Prefaces Acknowledgements 1. Mountains and their climatological study 2. Geographical controls of mountain meteorological elements 3. Circulation systems related to orography 4. Climatic characteristics of mountains 5. Regional case studies 6. Mountain bioclimatology 7. Changes in mountain climates Appendix General index Author index.

Mountain Weather and Climate

Historical reanalyses that span more than a century are needed for a wide range of studies, from understanding large‐scale climate trends to diagnosing the impacts of individual historical extreme weather events. The Twentieth Century Reanalysis (20CR) Project is an effort to fill this need. It is supported by the National Oceanic and Atmospheric Administration (NOAA), the Cooperative Institute for Research in Environmental Sciences (CIRES), and the U.S. Department of Energy (DOE), and is facilitated by collaboration with the international Atmospheric Circulation Reconstructions over the Earth initiative. 20CR is the first ensemble of sub‐daily global atmospheric conditions spanning over 100 years. This provides a best estimate of the weather at any given place and time as well as an estimate of its confidence and uncertainty. While extremely useful, version 2c of this dataset (20CRv2c) has several significant issues, including inaccurate estimates of confidence and a global sea level pressure bias in the mid‐19th century. These and other issues can reduce its effectiveness for studies at many spatial and temporal scales. Therefore, the 20CR system underwent a series of developments to generate a significant new version of the reanalysis. The version 3 system (NOAA‐CIRES‐DOE 20CRv3) uses upgraded data assimilation methods including an adaptive inflation algorithm; has a newer, higher‐resolution forecast model that specifies dry air mass; and assimilates a larger set of pressure observations. These changes have improved the ensemble‐based estimates of confidence, removed spin‐up effects in the precipitation fields, and diminished the sea‐level pressure bias. Other improvements include more accurate representations of storm intensity, smaller errors, and large‐scale reductions in model bias. The 20CRv3 system is comprehensively reviewed, focusing on the aspects that have ameliorated issues in 20CRv2c. Despite the many improvements, some challenges remain, including a systematic bias in tropical precipitation and time‐varying biases in southern high‐latitude pressure fields.

/pdf/towards-a-more-reliable-historical-reanalysis-improvements-3osv1v8h3n.pdf

Towards a more reliable historical reanalysis: improvements for version 3 of the Twentieth Century Reanalysis system

This study is motivated by diverse needs for better forecasts of extreme precipitation and floods. It is enabled by unique hourly observations collected over six years near California’s Russian River and by recent advances in the science of atmospheric rivers (ARs). This study fills key gaps limiting the prediction of ARs and, especially, their impacts by quantifying the duration of AR conditions and the role of duration in modulating hydrometeorological impacts. Precursor soil moisture conditions and their relationship to streamflow are also shown. On the basis of 91 well-observed events during 2004‐10, the study shows that the passage of ARs over a coastal site lasted 20 h on average and that 12% of the AR events exceeded 30 h. Differences in storm-total water vapor transport directed up the mountain slope contribute 74% of the variance in storm-total rainfall across the events and 61% of the variance in storm-total runoff volume. ARs with double the composite mean duration produced nearly 6 times greater peak streamflow and more than 7 times the storm-total runoff volume. When precursor soil moisture was less than 20%, even heavy rainfall did not lead to significant streamflow. Predicting which AR events are likely to produce extreme impacts on precipitationandrunoffrequiresaccuratepredictionofARdurationatlandfallandobservationsofprecursor soil moisture conditions.

Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal northern California and the role of long-duration atmospheric rivers in creating extreme hydrometeorological events

The eruption of Tambora (Indonesia) in April 1815 had substantial effects on global climate and led to the 'Year Without a Summer' of 1816 in Europe and North America. Although a tragic event-tens of thousands of people lost their lives-the eruption also was an 'experiment of nature' from which science has learned until today. The aim of this study is to summarize our current understanding of the Tambora eruption and its effects on climate as expressed in early instrumental observations, climate proxies and geological evidence, climate reconstructions, and model simulations. Progress has been made with respect to our understanding of the eruption process and estimated amount of SO2 injected into the atmosphere, although large uncertainties still exist with respect to altitude and hemispheric distribution of Tambora aerosols. With respect to climate effects, the global and Northern Hemispheric cooling are well constrained by proxies whereas there is no strong signal in Southern Hemisphere proxies. Newly recovered early instrumental information for Western Europe and parts of North America, regions with particularly strong climate effects, allow Tambora's effect on the weather systems to be addressed. Climate models respond to prescribed Tambora-like forcing with a strengthening of the wintertime stratospheric polar vortex, global cooling and a slowdown of the water cycle, weakening of the summer monsoon circulations, a strengthening of the Atlantic Meridional Overturning Circulation, and a decrease of atmospheric CO2. Combining observations, climate proxies, and model simulations for the case of Tambora, a better understanding of climate processes has emerged. WIREs Clim Change 2016, 7:569-589. doi: 10.1002/wcc.407 This article is categorized under: 1Paleoclimates and Current Trends > Paleoclimate.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcc.407

Tambora 1815 as a test case for high impact volcanic eruptions: Earth system effects.

This work focuses on the spatial and temporal variability of burnt area (BA) in the entire Iberian Peninsula (IP) and on the construction of statistical models to reproduce the inter-annual variability. A novel common dataset was assembled for the whole IP by merging the registered BA from 66 administrative regions of both Portugal and Spain. We applied a cluster analysis to identify larger regions with similar fire regimes and results point to the existence of four clusters (Northwestern, Northern, Southwestern and Eastern) whose spatial patterns and seasonal fire regimes are shown to be related with constraining factors such as topography, vegetation cover and climate conditions. The relationship between BA at monthly time scale with both long-term climatic pre-conditions and short-term synoptic forcing was assessed using correlation and regression analysis based on: (1) temperature and precipitation from 2 to 7 months in advance to fire peak season, (2) synoptic weather patterns derived from 11 distinct Weather Types Classifications (WTC). Different relations were obtained for each IP region with a relevant link being identified between BA and short-term synoptic forcing for all clusters, while the relation with long-term climatic preconditioning was relevant for all but one cluster. Stepwise regression models based on the best climatic and synoptic circulation predictors were developed with cross-validation to avoid over fitting. The performance of the models varies within IP regions, though models exclusively based on WTC tend to better reproduce the annual BA time series than those merely based on pre-conditioning climatic information. Nevertheless, the use of both synoptic and climatic predictors provides the best results, particularly for the two western clusters, with Pearson correlation coefficient values higher than 0.7. Finally, it is shown that typical synoptic configurations that favour high values of BA correspond to dry and warm wind flows associated with anti-cyclonic regimes.

Modelling wildfire activity in Iberia with different atmospheric circulation weather types

The vertical structure of water vapor content in the atmosphere strongly affects the amount of solar radiation reaching the Earth’s surface and processes associated with the formation of clouds and atmospheric precipitation. The purpose of this study was to assess the vertical differentiation of water vapor over Europe on a seasonal basis and also to evaluate the role of atmospheric circulation in changes therein. Daily values of specific humidity (SHUM) for the time period 1981–2015 were obtained from pressure levels available from ECMWF Era-Interim reanalysis data and used in the study. Eight grid points were analyzed in detail. Each point is representative of a region with different moisture conditions. SHUM profiles were then used to identify cases of moisture inversion. Horizontal flux of specific humidity (SHUMF) was analyzed for principal pressure levels that occur in both inversion-type and inversion-free situations. In addition, SHUM and SHUMF anomalies were identified for advection directions. The research results showed the existence of differences in the vertical structure of water vapor content in the troposphere over Europe, and the Northeastern Atlantic and the presence of moisture inversions not only in areas north of 60°N but also in temperate and subtropical zones. Inversions can occur in two different forms—surface-based and elevated. The occurrence of inversions varies with the seasons. The role of atmospheric circulation is observable in the winter and triggers both surpluses and shortages of moisture via the effect of specific pressure system types (significant role of seasonal pressure high) and via advection directions. In addition, there exists a clear difference between the structure of moisture in the atmospheric boundary layer and in the free atmosphere.

/pdf/vertical-structure-of-moisture-content-over-europe-mtwokqq4qs.pdf

Vertical Structure of Moisture Content over Europe

The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the “Pairwise Homogenization Algorithm” (PHA) to the non-homogenized datasets. Previous studies found that the PHA can perform well at correcting synthetic time series when certain artificial biases are introduced. However, its performance with real world data has been less well studied. Therefore, the homogenized GHCN datasets (Version 3 and 4) were downloaded almost daily over a 10-year period (2011-2021) yielding 3689 different updates to the datasets. The different breakpoints identified were analyzed for a set of stations from 24 European countries for which station history metadata were available. A remarkable inconsistency in the identified breakpoints (and hence adjustments applied) was revealed. Of the adjustments applied for GHCN Version 4, 64% (61% for Version 3) were identified on less than 25% of runs, while only 16% of the adjustments (21% for Version 3) were identified consistently for more than 75% of the runs. The consistency of PHA adjustments improved when the breakpoints corresponded to documented station history metadata events. However, only 19% of the breakpoints (18% for Version 3) were associated with a documented event within 1 year, and 67% (69% for Version 3) were not associated with any documented event. Therefore, while the PHA remains a useful tool in the community’s homogenization toolbox, many of the PHA adjustments applied to the homogenized GHCN dataset may have been spurious. Using station metadata to assess the reliability of PHA adjustments might potentially help to identify some of these spurious adjustments.

/pdf/evaluation-of-the-homogenization-adjustments-applied-to-2dsang6c.pdf

Evaluation of the Homogenization Adjustments Applied to European Temperature Records in the Global Historical Climatology Network Dataset

http://acta.urk.edu.pl/pdf-102877-34267?filename=VARIABILITY OF THERMAL.pdf

Variability of thermal resources in poland as a result of ongoing climate change

The impact of fog on relief modified urban heat island (RMUHI) in Krakow has been presented using fog observations at 06 UTC from two meteorological stations: a rural one (Balice, B) and an urban one (Botanical Garden, BG) from the period 2006–2015 Daily UHI magnitude for the valley floor for the same period was estimated as TminBG–TminB, while for the period 2010–2015, eight daily courses of UHI were available, for the urban areas in the valley floor and 50 m above it, together with air temperature inversion data UHI data for days with various combinations of fog occurrence and weather conditions were compared using non-parametric statistical tests: Wald-Wolfowitz test, Kolmogorov-Smirnov test and U Mann-Whitney test Data of 2010–2015 were also the subject of cluster analysis (k-means method) Fog is an important factor decreasing UHI magnitude by about 1 K but mainly during weather conditions with little or no cloudiness and small wind speed or atmospheric calm, during anticyclonic synoptic situations, and only in the valley floor areas With an increase in cloudiness and wind speed, the role of fog decreases and is similar in all parts of the city

/pdf/role-of-fog-in-urban-heat-island-modification-in-krakow-qrhhmwdd0e.pdf

Role of fog in urban heat island modification in Kraków, Poland

Extreme weather phenomena such as wind gusts, heavy precipitation, hail, thunderstorms, tornadoes, and many others usually occur when there is a change in air mass and the passing of a weather front over a certain region. The climatology of weather fronts is difficult, since they are usually drawn onto maps manually by forecasters; therefore, the data concerning them are limited and the process itself is very subjective in nature. In this article, we propose an objective method for determining the position of weather fronts based on the random forest machine learning technique, digitized fronts from the DWD database, and ERA5 meteorological reanalysis. Several aspects leading to the improvement of scores are presented, such as adding new fields or dates to the training database or using the gradients of fields.

Agnieszka Wypych

Papers

Vertical Structure of Moisture Content over Europe

Evaluation of the Homogenization Adjustments Applied to European Temperature Records in the Global Historical Climatology Network Dataset

Variability of thermal resources in poland as a result of ongoing climate change

Role of fog in urban heat island modification in Kraków, Poland

Machine Learning-Based Front Detection in Central Europe