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.

The National Oceanic and Atmospheric Administration (NOAA) released the 1981–2010 U.S. Climate Normals in July 2011, representing the latest decadal installment of this long-standing product line. Climatic averages (and other statistics) of temperature, precipitation, snowfall, and numerous derived quantities were calculated for ~9,800 stations operated by the U.S. National Weather Service (NWS). They include estimated normals, or “quasi normals,” for approximately 2,000 active short-record stations such as those in the U.S. Climate Reference Network. The 1981–2010 installment features several new products and methodological enhancements: 1) state-of-the-art temperature homogenization at the monthly scale, 2) extensive utilization of quality-controlled daily climate data, 3) new statistical approaches for calculating daily temperature normals and heating and cooling degree days, and 4) a comprehensive suite of precipitation, snowfall, and snow depth statistics. This paper provides a general overview of this new suite of climate normals products.

The two monthly precipitation products of the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) are compared on a 23-yr period, January 1979-December 2001. For the long-term mean, major precipitation patterns are clearly demonstrated by both products, but there are differences in the pattern magnitudes. In the tropical ocean the CMAP is higher than the GPCP, but this is reversed in the high-latitude ocean. The GPCP-CMAP spatial correlation is generally higher over land than over the ocean. The correlation between the global mean oceanic GPCP and CMAP is significantly low. It is very likely because the input data of the two products have much less in common over the ocean; in particular, the use of atoll data by the CMAP is disputable. The decreasing trend in the CMAP oceanic precipitation is found to be an artifact of input data change and atoll sampling error. In general, overocean precipitation represented by the GPCP is more reasonable; over land the two products are close, but different merging algorithms between the GPCP and the CMAP can sometimes produce substantial discrepancy in sensitive areas such as equatorial West Africa. EOF analysis shows that the GPCP and the CMAP are similar in 6 out of the first 10 modes, and the first 2 leading modes (ENSO patterns) of the GPCP are nearly identical to their

[1] Probable maximum precipitation (PMP) is the greatest accumulation of precipitation for a given duration meteorologically possible for an area. Climate change effects on PMP are analyzed, in particular, maximization of moisture and persistent upward motion, using both climate model simulations and conceptual models of relevant meteorological systems. Climate model simulations indicate a substantial future increase in mean and maximum water vapor concentrations. For the RCP8.5 scenario, the changes in maximum values for the continental United States are approximately 20%-30% by 2071-2100. The magnitudes of the maximum water vapor changes follow temperature changes with an approximate Clausius-Clapeyron relationship. Model-simulated changes in maximum vertical and horizontal winds are too small to offset water vapor changes. Thus, our conclusion is that the most scientifically sound projection is that PMP values will increase in the future due to higher levels of atmospheric moisture content and consequent higher levels of moisture transport into storms. Citation:

This paper presents new calculations of Lake Victoria's water balance. Evaporation is estimated using both the Penman formula and the energy balance approach, and sensitivity studies are performed to determine the influence of input data on the estimates. Rainfall over the lake is estimated from catchment rainfall using a relationship between the two that was derived using satellite data. The results, using the reference period 1956-1978, indicate that mean annual rainfall over the lake is 1791 mm, compared to mean annual evaporation of 1551 mm. When compared with lake level changes, tributary inflow, and discharge during this period, there is a resultant imbalance of 19 mm. Adding this amount to the calculated evaporation, we are able to reproduce with great accuracy the lake level changes during the period 1956-1978 utilizing precipitation estimates of this study plus measured inflow and discharge. Sensitivity studies show that the discrepancy in the balance of 19 mm is considerably smaller than the error in evaporation calculations that can be introduced by uncertainties in the input data. Of particular concern is cloudiness. The diurnal cycle of cloudiness is quite different over the lake than at shoreline stations and the total cloud cover over the lake is probably lower than at these stations. A change from 50% cloudiness to 30% can increase evaporation by about 30%. Thus, this study underscores the need for adequate cloud data, sufficient to resolve the diurnal cycle, as well as direct estimates of lake rainfall in assessing the lake's water balance. Le bilan hydrologique du Lac VictoriaRésumé Ce papier présente de nouveaux calculs du bilan hydrologique du Lac Victoria. L'évaporation est estimée par la formule de Penman et la méthode du bilan énergétique. Une étude de sensibilité a été entreprise pour déterminer l'influence des données d'entrée sur les estimations. Les précipitations sur le lac ont été calculées à partir de données satellitaires utilisant une relation établie entre la pluie sur le lac et celle du bassin versant. Les résultats, basés sur une période de référence allant de 1956 à 1978, indiquent que la moyenne des précipitations annuelles sur le lac est égale à 1791 mm, comparée à une moyenne annuelle de l'évaporation égale à 1551 mm. Une comparaison avec les modifications du niveau du lac, les écoulements et débits pendant cette période indique un surplus de 19 mm. Lorsque cette hauteur est ajoutée à l'évaporation calculée, on arrive à reproduire très exactement les fluctuations du lac de 1956 à 1978, en utilisant les précipitations estimées sur le lac ainsi que les débits et les écoulements mesurés. Les études de sensibilité montrent que l'erreur de 19 mm sur le bilan hydrologique est nettement inférieure à celle induite dans les calculs de l'évaporation en raison des incertitudes sur les données d'entrée. La nébulosité reste un problème majeur car son cycle diurne est sensiblement différent sur le lac et sur les stations côtières, la nébulosité totale sur le lac étant probableme...

Recent studies of snow climatology show a mix of trends but a preponderance of evidence suggest an overall tendency toward decreases in several metrics of snow extremes. The analysis performed herein on maximum seasonal snow depth points to a robust negative trend in this variable for the period of winter 1960/1961-winter 2014/2015. This conclusion is applicable to North America. Maximum snow depth is also mostly decreasing for those European stations analyzed. Research studies show generally negative trends in snow cover extent and snow water equivalent across both North America and Eurasia. These results are mostly, but not fully, consistent with simple hypotheses for the effects of global warming on snow characteristics.

The Integrated Global Radiosonde Archive (IGRA) is a collection of historical and near-real-time radiosonde and pilot balloon observations from around the globe. Consisting of a foundational dataset of individual soundings, a set of sounding-derived parameters, and monthly means, the collection is maintained and distributed by the National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI). It has been used in a variety of applications, including reanalysis projects, assessments of tropospheric and stratospheric temperature and moisture trends, a wide range of studies of atmospheric processes and structures, and as validation of observations from other observing platforms. In 2016, NCEI released version 2 of the dataset, IGRA 2, which incorporates data from a considerably greater number of data sources, thus increasing the data volume by 30%, extending the data back in time to as early as 1905, and improving the spatial coverage. To create IGRA 2, 40 data sources were converted into a common data format and merged into one coherent dataset using a newly designed suite of algorithms. Then, an overhauled version of the IGRA 1 quality-assurance system was applied to the integrated data. Last, monthly means and sounding-by-sounding moisture and stability parameters were derived from the new dataset. All of these components are updated on a regular basis and made available for download free of charge on the NCEI website.

Editor’s note: For easy download the posted pdf of the State of the Climate for 2019 is a low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download.