Aircraft observations of wind and temperature are very important for upper air meteorology. In this article, the quality of the meteorological information of an Automatic Dependent Surveillance-Contract (ADS-C) message is assessed. The ADS-C messages broadcast by the aircraft are received at air traffic control centres for surveillance and airline control centres for general aircraft and dispatch management. A comparison is performed against a global numerical prediction (NWP) model and wind and temperature observations derived from Enhanced Surveillance (EHS) air-traffic control radar which interrogates all aircraft in selective mode (Mode-S EHS). Almost 16 000 ADS-C reports with meteorological information were compiled from the Royal Dutch Airlines (KLM) database. The length of the data set is 76 consecutive days and started on 1 January 2011. The wind and temperature observations are of good quality when compared to the global NWP forecast fields from the European Centre for Medium-Range Weather Forecasts (ECMWF). Comparison of ADS-C wind and temperature observations against Mode-S EHS derived observations in the vicinity of Amsterdam Airport Schiphol shows that the wind observations are of similar quality and the temperature observations of ADS-C are of better quality than those from Mode-S EHS. However, the current ADS-C data set has a lower vertical resolution than Mode-S EHS. High vertical resolution can be achieved by requesting more ADS-C when aircraft are ascending or descending, but could result in increased data communication costs.
NB: Third author is my son – not me (GPK)
The distribution of outliers is used as a tool for finding the extreme value distribution of meteorological parameters and to provide return values for large return periods from short records. Its potential is demonstrated for 5 cases. For extreme winds in the Northern Hemisphere (NH) the method shows that appropriately transformed annual maximum wind speeds can be described by a Gumbel distribution; for extreme waves it rejects the proposed adoption of an exponential distribution and points to a Gumbel distribution; for extreme daily European precipitation R it confirms the theoretically predicted value k = 2/3 in its Weibull distribution and it also justifies the application of the Gumbel distribution to R2/3 up to return periods of about 50 000 years; for seasonal precipitation in the Netherlands it highlights enhanced extreme precipitation in the coastal area in December-January-February (DJF) and failure of the k = 2/3 hypothesis outside June-July-August (JJA); for sea levels in the Southern North Sea it points to the Gumbel distribution and provides improved estimates for the 104-return value of the sea level at coastal stations, which is elaborated for the Dutch tidal station Scheveningen.
The anomalous red twilights observed in mid-February 2008 over Western Europe can be attributed to the presence of a large field of Stratospheric Polar Clouds (PSCs). The vertical sounding of De Bilt indicates that a tropospheric high pressure system triggered an excess stratospheric cooling. Pictures of the twilight taken from several spots are shown.
The temperature and pressure differences between Tokyo and Nagasaki were used to reconstruct past climate conditions. January and July in each available year since the 1820s were classified into several types with characteristic sea level atmospheric pressure patterns. This results in 18 years of pre-1881 data and a continuous series thereafter. The series indicate that the warming after 1900 (after the end of the so-called Little Ice Age) and again after 1960 can at least partly be attributed to an increase in the frequency of warm circulation pattern types at the expense of cold types. The difference in nature of the shifts in circulation types that occurred in the late 19th century compared with that in the late 20th centuries suggests that the mechanism behind the warming in the late 19th century differs from that in the late 20th century.
A general expression for the statistical distribution of the probability of the highest event occurring in a record is presented. This result can be empirically applied to situations where records are available for multiple geographical locations. The empirical estimation of the probability of the highest events provides a means to assess whether the assumed (extreme value) distribution is appropriate for extrapolation or not. The approach allows for combining the highest events from different records and to validate estimated return periods in the order of the length of the combined records. The method is illustrated with an analysis of the annual extreme wind speeds over the North Atlantic area according to the ERA40 dataset, showing that the Gumbel distribution is in favor of the GEV distribution to describe the (appropriately transformed) extreme wind speeds up to return periods of 104 years.
An outline is given about the international data abstraction project ship's logbooks and its application in the reconstruction of wind fields, circulation patters and of the North Atlantic Oscillation and the El Niño-Southern Oscillation index for the 1750-1854 period.
We have recovered instrumental temperature and pressure observations from Tokyo covering the periods 1825-1828, 1839-1855, and 1872-1875, from Yokohama covering the periods 1860-1871 and 1874, from Osaka covering the periods 1828-1833 and 1869-1871, and from Kobe covering the periods 1869-1871 and 1875-1888. The newly recovered records contain data before the 1870s, which is a period where until recently no instrumental data in Japan were believed to exist. Their addition to the previous backward extension of Japanese series, as based on the recently recovered intermittent Dejima/Nagasaki series 1819-1878, implies that the 19th century extension of the Japanese instrumental record no longer contains major temporal gaps. The recovered data were used for a preliminary calculation of the West-Japan Temperature (WJT) series, which is a representative temperature series for the area. The existence of a warm epoch in the 1850s over W-Japan and a downward temperature trend till the early 20th century, as previously inferred from documentary data, is confirmed from the WJT data. The pressure data implies that the temperature difference between the 19th and 20th century are at least partly caused by a change in atmospheric circulation.
Nearest-neighbor resampling is introduced as a means for homogenizing temperature records on a daily to sub-daily level. Homogenization refers here to the problem of calculating daily mean and sub-daily temperatures from a time series subject to irregular observation frequencies and changing observation schedules. The method resamples diurnal temperature cycles from an observed hourly temperature subrecord at the station. Unlike other methods, the technique maintains the variance in a natural way. This property is especially important for the analysis of trends and variability of extremes. For a given day, the resampling technique does not generate a single-valued solution but this peculiarity is of no effect in the applications considered here. The skills of the nearest-neighbor resampling technique, in terms of bias, RMSE, and variability, are compared with those of four other methods: a sine-exponential model, a model that uses the climatological mean daily cycle, a regression model for calculating daily values, and a deterministic version of the nearest-neighbor technique. The series used in the tests is the 1951-2000 meteorological record of De Bilt (The Netherlands). The emphasis in the comparisons is on the reconstruction of daily mean temperatures. The analysis shows important differences in performance between the models. The regression-based method performs best with respect to the calculation of the individual daily mean temperatures; the day-to-day variability is best reproduced with the nearest-neighbor resampling technique. The performance of the models improves when cloudiness is used as an extra predictor. The improvement is, however, small compared to the intermodel differences. The type of model that should be used depends on the desired application. For trend and variability studies, the nearest-neighbor resampling technique performs best. Nearest-neighbor resampling can successfully be performed even in situations where the length of the hourly subrecord is an order of magnitude less than the length of the series to be homogenized.
An overview is given about the history, methodology and results of the EU Cliwoc project 2000-2003 that aimed to a meteorological database over the world's oceans based on regular observations from ships of the great maritime countries in the period 1750-1854.
We have compiled a meteorological database over the world's oceans by digitizing data from European ship logbooks of voyages in the period 1750-1854. The observations are carefully reviewed and transformed into quantitative data. The chief contents of the database are wind direction and wind force information, from a period without standardized scales. It is found that the information content of these so-called non-instrumental data is much higher than previously believed. The 105-yr CLIWOC database extends existing meteorological world ocean databases like ICOADS back in time by a full century.
The Dutch wind force terms in the CLIWOC period (1750-1854) consist for 59% of descriptors and for 41% of regular Beaufort numbers. In total, over 1,600 different descriptors are encountered. An attempt is made to transform the descriptors in wind speed via the Beaufort scale of wind force. Nearly two third of the descriptors refer to the use of sails. Despite of the huge amount of descriptors, it was possible to condense 99% of the wind force reports into the 13-point Beaufort scale. Quality checks against ICOADS indicate that the quality of the post-1800 Dutch CLIWOC wind data surpasses that of the pre-1800 Dutch data, while for the pre-1800 data the quality seems comparable with that from the other countries. Weather terms other than wind are denoted in 15% of the reports by special symbols, of which the meaning was lost. A key to these symbols is reconstructed.
Signals of anthropogenic warming over Europe are searched for in the spatial trend patterns for the variance and skewness (expressed by the 10th and 90th percentiles) of the distribution of daily mean temperature. Comparisons are made between these patterns in the station records of the European Climate Assessment dataset for the 1976-99 period, the patterns associated with natural variability in the observations (which were empirically derived from the observations in the 1946-75 period), and the patterns of future warming and natural variability as simulated by the National Center for Atmospheric Research Community Climate System Model in the Challenge ensemble experiment.
The results indicate that, on the basis of the patterns for the variance, a distinction can be made between temperature change due to natural variability and temperature change due to changes in external forcing. The observed variance trend patterns for the spring (March-May) and summer (June-August) warming 1976-99 are clearly different from the patterns for the change in variance associated with a warming due to natural variability in the observations. This led us to conclude that a change in an external forcing has to be invoked to explain the observed spring and summer warming. From the evaluation of the greenhouse and natural variability patterns in the climate model simulations, we infer that the observed spring and summer variance trend patterns contain imprints consistent with anthropogenic warming. The analysis of the variance trend patterns for the winter (December-February) season is inconclusive about identifying causes of the observed warming for that season. Unlike the other three seasons, the autumn (September-November) is for Europe a period of cooling in recent decades. The observed variance trend pattern for this season closely resembles the estimated pattern for the change in variance associated with a cooling due to natural variability, indicating that the observed autumn cooling can be ascribed to random weather variations in the period under consideration.
We present a series of daily pressure readings taken 1697-1698 in Leiden (Netherlands) by W. Senguerd. The readings were reviewed, converted to modern units, and reduced to 0°C. The 2-yr series runs parallel with the Paris 1665-1713 and London 1697-1708 pressure series. Although the series covers a time span of 23 months only, it can be regarded as a useful addition to the very few pressure series that extend back into the 17th century.
Trends in the annual number of independent wind events over the Netherlands are studied for the period 1962-2002. The events are selected out of 13 hourly 10 m wind speed records that are part of a high quality dataset of near-surface wind observations at Dutch meteorological stations. Comparisons are made with trends in independent wind events selected from geostrophic wind speed records and reanalysis data.
The results for moderate wind events (that occur on average 10 times per year) and strong wind events (that occur on average twice a year) indicate a decrease in storminess over the Netherlands between 5 and 10%/decade. This result is inconsistent with National Centers for Environmental Prediction-National Center for Atmospheric Research or European Centre for Medium-Range Weather Forecasts reanalysis data, which suggest increased storminess during the same 41 year period.
Possible explanations are given for the discrepancy between the trends in storminess based on station data and the trends in storminess based on reanalysis data. Evaluation of trends in geostrophic wind, both from station data and reanalysis data, and evaluation of trends in vector-averaged (upscaled) 10 m wind over the Netherlands point towards inhomogeneities in the reanalysis data as the main cause of the discrepancy. We conclude that it is likely that the decrease in storminess observed in Dutch station records of near-surface wind in the past four decades is closer to reality than the increase suggested by the reanalysis data.
We developed a user-friendly database with the 1750-1854 CLIWOC data, which is suitable to be integrated with the ICOADS database. The meteorological content focuses on wind direction and wind speed. The data, stored in the IMMA format, are accessible in numerical and in their original descriptive forms. Apart from alphanumerical meteorological information, the database contains a considerable number of images of logbook pages, and nautical information relevant to historians. The construction of the database involved a number of difficulties, including language, unit conversion, terminology and zero meridian problems. We believe that this publicly accessible database can give an important contribution to the understanding of low-frequency climate variability, as it extends the current climatological ocean databases by more than a century and probes deep into the pre-industrial era.
Meteorological extremes have large impacts on society. The fact that approximately 40% of the Netherlands is below sea level makes this country especially vulnerable to flooding, both from the sea and from rivers. This has resulted in extensive research on the statistics of extremes. However, applications to meteorological and hydrological situations are always hampered by the brevity of the available datasets, as the required return levels exceed the record lengths by a factor of 10 to 100. In order to overcome this problem, we use archived data from all past seasonal forecast ensemble runs of the European Centre for Medium-Range Weather Forecasts (ECMWF) since 1987 as input for extreme-value statistics analysis. We make use of the fact that the seasonal forecast has little seasonal skill for the Netherlands, which implies that the ensembles can be regarded as independent sets that cumulate to over 1500 years.
We investigate the hydraulic response in the Netherlands to extreme synoptic-scale weather systems by studying the extreme-value distributions of sea storm surge levels, waves and river discharges. The application is detailed in four practical examples originating from coastal protection, river flooding protection, and water management problems. The long record length of the ECMWF data reduces the uncertainty in the 103-year and the 104-year return values considerably with respect to the results based on observational time series. The ECMWF dataset gives the opportunity to explore the distribution of events that depend on several kinds of extreme.
Ensemble simulations with a total length of 7540 years are generated with a climate model, and coupled to a simple surge model to transform the wind field over the North Sea to the skew surge level at Delfzijl, The Netherlands. The 65 constructed surge records, each with a record length of 116 years, are analysed with the generalized extreme value (GEV) and the generalized Pareto distribution (GPD) to study both the model and sample uncertainty in surge level estimates with a return period of 104 years, as derived from 116-year records. The optimal choice of the threshold, needed for an unbiased GPD estimate from peak over threshold (POT) values, cannot be determined objectively from a 100-year dataset. This fact, in combination with the sensitivity of the GPD estimate to the threshold, and its tendency towards too low estimates, leaves the application of the GEV distribution to storm-season maxima as the best approach. If the GPD analysis is applied, then the exceedance rate, l, chosen should not be larger than 4. The climate model hints at the existence of a second population of very intense storms. As the existence of such a second population can never be excluded from a 100-year record, the estimated 104-year wind-speed from such records has always to be interpreted as a lower limit.
Meteorological applications of extreme value statistics are often limited by the relative shortness of the available datasets. In order to overcome this problem, we use archived data from all past seasonal forecast ensemble runs of the European Centre for Medium-Range Weather Forecasts (ECMWF) for estimating low frequency return values. For regions where the forecasts have very little seasonal skill the archived seasonal forecast ensembles provide independent sets that cumulate to over 1500 years. We illustrate this approach by estimating 104-year sea-surge levels at high-tide along the Dutch coast. In comparison with the observational sets, the ECMWF set shows a decrease in the statistical uncertainty of the estimated 104-year return value by a factor four
Statistical analysis of the wind speeds, generated by a climate model of intermediate complexity, indicates the existence of areas where the extreme value distribution of extratropical winds is double populated, the second population becoming dominant for return periods of order 103 yr. Meteorological analysis of the second population shows that it is caused when extratropical cyclones merge in an extremely strong westerly jet stream such that conditions are generated that are favorable for occurrence of strong diabatic feedbacks. Doubling of the greenhouse gas concentrations changes the areas of second population and increases its frequency. If these model results apply to the real world, then in the exit areas of the jet stream the extreme wind speed with centennial-to-millennial return periods is considerably larger than extreme value analysis of observational records implies.
There is an ancient myth that the light in Holland is different from anywhere else. It's the legendary light we see in old Dutch paintings. The reality of this elusive effect is discussed by several people. My explanation is that the light is just a contrast effect, cause by the flat and featureless Dutch landscape which attracts the eyes to the near-horizon sky, where remote cumulus clouds can a spectacular sight. (versions in English, Dutch, German, French, and Spanish)
NB: This documentary won in 2003 a ‘Gouden Kalf' award
The official Final Report of the CLIWOC project (CLImatological database for the World's OCeans 1750-1854) to the European Union (EU). Scientific output of CLIWOC can be found in the various papers that appeared in the Special Issue on CLIWOC of Climatic Change, in 2005.
Daily European station series (1901-99) of surface air temperature and precipitation from the European Climate Assessment dataset are statistically tested with respect to homogeneity. A two-step approach is followed. First, four homogeneity tests are applied to evaluate the daily series. The testing variables used are (1) the annual mean of the diurnal temperature range, (2) the annual mean of the absolute day-to-day differences of the diurnal temperature range and (3) the wet day count (threshold 1 mm). Second, the results of the different tests are condensed into three classes: ‘useful', ‘doubtful' and ‘suspect'. A qualitative interpretation of this classification is given, as well as recommendations for the use of these labelled series in trend analysis and variability analysis of weather extremes. In the period 1901-99, 94% of the temperature series and 25% of the precipitation series are labelled ‘doubtful' or ‘suspect'. In the sub-period 1946-99, 61% of the temperature series and 13% of the precipitation series are assigned to these classes. The seemingly favourable scores for precipitation can be attributed to the high standard deviation of the testing variable, and hence the inherent restricted possibilities for detecting inhomogeneities. About 65% of the statistically detected inhomogeneities in the temperature series labelled ‘doubtful' or ‘suspect' in the period 1946-99 can be attributed to observational changes that are documented in the metadata. For precipitation this percentage is 90%.
Instrumental observations from Dejima (Nagasaki), taken under the responsibility of the Dutch, covering the periods 1819-1828, 1845-1858 and 1871-1878 have been recovered. The Dejima series overlaps by six months with the modern Nagasaki Observatory series 1878-present. The recovered data extend the start of the instrumental Japanese series back from 1872 to 1819, leaving major gaps during 1829-1844 and 1859-1871.
The quality of the 5.7 million punched sea level pressure observations from Dutch ships 1854-1938 has been under debate due to ambiguities in the gravity correction. The observations were omitted from the 1985 COADS (Comprehensive Ocean-Atmosphere Data Set) Release 1 monthly summaries. We re-examined the Dutch data with the help of original meteorological ship logs. It is concluded that the Dutch procedure for pressure reduction was consistent throughout time. In the recent (2001) COADS Release 1c the Dutch data are incorporated. This increases the number of COADS pressure observations 1854-1938 by about 28%. For the 1854-1880 subperiod the increase is more than a factor two.
General Circulation Model-generated surges are analyzed with the Generalized Extreme Value distribution to study the uncertainty in surge level estimates with a return period of 104 years, derived from observational records of order hundred years.
Ensemble simulations with a total length of 5336 years were generated with the KNMI General Circulation Model ECBilt, coupled with a simple surge model to transform the wind field over the North Sea to the surge level at Delfzijl (NL). The 46 estimated surge levels with a return period of 104 years, calculated from sets of 116 year each, vary between 4.5 and 17 meters, with a median of 8.5 meter. The 104-year estimate of the 118-year observational Delfzijl record (5.8 meter) fits well among these subsets, but this surge level is considerably lower than the median of the ensemble estimate. For an estimate of the 104-year return level of the surge within an uncertainty of 10%, a record length of about 103 years is required.
CO2-doubling does not have a detectable influence on the mean wind speed over the North Sea in ECBilt. However, the model hints on the excitation of severe storms, with a frequency lower than once in 250 year. In ECBilt, these severe storms tend to dominate the 104-year return value of the wind speed over the North Sea.
Trends in indices of climate extremes are studied on the basis of daily series of temperature and precipitation observations from more than 100 meteorological stations in Europe. The period is 1946-1999, being a warming episode. Averaged over all stations, the indices of temperature extremes indicate ‘symmetric' warming of the cold and warm tails of the distributions of daily minimum and maximum temperature in this period. However, ‘asymmetry' is found for the trends if the period is split into two sub-periods. For the 1946-1975 sub-period, being an episode of slight cooling, the annual number of warm extremes decreases, but the annual number of cold extremes does not increase. This implies a reduction in temperature variability. For the 1976-1999 sub-period, being an episode of pronounced warming, the annual number of warm extremes increases two times faster than expected from the corresponding decrease in the number of cold extremes. This implies an increase in temperature variability, which is mainly due to stagnation in the warming of the cold extremes.
For precipitation, all Europe-average indices of wet extremes increase in the 1946-1999 period, although the spatial coherence of the trends is low. At stations where the annual amount increases, the index that represents the fraction of the annual amount due to very wet days gives a signal of disproportionate large changes in the extremes. At stations with decreasing annual amount, there is no such amplified response of the extremes.
The indices of temperature and precipitation extremes in this study were selected from the list of WMO-CCL/CLIVAR-recommended climate change indices. The selected indices are expressions of events with return period 5-60 days. This means that the annual number of events is sufficiently large to allow for meaningful trend analysis in ~50 year time series. Although the selected indices refer to events that may be called ‘soft' climate extremes, these indices have clear impact relevance.
The influence of urban heat advection on the temperature time series of the Dutch GCOS station De Bilt has been studied empirically by comparing the hourly meteorological observations (1993-2000) with those of the nearby (7.5 km) rural station at Soesterberg. Station De Bilt is in the transition zone (TZ) between the urban and rural area, being surrounded by three towns, Utrecht, De Bilt and Zeist. The dependence of the hourly temperature differences between De Bilt and Soesterberg on wind direction has been examined as a function of season, day- and night-time hours and cloud amount. Strong dependence on wind direction was apparent for clear nights, with the greatest effects (up to 1 °C on average) for wind coming from the towns. The magnitude of the effect decreased with increasing cloudiness. The analysis suggests that most of the structure in the wind direction dependence is caused by urban heat advection to the measuring site in De Bilt. The urban heat advection is studied in more detail with an additive statistical model. Because the urban areas around the site expanded in the past century, urban heat advection trends contaminate the long-term trends in the temperature series (1897-present) of De Bilt. Based on the present work, we estimate that this effect may have raised the annual mean temperatures of De Bilt by 0.10 ± 0.06 °C during the 20th century, being almost the full value of the present-day urban heat advection. The 0.10 ± 0.06 °C rise due to urban heat advection corresponds to about 10% of the observed temperature rise of about 1.0 °C in the last century.
We present a dataset of daily resolution climatic time series that has been compiled for the European Climate Assessment (ECA). As of December 2001, this ECA dataset comprises 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East. Almost all series cover the standard normal period 1961-90, and about 50% extends back to at least 1925. Part of the dataset (90%) is made available for climate research on CDROM and through the Internet (at http://www.knmi.nl/samenw/eca).
A comparison of the ECA dataset with existing gridded datasets, having monthly resolution, shows that correlation coefficients between ECA stations and nearest land grid boxes between 1946 and 1999 are higher than 0.8 for 93% of the temperature series and for 51% of the precipitation series. The overall trends in the ECA dataset are of comparable magnitude to those in the gridded datasets.
The potential of the ECA dataset for climate studies is demonstrated in two examples. In the first example, it is shown that the winter (October-March) warming in Europe in the 1976-99 period is accompanied by a positive trend in the number of warm-spell days at most stations, but not by a negative trend in the number of cold-spell days. Instead, the number of cold-spell days increases over Europe. In the second example, it is shown for winter precipitation between 1946 and 1999 that positive trends in the mean amount per wet day prevail in areas that are getting drier and wetter. Because of its daily resolution, the ECA dataset enables a variety of empirical climate studies, including detailed analyses of changes in the occurrence of extremes in relation to changes in mean temperature and total precipitation.
The long struggle to come from ad hoc and indiscriminate use or misuse of the river Rhine by locals and travellers towards the present integrated and internationally co-ordinated approach to the management of the river and its uses is described as a long and protracted mental climate change. In hindsight, this process was necessary to be prepared for the real climate change that we are currently experiencing. We describe how the river managers in the Rhine basin anticipate climate change.
The Climate scenario's for WB21 (published in Dutch, see the chapter ‘klimaat' of this website) are explained and augmented with a stagnating Gulf Stream scenario. The various scenario's are coupled on the so-called ‘perspectives' (Egalitarian, Controlist/Individualist), defined in the IRMA report.
These scenarios are an update of the NW4/WB21 scenarios originating from 1997/2000. The update incorporates in the WB21 scenarios the results of the recently published IPCC Third Assessment Report (TAR). Together with the previous versions, these scenarios had been the standard for climate impact studies in the Netherlands from 1997 onward. They are replaced by new ones in 2006, after the publication of the IPCC Fourth Assessment Report (4AR)
There seems some contradiction between the subjective and the instrumental perception of past climate change. Nowadays the fairy tale from Granny's days about climate change seems to be mixed with real effects.
We recovered daily visual Weather reports of Isahaya, a town close to
The official meteorological records in
Zonal-scale patterns of precipitation change, as reconstructed for the Mid-Pliocene and two Pleistocene maxima, are compared with those generated in standard 2*CO2-1*CO2 equilibrium experiments by two high-resolution GCMS of equal sensitivities of precipitation and temperature to CO2 doubling. We find that the three warm paleoclimates, despite differences in boundary conditions/forcings, exhibit a similarity in zonal-scale patterns of change for precipitation over land in the Northern Hemisphere (NH); the between-epoch pattern correlation is 0.9 on the average. The two models give marked differences in zonal distribution of precipitation anomalies at mid-latitudes; the between-model pattern correlation for changes of precipitation over NH land is 0.4.
The response of precipitation over the NH land area to the NH warming is about 10%/°C in the paleodata compared to 3%/°C in the models. The largest model/paleodata discrepancy refers to the present-day desert belt, where a large precipitation anomaly persists in all epochs. North of 50 N, the absolute values of the zonally-averaged precipitation anomalies simulated by both models fall in the range implied by the three warm paleoclimates, but they are systematically lower than the anomalies of the Mid-Pliocene. If our reconstructions are valid and if climate changes in the Mid-Pliocene were driven solely by CO2 changes, then our results suggest that models are underestimating the magnitude of the precipitation response, especially in the regions of subtropical deserts; the magnitude of the simulated temperature response at high latitudes is also underestimated. At least part of the reported model/paleodata discordance appears to be due to lack of interactive land surface package in the models examined.
Pressure data from Indonesia and Tahiti for years before 1866 are used to extend the Southern Oscillation Index (SOI) back to 1841, with a gap between 1861 and 1865. Extension further is possible using an index of Jakarta rainday counts back to 1829. Rainday counts correlate (r = -0.60) with average Jakarta pressure for the June-November dry season over the 1876-1944 period. Although low, this correlation is still better than the correlation of tree rings with pressure or SOI. After 1950 the rainday count/pressure relationship alters, and by the 1990s 18% more raindays (an increase of seven per dry season) occur than the pressure would indicate. The dramatic increase in the size and population of Jakarta since 1950 is considered the most likely reason.
Consequences of a Gulf Stream induced ocean surface cooling for the temperature climate of Western Europe were studied by means of a conditional perturbation of the observed daily temperature time series of the Netherlands. On days with advection of air masses of maritime origin, the observed temperatures in the series were lowered with a fixed value, representing the influence of a cooler Atlantic Ocean. On the other days, the observed temperatures were left unchanged. The perturbation results in a decrease in the mean temperature that is almost constant over the year, and in a change in the standard deviation of the daily temperatures that is seasonally dependent. Due to preferential cooling of warm winter days, the standard deviation decreases in the winter, whereas in the other seasons the standard deviation increases as a result of preferential cooling of days with low temperatures. Although this ocean cooling scenario indicates an increase of the relative frequency of cold winters and cool summers, it is neither characterized by the occurrence of winters with unprecedented low temperatures nor by the disappearance of summer heat waves.
Observed relations between meteorological elements in the present-day climate are used to transform an observed daily series into representative series of the possible future climate. For point precipitation the method needs a reasonable guess of the large-scale seasonal changes in the seasonal surface air temperature and surface air pressure. An example of the application is given for De Bilt (The Netherlands).
The De Bilt temperature series shows a warming trend. Using the P27 circulation classification, we separated the advection effect from the large-scale warming. The analysis shows that the trend in De Bilt should be explained by a (temporary) change in circulation rather then by an intrinsic atmospheric warming.
Paleoclimatic reconstructions for the Mid-Holocene, Eemian, Mid-Pliocene, and the Last Glacial Maximum are used to test the paleoanalog hypothesis and to develop a regional climate change scenario based on linear scaling by one parameter - the mean Northern Hemisphere temperature change with respect to present, ΔTHN. The empirical verification of the paleoanalog hypothesis is extended to a cold epoch for zonal means and to regional distributions of temperature for the warm epochs. The best agreement among the scaled paleoanomolies from different epochs is obtained if the seasonal temperatures are scaled with ΔTHN of the corresponding season. Preferential areas are identified where the paleoanalog hypothesis works relatively well; these areas coincide with the areas of the most pronounced warming. It is shown that the geographical distributions of the winter temperature anomalies over land in the paleodata are similar to those in the 1980-1990 period. From the three warm periods, a paleodata-based scenario is deduced for the spatial distribution of temperature in a future climate, on the scale of continents. The conditions under which scenarios based on paleodata can be applied are discussed.
The Climate Scenario Group at the Royal Netherlands Meteorological Institute makes use of empirical relations between different climate elements to transform an observed local meteorological time series with daily resolution into an internally consistent daily time series that could occur in the future climate. This scenario meets the requirement from impact groups, as it has local details and gives a plausible description of the day to day variability including the daily extremes.
The dependence of rainfall amount per wet day as function of temperature is explored for De Bilt. On basis of diurnal cycle, frontal rain amounts can be separated from surface-forced convective rain amounts. The convective branch in rainfall starts from maximum temperatures of 20°C and becomes increasingly dominating for higher temperatures. The convective amounts increases in that region by 10%/°C, which is Clausius-Clapeyron to the power 3/2.
The time delay Δ between the warmest day in the mean annual curve and 21 June varies from 55 days over the coastal sea to 35 days in the inland of the Netherlands. Worldwide the lowest values is about 25 days for remote continental areas (Siberia). The delay seawater is about 60-65 days. The major variation is found in a coastal zone of 50 km lateral extend. The variation is understood by a simple model of periodic sinusoidal heating and Newtonial damping.
Preliminary results are reported about experiments on the effect on 36-h progs of perturbations in the initial condition.