGT, remote heating and cooling anomalies over North America and equatorial Africa are found to be effective at exciting stationary Rossby waves trapped on the Atlantic and Asian jets. It is thus suggested that the mechanisms generating the heating anomalies over these regions are the key to the predictability of the CGT pattern.

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Taylor, Patrick C. „Variability of Regional TOA Flux Diurnal Cycle Composites at the Monthly Time Scale“. Journal of the Atmospheric Sciences 71, Nr. 9 (28.08.2014): 3484–98. http://dx.doi.org/10.1175/jas-d-13-0336.1.

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Abstract Diurnal variability is a fundamental component of Earth’s climate system. Clouds, temperature, and precipitation exhibit robust responses to the daily cycle of solar insolation. Recent work indicates significant variability in the top-of-the-atmosphere (TOA) flux diurnal cycle in the tropics associated with monthly changes in the cloud diurnal cycle evolution. It has been proposed that the observed month-to-month variations in the TOA flux diurnal cycle are caused by anomalies in the atmospheric dynamic and thermodynamic state. This hypothesis is tested using a regression analysis to quantify the relationship between diurnal cycle shape and the atmospheric dynamic and thermodynamic state. TOA radiative fluxes are obtained from Clouds and the Earth’s Radiant Energy System (CERES) Edition 3 data and the atmospheric dynamic and thermodynamic state is taken from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis. Four regions representing traditional diurnal cycle regimes are used in this analysis: North Africa (land nonconvective), central South America (land convective), Peru marine stratocumulus (ocean nonconvective), and Indian Ocean (ocean convective). The results show a statistically significant diurnal cycle shape change and cloud response related to monthly atmospheric state anomalies. Using the single-variable regression relationships to predict monthly diurnal cycle variability shows improvements of 1%–18% over assuming a climatological diurnal cycle shape; the most significant gains are found in North Africa. The proposed hypothesis, therefore, contributes to diurnal cycle variability explaining at least 10%–20% of the total monthly-mean diurnal cycle variability.

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