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Abstract There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far. 

Abstract Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies. 

Abstract During and after recent La Niña events, the decline of the eastern East African (EA) March‐April‐May (MAM) rains has set the stage for life‐threatening sequential October‐November‐December (OND) and MAM droughts. The MAM 2022 drought was the driest on record, preceded by three poor rainy seasons, and followed by widespread starvation. Connecting these dry seasons is an interaction between La Niña and climate change. This interaction provides important opportunities for long‐lead prediction and proactive disaster risk management, but needs exploration. Here, for the first time, we use observations, reanalyses, and climate change simulations to show that post‐1997 OND La Niña events are robust precursors of: (a) strong MAM “Western V sea surface temperature Gradients” in the Pacific, which (b) help produce large increases in moisture convergence and atmospheric heating near Indonesia, which in turn produce (c) regional shifts in moisture transports and vertical velocities, which (d) help explain the increased frequency of dry EA MAM rainy seasons. We also show that, at 20‐year time scales, increases in atmospheric heating in the Indo‐Pacific Warm Pool region are attributable to warming Western V SST, which is in turn largely attributable to climate change. As energy builds up in the oceans and atmosphere, during and after La Niña events, we see stronger heating and heat convergence over warm tropical waters near Indonesia. The result of this causal chain is that increased Warm Pool atmospheric heating and moisture convergence sets the stage for dangerous sequential droughts in EA. These factors link EA drying to a stronger Walker Circulation and explain the predictable risks associated with recent La Niña events. 

Abstract Dendrochronology in West Africa has not yet been developed despite encouraging reports suggesting the potential for long tree-ring reconstructions of hydroclimate in the tropics. This paper shows that even in the absence of local tree chronologies, it is possible to reconstruct the hydroclimate of a region using remote tree rings. We present the West Sub-Saharan Drought Atlas (WSDA), a new paleoclimatic reconstruction of West African hydroclimate based on tree-ring chronologies from the Mediterranean Region, made possible by the teleconnected climate relationship between the West African Monsoon and Mediterranean Sea surface temperatures. The WSDA is a one-half degree gridded reconstruction of summer Palmer Drought Severity indices from 1500 to 2018 CE, produced using ensemble point-by-point regression. Calibration and verification statistics of the WSDA indicate that it has significant skill over most of its domain. The three leading modes of hydroclimate variability in West Africa are accurately reproduced by the WSDA, demonstrating strong skill compared to regional instrumental precipitation and drought indices. The WSDA can be used to study the hydroclimate of West Africa outside the limit of the longest observed record and for integration and comparison with other proxy and archaeological data. It is also an essential first step toward developing and using local tree-ring chronologies to reconstruct West Africa’s hydroclimate. 

Abstract The Congo basin in central equatorial Africa is home to some of the most intense convection in the global tropics. Mesoscale convective systems (MCSs) provide much of the annual rainfall over this region during the March–April–May (MAM) and September–October–November (SON) rainy seasons. Features of these systems are essential to rainfall variability in this region and greatly impact human health, agriculture, livestock, and drought monitoring. Knowledge of variability is hindered by the lack of in‐situ observations and meteorological stations. The present study identifies and tracks MCSs for the 33‐year period 1983–2015 for MAM and SON. MCS and environmental parameters are calculated for the rainy seasons using satellite and reanalysis data. Spatial distributions of MCS parameters and diurnal cycles for select MCS parameters are compared to prior research. Statistical significance testing is performed to determine if there are meaningful differences between the seasons. Seasonal differences are briefly discussed. 650 hPa relative vorticity patterns suggest localized terrain effects may play a role near a local maximum in MCS initiation frequency in the lee of the Great Rift Valley. Spatial distributions of 33‐year MCS counts, trajectories, speeds, sizes, maximum intensities, and durations, based on initiation locations, agree well with prior research. Differences between seasons are statistically significant and variable and latitude dependent. There is high interannual variability among all MCS and environmental parameters. 

Abstract This paper compares the characteristics of the Tropical Easterly Jet (TEJ) and upper‐level winds in six reanalysis products, compares them with soundings at seven West African locations, examines the relationship between Sahel rainfall and the TEJ, and examines factors influencing the TEJ. The jet characteristics assessed by MERRA2, NCEP 1, JRA 55, and ERA 5 are similar. CFSR and 20th Century Reanalysis are outliers in nearly every analysis, overestimating wind speeds by as much as 25 to 40% compared to other reanalyses. Over the period 1948 to 2014, the correlation between rainfall and TEJ magnitude is .72. Arguments based on observations and modelling studies provide evidence that on interannual scales changes in the TEJ are not forced by rainfall, that large‐scale factors drive the TEJ. Potential mechanisms are discussed for a causal relationship such that a strong jet leads to high rainfall. However, further modelling efforts are needed to conclusively determine whether the TEJ/Sahel rainfall link is a result of common forcing factors. The factors that appear to control jet strength include sea‐surface temperature (SST) contrast between the central equatorial Pacific and central equatorial Indian Ocean (correlation of −.64), SST contrast between the central equatorial and the southern subtropical Indian Ocean (correlation of −.39), the latitude of the shift between upper‐tropospheric easterlies and westerlies in the Southern Hemisphere (correlation of −.84 at 150 hPa), and the intensity of the Southern Hemisphere westerlies (correlation of +.52 at 200 hPa). This suggests considerable control on the TEJ by extra‐tropical circulation in the Southern Hemisphere. 

Abstract. Narrative evidence contained within historical documents and inscriptions provides an important record of climate variability for periods prior to the onset of systematic meteorological data collection. A common approach used by historical climatologists to convert such qualitative information into continuous quantitative proxy data is through the generation of ordinal-scale climate indices. There is, however, considerable variability in the types of phenomena reconstructed using an index approach and the practice of index development in different parts of the world. This review, written by members of the PAGES (Past Global Changes) CRIAS working group – a collective of climate historians and historical climatologists researching Climate Reconstructions and Impacts from the Archives of Societies – provides the first global synthesis of the use of the index approach in climate reconstruction. We begin by summarising the range of studies that have used indices for climate reconstruction across six continents (Europe, Asia, Africa, the Americas, and Australia) as well as the world’s oceans. We then outline the different methods by which indices are developed in each of these regions, including a discussion of the processes adopted to verify and calibrate index series, and the measures used to express confidence and uncertainty. We conclude with a series of recommendations to guide the development of future index-based climate reconstructions to maximise their effectiveness for use by climate modellers and in multiproxy climate reconstructions.