Subdaily meteorological measurements of temperature, direction of the movement of the clouds, and cloud cover in the Late Maunder Minimum by Louis Morin in Paris

We have digitized three meteorological variables (temperature, direction of the movement of the clouds, and cloud cover) from copies of Louis Morin’s original measurements (source: Institute of History/Oeschger Centre for Climate Change Research, University of Bern; Institut de France) and subjected them to quality analysis to make these data available to the scientific community. Our available data cover the period 1665–1713 (temperature beginning in 1676). We compare the early instrumental temperature dataset with statistical methods and proxy data to validate the measurements in terms of inhomogeneities and claim that they are, apart from small inhomogeneities, reliable. The Late Maunder Minimum (LMM) is characterized by cold winters and falls and moderate springs and summers with respect to the reference period of 1961–1990. Winter months show a significantly lower frequency of the westerly direction in the movement of the clouds. This reduction of advection from the ocean leads to a cooling in Paris in winter. The influence of the advection becomes apparent when comparing the last decade of the 17th century (cold) and the first decade of the 18th century (warm). Consequently, the unusually cold winters in the LMM are largely caused by a lower frequency of the westerly direction in the movement of the clouds. An impact analysis reveals that the winter of 1708/09 was a devastating one with respect to consecutive ice days, although other winters are more pronounced (e.g., the winters of 1676/77, 1678/79, 1683/84, 1692/93, 1694/95, and 1696/97) in terms of mean temperature, ice days, cold days, or consecutive cold days. An investigation of the cloud cover data revealed a high discrepancy, with the winter season (DJF, -14.0 %), the spring season (MAM, -20.8 %), the summer season (JJA, -17.9 %), and the fall season (SON, -18.0 %) showing negative anomalies of total cloud cover (TCC) with respect to the 30-year mean of the ERA5 data (1981–2010). Thus, Morin’s measurements of temperature and direction of the movement of the clouds seem to be trustworthy, whereas cloud cover in quantitative terms should be taken with caution

Early Humidity Measurements by Louis Morin in Paris between 1701 and 1711—Data and Metadata

This paper discusses what is, to our knowledge, the oldest subdaily measurement series of humidity taken over several years. Louis Morin performed the measurements in Paris, three times a day, between May 1701 and June 1711. A correlation analysis of Morin’s humidity measurements with various meteorological variables yields results comparable to those of a parallel analysis of the relative humidity measurements of the E-OBS data: the Spearman correlation coefficient between the humidity and the daily minimum temperature is -0.43 (p < 0.01); with the mean temperature, it is -0.54 (p < 0.01); with the maximum temperature, it is -0.59 (p < 0.01); with the diurnal temperature range, it is -0.65 (p < 0.01); and with the total cloud cover, 0.33 (p < 0.01). However, with a Spearman correlation coefficient of 0.11 (p < 0.01), no correlation is found with the precipitation data. Further evidence for the plausibility of the measurements is shown by a day-by-day analysis of the first half-year of 1709. Here, abrupt changes in the humidity measurements of Morin can be explained by the other measurements/observations of Morin. According to the correlation analysis, indirect notes in his journal, and others, we argue that Morin used the hygrometer developed by Vincenzo Viviani. However, the conversion of the data to common units is not performed and is subject to further research

Precipitation reconstructions for Paris based on the observations by Louis Morin, 1665-1713 CE

This paper presents a precipitation reconstruction that is based on the continuous observations by Louis Morin in Paris from 1665–1713. Morin usually recorded precipitation intensity and duration three times each day (sometimes up to six times) when it snowed or rained. The continuity of his observations can be calculated considering all measurements and observations (e.g., temperature, cloud cover), where on 98.7% of all days between February 1665 and July 1713 at least one entry per day is noted. To convert these observations to common units, we calibrated them with a multiplicative interacting model using Philippe and Gabriele-Philippe de la Hire’s instrumental measurements from Paris. The two series of measurements by de la Hire (father and son) and observations by Morin overlap from 1688–1713. To test the quality of the reconstruction, we analyzed it with the de la Hire’s measurements, proxy data, an internal analysis of Morin’s measurements of different climate variables, and modern data. Thus, we assess the reliability of the precipitation reconstructions based on Morin’s data as follows. We have moderate confidence regarding the exact quantities of daily, seasonal, and annual precipitation totals. We have low confidence regarding exceptionally high precipitation amounts, but we have high confidence in the indices of an impact analysis (i.e., dry days, wet days, consecutive dry days, consecutive wet days); in monthly frequencies of rainfall; and in interannual, interseasonal, and interdecadal variability. Rainy seasons with precipitation totals greater than 250mm occurred in MAM 1682, JJA 1682, SON 1687, JJA 1697, and JJA 1703. Furthermore, compared to other DJF seasons, the winter of 1666/1667 slightly stands out with a precipitation total of 214.6 mm. Dry seasons with precipitation totals less than 60mm occurred in SON 1669, DJF 1671/1672, and DJF 1690/1691. An impact analysis shows no abnormalities regarding consecutive dry days or wet days in MAM. In JJA a longer dry period of 31 days appeared in 1686 and a dry period of 69 d appeared in DJF 1671/1672

Assessing the Climate Monitoring Utility of Radio Occultation Data: From CHAMP to FORMOSAT-3/COSMIC

Radio Occultation (RO) data, using Global Positioning System (GPS) signals, deliver high quality observations of the atmosphere, which are well suited for monitoring global climate change. The special climate utility of RO data arises from their accuracy and long-term stability due to self-calibration. Launched in 2000, the German research satellite CHAMP (CHAllenging Minisatellite Payload for geoscientific research) provides the first opportunity to create RO based climatologies. Overlap with data from the Taiwan/US FORMOSAT-3/COSMIC (Formosa Satellite Mission 3/Constellation Observing System for Meteorology, Ionosphere and Climate, F3C) mission allows the testing for consistency of climatologies derived from different satellites.We show initial results for zonal mean climatologies as well as tropical tropopause parameters based on F3C RO data. Our results indicate excellent agreement between RO climatologies from different F3C satellites as well as between data from different RO missions. After subtraction of the estimated respective sampling error, seasonal temperature climatologies derived from different F3C satellites are in agreement to within < 0.1 K almost everywhere in the considered domain between 8 and 35 km altitude. Monthly mean tropical tropopause (lapse rate) temperatures and altitudes derived from four different RO missions show remarkable consistency (< 0.2 - 0.5 K, < 50 - 100 m) and indicate that data from different RO missions can indeed be combined without need for inter-calibration. F3C final constellation sampling error estimation shows a small oscillating local time related error (__0.03 K amplitude) in the extratropics

Revisiting internal gravity waves analysis using GPS RO density profiles: comparison with temperature profiles and application for wave field stability study

We revise selected findings regarding the utilization of Global Positioning System radio occultation (GPS RO) density profiles for the analysis of internal gravity waves (IGW), introduced by Sacha et al. (2014). Using various GPS RO datasets, we show that the differences in the IGW spectra between the dry-temperature and dry-density profiles that were described in the previous study as a general issue are in fact present in one specific data version only. The differences between perturbations in the temperature and density GPS RO profiles do not have any physical origin, and there is not the information loss of IGW activity that was suggested in Sacha et al. (2014). We investigate the previously discussed question of the temperature perturbations character when utilizing GPS RO dry-temperature profiles, derived by integration of the hydrostatic balance. Using radiosonde profiles as a proxy for GPS RO, we provide strong evidence that the differences in IGW perturbations between the real and retrieved temperature profiles (which are based on the assumption of hydrostatic balance) include a significant nonhydrostatic component that is present sporadically and might be either positive or negative. The detected differences in related spectra of IGW temperature perturbations are found to be mostly about ±10 %. The paper also presents a detailed study on the utilization of GPS RO density profiles for the characterization of the wave field stability. We have analyzed selected stability parameters derived from the density profiles together with a study of the vertical rotation of the wind direction. Regarding the Northern Hemisphere the results point to the western border of the Aleutian high, where potential IGW breaking is detected. These findings are also supported by an analysis of temperature and wind velocity profiles. Our results confirm advantages of the utilization of the density profiles for IGW analysis.Grantová Agentura České Republiky | Ref. 16-01562JMinisterstvo Školství, Mládeže a Tělovýchovy | Ref. 7AMB16AT021OeAD-GmbH | Ref. CZ 06/2016Ministerio de Ciencia e Innovación | Ref. CGL2015-71575-

Climate History of the Principality of Transylvania during the Maunder Minimum (MM) Years (1645&ndash;1715 CE) Reconstructed from German Language Sources

This paper deals with the climate in the former Grand Duchy of Transylvania, now one of the three major geographical provinces of Romania, within the so-called Maunder Minimum (MM) (1645&ndash;1715), an astrophysically defined part of the Little Ice Age (LIA), which was characterized by reduced solar activity. The historical data from Transylvania are compared with that from Germany, Austria and Switzerland. This comparison for the period 1645&ndash;1715 shows good agreement but also reveals geographic characteristics of the region. For the first time, we present here a comparison between the four geographic areas in text and tabular form. Quotes from mostly German-language sources are reproduced in English translation. The results clearly help to identify regional climatic differences during the MM. Furthermore, we examine for a longer period (1500&ndash;1950) the extent to which the climate of Transylvania might have been affected by long-term fluctuations in solar activity, as deduced from isotopic reconstructions from ice cores. This way we compared astrophysical conditions with climatological ones in order to see if any probable relations do indeed show up. This comparison suggests a certain solar influence but the agreement is not very pronounced. Future investigation in a pan-European context is needed to reach reliable statements. Some results are unexpected&mdash;such as an unusually small number of severe winters during the last decades of the MM, where extreme cold was restricted to a few years, like the extreme winters 1699/1700 and 1708/1709

Occultations for probing atmosphere and climate

Use of occultation methodology for observing the Earth's atmosphere and climate has become so broad as to comprise solar, lunar, stellar, navigation and satellite­ crosslink occultation methods. The atmospheric parameters obtained extend from the fundamental variables temperature, density, pressure, water vapor, and ozone via a multitude of trace gas species to particulate species such as aerosols and cloud liquid water. Ionospheric electron density is sensed as well. The methods all share the key properties of self-calibration, high accuracy and vertical resolution, global coverage, and (if using radio signals) all-weather capability. Occultation data are thus of high value in a wide range of fields including climate monitoring and research, atmospheric physics and chemistry, operational meteorology, and other fields such as space weather and planetary science. This wide area of variants and uses of the occultation method has led to a diversi­ fication of the occultation-related scientific community into a range of different sub-communities, however. The 1st International Workshop on Occultations for Probing Atmosphere and Cli­ mate-OPAC-1- held September 16-20, 2002, in Graz, Austria, has set in ex­ actly at this point. OPAC-1 aimed at providing a casual forum and stimulating at­ mosphere fertilizing scientific discourse, co-operation initiatives, and mutual learning and support amongst members of all the different sub-communities. The workshop was attended by about 80 participants from 17 different countries who actively contributed to a scientific programme of high quality and to an excellent workshop atmosphere, which was judged by the participants to have fully met the aims expressed

Precipitation reconstructions for Paris based on the observations by Louis Morin, 1665–1713 CE

This dataset includes Louis Morin's daily rainfall records from 1665--1713. More details can be found in the file

An observing system simulation experiment for climate monitoring with GNSS radio occulation data: setup and testbed study

The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data