Long memory, seasonality and time trends in the average monthly temperatures in Alaska

This paper deals with the analysis of monthly temperatures in 19 meteorological stations in Alaska during the last 50?years. For this purpose, we employ a procedure that permits us to examine in a single framework several features observed in climatological time series such as time trends, long-range persistence and seasonality. The results indicate that the highest degrees of persistence are observed in stations located in the southern regions and seasonality appears as a major issue in all cases. Removing the seasonal structure and focussing on the anomalies with respect to the monthly means, the time trend coefficients appear significantly positive in the majority of the cases, implying that temperatures have increased during the last 50?years.     

A note on the intercornparison between monthly mean radiance equivalent and rocketsonde temperatures

Summary Rocketsonde monthly mean temperature structure of the stratosphere is compared with that derived from Nimbus-5 SCR radiance measurements for the solsticial months in 1973 and for the equinoctial months in 1974. The comparison shows good agreement only at pressure levels between about 5 mb and 15 mb (upper-middle stratosphere). The satellite minus rocket bias is highest at the stratopause region possibly due to the constraints applied in retrieving the radiance equivalent temperatures.

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Über einen Vergleich zwischen Monatsmittelwerten von strahlungsäquivalenten Temperaturen und Temperaturen von Raketensonden

Zusammenfassung Die mit Raketensonden gewonnene mittlere monatliche Temperaturstruktur der Stratosphäre wird mit der aus Strahlungsmessungen von Nimbus-5 SCR abgeleiteten für die Monate Juni und Dezember 1973 und für März und September 1974 verglichen. Der Vergleich zeigt eine gute Übereinstimmung nur in den Druckniveaus zwischen 5 mb und 15 mb, das ist in der oberen mittleren Stratosphäre. Die Differenz zwischen den mit Satelliten und den mit Raketensonden gewonnenen Temperaturen ist am größten in der Stratopausenregion, möglicherweise zufolge der zur Ableitung der strahlungsäquivalenten Temperaturen angewendeten Methode.

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With 2 Figures     

Differences between true mean daily, monthly and annual air temperatures and air temperatures calculated with three equations: a case study from three Croatian stations

Differences between true mean daily, monthly and annual air temperatures T0 [Eq. (1)] and temperatures calculated with three different equations [(2), (3) and (4)] (commonly used in climatological practice) were investigated at three main meteorological Croatian stations from 1 January 1999 to 31 December 2011. The stations are situated in the following three climatically distinct areas: (1) Zagreb-Gri? (mild continental climate), (2) Zavi?an (cold mountain climate), and (3) Dubrovnik (hot Mediterranean climate). T1 [Eq. (2)] and T3 [Eq. (4)] mean temperatures are defined by the algorithms based on the weighted means of temperatures measured at irregularly spaced, yet fixed hours. T2 [Eq. (3)] is the mean temperature defined as the average of daily maximum and minimum temperature. The equation as well as the time of observations used introduces a bias into mean temperatures. The largest differences occur for mean daily temperatures. The calculated daily difference value from all three equations and all analysed stations varies from ?3.73 °C to +3.56 °C, from ?1.39 °C to +0.79 °C for monthly differences and from ?0.76 °C to +0.30 °C for annual differences.     

Record occurrence and record values in daily and monthly temperatures

We analyze the occurrence and the values of record-breaking temperatures in daily and monthly temperature observations. Our aim is to better understand and quantify the statistics of temperature records in the context of global warming. Similar to earlier work we employ a simple mathematical model of independent and identically distributed random variables with a linearly growing expectation value. This model proved to be useful in predicting the increase (decrease) in upper (lower) temperature records in a warming climate. Using both station and re-analysis data from Europe and the United States we further investigate the statistics of temperature records and the validity of this model. The most important new contribution in this article is an analysis of the statistics of record values for our simple model and European reanalysis data. We estimate how much the mean values and the distributions of record temperatures are affected by the large scale warming trend. In this context we consider both the values of records that occur at a certain time and the values of records that have a certain record number in the series of record events. We compare the observational data both to simple analytical computations and numerical simulations. We find that it is more difficult to describe the values of record breaking temperatures within the framework of our linear drift model. Observations from the summer months fit well into the model with Gaussian random variables under the observed linear warming, in the sense that record breaking temperatures are more extreme in the summer. In winter however a significant asymmetry of the daily temperature distribution hides the effect of the slow warming trends. Therefore very extreme cold records are still possible in winter. This effect is even more pronounced if one considers only data from subpolar regions.     

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.     

Long-term changes and variability of monthly extreme temperatures in India

Extreme temperatures are changing worldwide together with changes in the mean temperatures. This study investigates the long-term trends and variations of the monthly maximum and minimum temperatures and their effects on seasonal fluctuations in various climatological regions in India. The magnitude of the trends and their statistical significance were determined by parametric ordinary least square regression techniques and the variations were determined by the respective coefficient of variations. The results showed that the monthly maximum temperature increased, though unevenly, over the last century. Minimum temperature changes were more variable than maximum temperature changes, both temporally and spatially, with results of lesser significance. The results of this study are good indicators of Indian climate variability and its changes over the last century.     

On the reconstruction of temperature records from proxy data in mid Europe

Summary The problem of the reconstruction of mean summer temperatures from proxy data on a rigorous statistical basis is addressed: Cross spectral analysis is used for evaluating the suitability of linear transfer models between proxy data and temperature, the linear model is estimated from the data of a calibration period and it is verified using the data of a different period. Strict statistical tests are applied at every step of the analysis. Three examples using the proposed method are given: the reconstruction of mean April–July temperatures at Basel from grape harvest data in NE France (1484–1768), mean April–September temperatures at Basel from late wood density of trees from the Swiss Prealps (1270‐1768), and mean April–September temperatures at Great St. Bernhard from the late wood proxy too (1270–1850). The grape harvest data give a very good reconstruction, the resulting temperatures from 1500–1768 are documented. The late wood data fails to give a good reconstruction.

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Die Rekonstruktion von Temperaturreihen aus Proxydaten in Mitteleuropa

Zusammenfassung Es wird das Problem der Rekonstruktion von mittleren Sommertemperaturen aus sogenannten Proxydaten untersucht. Sehr viel Wert wird auf die statistische Signifikanz der Rekonstruktion gelegt. Kreuzspektralanalyse wird benutzt, um die Verwendungsf?higkeit eines linearen Modells als Transfermodell zwischen Temperatur und Proxydaten zu ermitteln. Die Parameter des linearen Transfermodells werden aus den Daten der sogenannten Eichperiode abgesch?tzt und die damit für eine unabh?ngige Periode rekonstruierten Temperaturen werden mit gemessenen verglichen. In jedem Schritt der Analyse werden strikte statistische Tests durchgeführt, um die Ergebnisse zu untermauern. Die Methode wird an drei Beispielen erprobt: die mittlere April–Juli Temperatur in Basel wird mit Hilfe von Weinlesedaten von NE-Frankreich für die Zeit (1484–1768) rekonstruiert, die mittlere April–September Temperatur in Basel und am Gro?en Bernhard wird mit Sp?tholzdichtewerten der Schweizer Voralpen verglichen. Die Weinlesedaten ergeben eine sehr gute Rekonstruktion und die Temperaturreihe für den Zeitraum 1500–1768 wird dokumentiert. Die Sp?tholzdichten liefern keine gute Temperaturrrekonstruktion.

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With 11 Figures     

Study of the mean monthly air temperatures during the successive sunspot cycles

In the first part of this paper (I–III) the mean monthly air temperatures during successive sunspot cycles are examined for six stations of Central and Northwestern Europe. Based upon the observed data the variations between two consecutive 11-year periods of solar activity are studied for the following elements:

1. a)
   The differenceT _h?T_c between the mean temperatures of the four warmer (May–August) and the four colder (November–February) months of the year.     
   
   

Some aspects of the relation between monthly temperatures and rainfall,and its use in evaluating earlier climates in the Middle East

The quantitative relation between mean monthly temperatures and rainfall has been investigated for a hundred years period at Jerusalem. It was found that a decrease of 1°C in the mean monthly temperature is associated with an average increase of 13 mm in monthly precipitation, on the seasonal scale. The findings are consonant with previous results pointing to an increase of about 100 mm in annual rainfall for a decrease of 1°C in the seasonal temperature. Such coefficients may, to a first approximation and with some qualifications, be used in estimating rainfall in earlier periods in the Middle East, and to evaluate hydrological effects and potential risks in future centuries.     

北太平洋700毫巴月平均环流形势与海温的相互关系

北太平洋700 mb环流形势具有相当鲜明的季节性与地域性特征.北太平洋的海、气相互作用是这些特征以及东亚季风形成的一个原因.从海、气相互作用的角度出发,对比分析北太平洋700 mb环流形势和海表温度距平的分布,可以看出:有些情况下,大气对海洋的影响比较明显;在另一些情况下,海洋对700 mb环流形势的影响较为明显.它们之间的矛盾与矛盾的主要方面是不断地、经常地在转化以及相互影响着.它们的转化、演变对我国副热带高压及旱涝天气的变化有一定的关系。     

Mathematical modelling of the annual temperature wave based on monthly mean temperatures,and comparisons between local climate trends at seven Norwegian stations

Summary Based on observed monthly mean temperatures, it is possible to construct a simple mathematical model of the annual variation of daily mean temperature, the annual temperature wave. For periods of 15 years, the model gives a good correlation with the observed monthly values. The model may be used as a tool for the generation of daily mean temperatures for the corresponding period. It is continuous, differentiable and strictly monotonous between the unique maximum and the minimum of the curve. Consequently, climate quantities of interest for each period can be calculated by the means of simple mathematical analyses. The model was tested by reproducing values for quantities such as annual mean temperature, winter mean temperature, summer mean temperature and temperature sums. Model calculated values, fit values calculated directly from observed data well. The model was also tested by comparing results from two different but neighbouring stations. There was a good correlation between the results from the two stations. Long homogenised time series with 130 years of monthly mean temperature from seven Norwegian stations were analysed by means of the model. It was found that the Frost Free Season Length and the Growth Season Length had increased for all stations by 10–20 days/100 years in the period 1871–1990. The Summer Half-year Length, even if it was defined relative to the annual mean temperature, also increased for all stations by 4–9 days/100 years. The Hot Season Length showed positive trends as well, and for the five stations in Southern Norway, the trends were as high as 18–29 days/100 years. The Heat Sum had increased by 6–11% for southern stations and 20–22% for the northern stations. The results indicate that the level as well as the shape of the annual temperature wave changed in the period from 1871 to 1990. Some of the results for the period 1990–1999 diverge substantially from the trends, possibly indicating significant changes in the shape of the annual temperature wave in this last period.     

On the prediction of soil temperatures from meteorological data during the winter period

The seasonal freezing and thawing of soils in the absence or in the presence of a snow cover is considered. The method may also be used in such calculations for the summer period. An example is given.     

Estimation methods for monthly humidity from dynamical downscaling data for quantitative assessments of climate change impacts

Methods are proposed to estimate the monthly relative humidity and wet bulb temperature based on observations from a dynamical downscaling coupled general circulation model with a regional climate model (RCM) for a quantitative assessment of climate change impacts. The water vapor pressure estimation model developed was a regression model with a monthly saturated water vapor pressure that used minimum air temperature as a variable. The monthly minimum air temperature correction model for RCM bias was developed by stepwise multiple regression analysis using the difference in monthly minimum air temperatures between observations and RCM output as a dependent variable and geographic factors as independent variables. The wet bulb temperature was estimated using the estimated water vapor pressure, air temperature, and atmospheric pressure at ground level both corrected for RCM bias. Root mean square errors of the data decreased considerably in August.     

相关比和线性相关系数的对比分析

本文对相关比和线性相关系数进行了理论比较,并用实际资料对两者的相关评价特点进行了计算对比,分析结果表明相关比确实是一种优于线性相关系数的相关度量:1)它不对相关形式作任何要求,用它来反映相关比线性相关系数更为全面;2)在相关比计算的过程中,我们可以同时得到相关程度和相关形式两项信息。另外,我们还就相关比计算中的问题作了讨论,指出了应该注意的问题。     

南方涛动与我国大尺度季、月气温的关系

南方涛动与我国月平均气温的相关,在当年2月、4月、9月以正相关为主,9月以后出现持续的负相关。南方涛动与我国季平均气温相关最显著的季节是当年秋季,其次是次年春季。南方涛动与次年长江下游、广东、福建、山东的年平均气温有良好的负相关。这些关系均可在预报中利用。此外,还指出,在我国4、5月,9、10月的大范围气温记录中存在早期识别厄尔尼诺的信号。     

Investigating the relationship between growing season quality and childbearing goals

Agricultural production and household food security are hypothesized to play a critical role connecting climate change to downstream effects on women’s health, especially in communities dependent on rainfed agriculture. Seasonal variability in agriculture strains food and income resources and makes it a challenging time for households to manage a pregnancy or afford a new child. Yet, there are few direct assessments of the role locally varying agricultural quality plays on women’s health, especially reproductive health. In this paper we build on and integrate ideas from past studies focused on climate change and growing season quality in low-income countries with those on reproductive health to examine how variation in local seasonal agricultural quality relates to childbearing goals and family planning use in three countries in sub-Saharan Africa: Burkina Faso, Kenya, and Uganda. We use rich, spatially referenced data from the Performance Monitoring for Action (PMA) individual surveys with detailed information on childbearing preferences and family planning decisions. Building on recent advances in remote monitoring of seasonal agriculture, we construct multiple vegetation measures capturing different dimensions of growing season conditions across varying time frames. Results for the Kenya sample indicate that if the recent growing season is better a woman is more likely to want a child in the future. In Uganda, when the growing season conditions are better, women prefer to shorten the time until their next birth and are also more likely to discontinue using family planning. Additional analyses reveal the importance of education and birth spacing in moderating these findings. Overall, our findings suggest that, in some settings, women strategically respond to growing season conditions by adjusting fertility aspirations or family planning use. This study also highlights the importance of operationalizing agriculture in nuanced ways that align with women’s lives to better understand how women are impacted by and respond to seasonal climate conditions.     

Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data,satellite estimates,and merged analyses over China

Theoretical and Applied Climatology - In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2...