Relationship between synoptic circulations and the spatial distributions of rainfall in Zimbabwe

This study examines how the atmospheric circulation patterns in Africa south of the equator govern the spatial distribution of precipitation in Zimbabwe. The moisture circulation patterns are designated by an ample set of eight classified circulation types (CTs). Here it is shown that all wet CTs over Zimbabwe features enhanced cyclonic/convective activity in the southwest Indian Ocean. Therefore, enhanced moisture availability in the southwest Indian Ocean is necessary for rainfall formation in parts of Zimbabwe. The wettest CT in Zimbabwe is characterized by a ridging South Atlantic Ocean high-pressure, south of South Africa, driving an abundance of southeast moisture fluxes, from the southwest Indian Ocean into Zimbabwe. Due to the proximity of Zimbabwe to the Agulhas and Mozambique warm current, the activity of the ridging South Atlantic Ocean anticyclone is a dominant synoptic feature that favors above-average rainfall in Zimbabwe. Also, coupled with a weaker state of the Mascarene high, it is shown that a ridging South Atlantic Ocean high-pressure, south of South Africa, can be favorable for the southwest movement of tropical cyclones into the eastern coastal landmasses resulting in above-average rainfall in Zimbabwe. The driest CT is characterized by the northward track of the Southern Hemisphere mid-latitude cyclones leading to enhanced westerly fluxes in the southwest Indian Ocean, limiting moist southeast winds into Zimbabwe

Circulation pattern controls of wet days and dry days in Free State, South Africa

Atmospheric circulation is a vital process in the transport of heat, moisture, and pollutants around the globe. The variability of rainfall depends to some extent on the atmospheric circulation. This paper investigates synoptic situations in southern Africa that can be associated with wet days and dry days in Free State, South Africa, in addition to the underlying dynamics. Principal component analysis was applied to the T-mode matrix (variable is time series and observation is grid points at which the field was observed) of daily mean sea level pressure field from 1979 to 2018 in classifying the circulation patterns in southern Africa. 18 circulation types (CTs) were classified in the study region. From the linkage of the CTs to the observed rainfall data, from 11 stations in Free State, it was found that dominant austral winter and late austral autumn CTs have a higher probability of being associated with dry days in Free State. Dominant austral summer and late austral spring CTs were found to have a higher probability of being associated with wet days in Free State. Cyclonic/anti-cyclonic activity over the southwest Indian Ocean, explained to a good extent, the inter-seasonal variability of rainfall in Free State. The synoptic state associated with a stronger anti-cyclonic circulation at the western branch of the South Indian Ocean high-pressure, during austral summer, leading to enhanced low-level moisture transport by southeast winds was found to have the highest probability of being associated with above-average rainfall in most regions in Free State. On the other hand, the synoptic state associated with enhanced transport of cold dry air, by the extratropical westerlies, was found to have the highest probability of being associated with (winter) dryness in Free State.Julius-Maximilians-Universität Würzburg (3088)https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interimhttp://www.dwa.gov.za/Hydrology/Verified/hymain.asp

Patterns of atmospheric circulation in Western Europe linked to heavy rainfall in Germany: preliminary analysis into the 2021 heavy rainfall episode

The July 2021 heavy rainfall episode in parts of Western Europe caused devastating floods, specifically in Germany. This study examines circulation types (CTs) linked to extreme precipitation in Germany. It was investigated if the classified CTs can highlight the anomaly in synoptic patterns that contributed to the unusual July 2021 heavy rainfall in Germany. The North Atlantic Oscillation was found to be the major climatic mode related to the seasonal and inter-annual variations of most of the classified CTs. On average, wet (dry) conditions in large parts of Germany can be linked to westerly (northerly) moisture fluxes. During spring and summer seasons, the mid-latitude cyclone when located over the North Sea disrupts onshore moisture transport from the North Atlantic Ocean by westerlies driven by the North Atlantic subtropical anticyclone. The CT found to have the highest probability of being associated with above-average rainfall in large part of Germany features (i) enhancement and northward track of the cyclonic system over the Mediterranean; (ii) northward track of the North Atlantic anticyclone, further displacing poleward, the mid-latitude cyclone over the North Sea, enabling band of westerly moisture fluxes to penetrate Germany; (iii) cyclonic system over the Baltic Sea coupled with northeast fluxes of moisture to Germany; (iv) and unstable atmospheric conditions over Germany. In 2021, a spike was detected in the amplitude and frequency of occurrence of the aforementioned wet CT suggesting that in addition to the nearly stationary cut-off low over central Europe, during the July flood episode, anomalies in the CT contributed to the heavy rainfall event

Circulation patterns linked to the positive sub-tropical Indian Ocean dipole

The positive phase of the subtropical Indian Ocean dipole (SIOD) is one of the climatic modes in the subtropical southern Indian Ocean that influences the austral summer inter-annual rainfall variability in parts of southern Africa. This paper examines austral summer rain-bearing circulation types (CTs) in Africa south of the equator that are related to the positive SIOD and the dynamics through which specific rainfall regions in southern Africa can be influenced by this relationship. Four austral summer rain-bearing CTs were obtained. Among the four CTs, the CT that featured (i) enhanced cyclonic activity in the southwest Indian Ocean; (ii) positive widespread rainfall anomaly in the southwest Indian Ocean; and (iii) low-level convergence of moisture fluxes from the tropical South Atlantic Ocean, tropical Indian Ocean, and the southwest Indian Ocean, over the south-central landmass of Africa, was found to be related to the positive SIOD climatic mode. The relationship also implies that positive SIOD can be expected to increase the amplitude and frequency of occurrence of the aforementioned CT. The linkage between the CT related to the positive SIOD and austral summer homogeneous regions of rainfall anomalies in Africa south of the equator showed that it is the principal CT that is related to the inter-annual rainfall variability of the south-central regions of Africa, where the SIOD is already known to significantly influence its rainfall variability. Hence, through the large-scale patterns of atmospheric circulation associated with the CT, the SIOD can influence the spatial distribution and intensity of rainfall over the preferred landmass through enhanced moisture convergence

Large‐scale forcing over the homogeneous regions of summer rainfall anomalies in southern Africa

Abstract For the study region (southern Africa), regional and remote large‐scale climate forcing play vital roles in the seasonal rainfall variability. Thus, uncovering the nature of the relationship between large‐scale circulations and homogeneous regions of rainfall anomalies will enhance the predictability of seasonal rainfall at specific domains in southern Africa. Considering both land and adjacent oceans in southern Africa, six austral summer homogeneous regions of rainfall anomalies were classified using the rotated principal component analysis. The analysis of the physical processes associated with the modulation of the distinct rainfall variability patterns reveals that generally, regional variations in cyclonic/anticyclonic circulations and convergence/divergence in the adjacent oceans (and landmasses) modulate the regional convergence of moisture fluxes in southern Africa. Some classified rainfall variability patterns feature homogeneous landmasses that are contiguous with the adjacent ocean, revealing land and adjacent oceans that respond coherently to the large‐scale circulation anomalies associated with the time development of the rainfall variability pattern. Further, remote climate drivers were found to be distinctively related to the regionalized rainfall anomalies, implying that the respective homogeneous rainfall regions respond differently to the large‐scale forcing induced by the (remote) climate drivers over southern Africa. Specifically, among the climate drivers that influence the hydroclimate of southern Africa, variations in the Southern Annular Mode (SAM) and the El Niño Southern Oscillation are relatively more associated with regionalized summer rainfall anomalies in southern Africa. Above‐average Nino 3.4 index (i.e., El Niño) negatively correlates with regionalized summer rainfall anomalies over large parts of southern Africa. The positive phase of the SAM positively correlates with rainfall anomaly in the homogeneous summer rainfall region comprising the subtropical parts of southern Africa and the homogeneous summer rainfall region comprising the western equatorial parts of the study region

Circulation pattern controls of wet days and dry days in Free State, South Africa

Atmospheric circulation is a vital process in the transport of heat, moisture, and pollutants around the globe. The variability of rainfall depends to some extent on the atmospheric circulation. This paper investigates synoptic situations in southern Africa that can be associated with wet days and dry days in Free State, South Africa, in addition to the underlying dynamics. Principal component analysis was applied to the T-mode matrix (variable is time series and observation is grid points at which the field was observed) of daily mean sea level pressure field from 1979 to 2018 in classifying the circulation patterns in southern Africa. 18 circulation types (CTs) were classified in the study region. From the linkage of the CTs to the observed rainfall data, from 11 stations in Free State, it was found that dominant austral winter and late austral autumn CTs have a higher probability of being associated with dry days in Free State. Dominant austral summer and late austral spring CTs were found to have a higher probability of being associated with wet days in Free State. Cyclonic/anti-cyclonic activity over the southwest Indian Ocean, explained to a good extent, the inter-seasonal variability of rainfall in Free State. The synoptic state associated with a stronger anti-cyclonic circulation at the western branch of the South Indian Ocean high-pressure, during austral summer, leading to enhanced low-level moisture transport by southeast winds was found to have the highest probability of being associated with above-average rainfall in most regions in Free State. On the other hand, the synoptic state associated with enhanced transport of cold dry air, by the extratropical westerlies, was found to have the highest probability of being associated with (winter) dryness in Free State

Exploring non-linear modes of the subtropical Indian Ocean Dipole using autoencoder neural networks

The subtropical Indian Ocean Dipole (SIOD) significantly influences climate variability, predominantly within parts of the Southern Hemisphere. This study applies an autoencoder—a type of artificial neural network (ANN)—known for its ability to capture intricate non-linear relationships in data through the process of encoding and decoding—to analyze the spatiotemporal characteristics of the SIOD. The encoded SIOD pattern(s) is compared to the conventional definition of the SIOD, calculated as the sea surface temperature (SST) anomaly difference between the western and eastern subtropical Indian Ocean. The analysis reveals two encoded patterns consistent with the conventional SIOD structure, predominantly represented by the SST dipole pattern south of Madagascar and off Australia’s west coast. During different analysis periods, distinct variability in the global SST patterns associated with the SIOD was observed. This variability underscores the SIOD’s dynamic nature and the challenges of accurately defining modes of variability with limited records. One of the ANN patterns has a substantial congruence match of 0.92 with the conventional SIOD pattern, while the other represents an alternate non-linear pattern within the SIOD. This implies the potential existence of additional non-linear SIOD patterns in the subtropical Indian Ocean, complementing the traditional model. When global temperature and precipitation are regressed onto the ANN temporal patterns and the conventional SIOD index, both appear to be associated with anomalous climate conditions over parts of Australia, with several other consistent global impacts. Nevertheless, due to the non-linear nature of the ANN patterns, their effects on local temperature and precipitation vary across different regions as compared to the conventional SIOD index. This study highlights that while the conventional SIOD pattern is consistent with the ANN-derived SIOD pattern, the climate system’s complexity and non-linearity might require ANN modeling to advance our comprehension of climatic modes

Bias-Korrektur des Klimamodell-Outputs für Deutschland

Regional climate models (RCMs) are tools used to project future climate change at a regional scale. Despite their high horizontal resolution, RCMs are characterized by systematic biases relative to observations, which can result in unrealistic interpretations of future climate change signals. On the other hand, bias correction (BC) is a popular statistical post-processing technique applied to improve the usability of output from climate models. Like every other statistical technique, BC has its strengths and weaknesses. Hence, within the regional context of Germany, and for temperature and precipitation, this study is dedicated to the assessment of the impact of different BC techniques on the RCM output. The focuses are on the impact of BC on the RCM’s statistical characterization, and physical consistency defined as the spatiotemporal consistency between the bias-corrected variable and the simulated physical mechanisms governing the variable, as well as the correlations between the bias-corrected variable and other (simulated) climate variables. Five BC techniques were applied in adjusting the systematic biases in temperature and precipitation RCM outputs. The BC techniques are linear scaling, empirical quantile mapping, univariate quantile delta mapping, multivariate quantile delta mapping that considers inter-site dependencies, and multivariate quantile delta mapping that considers inter-variable dependencies (MBCn). The results show that each BC technique adds value in reducing the biases in the statistics of the RCM output, though the added value depends on several factors such as the temporal resolution of the data, choice of RCM, climate variable, region, and the metric used in evaluating the BC technique. Further, the raw RCMs reproduced portions of the observed modes of atmospheric circulation in Western Europe, and the observed temperature, and precipitation meteorological patterns in Germany. After the BC, generally, the spatiotemporal configurations of the simulated meteorological patterns as well as the governing large-scale mechanisms were reproduced. However, at a more localized spatial scale for the individual meteorological patterns, the BC changed the simulated co-variability of some grids, especially for precipitation. Concerning the co-variability among the variables, a physically interpretable positive correlation was found between temperature and precipitation during boreal winter in both models and observations. For most grid boxes in the study domain and on average, the BC techniques that do not adjust inter-variable dependency did not notably change the simulated correlations between the climate variables. However, depending on the grid box, the (univariate) BC techniques tend to degrade the simulated temporal correlations between temperature and precipitation. Further, MBCn which adjusts biases in inter-variable dependency has the skill to improve the correlations between the simulated variables towards observations.Regionale Klimamodelle (RCMs) sind Werkzeuge, die verwendet werden, um den zukünftigen Klimawandel auf regionaler Ebene zu prognostizieren. Trotz ihrer hohen horizontalen Auflösung sind RCMs je nach Beobachtung durch systematische Verzerrungen gekennzeichnet, was zu unrealistischen Interpretationen zukünftiger Signale des Klimawandels führen kann. Andererseits ist die Bias-Korrektur (BC) eine beliebte statistische Nachbearbeitungstechnik, die angewendet wird, um die Nutzbarkeit der Ergebnisse von Klimamodellen zu verbessern. Wie jede andere statistische Technik hat BC seine Stärken und Schwächen. Daher widmet sich diese Studie im regionalen Kontext Deutschlands und für Temperatur und Niederschlag der Bewertung der Auswirkungen verschiedener BC-Techniken auf den das RCM-ErtragErgebnis. Die Schwerpunkte liegen auf der Auswirkung von BC auf die statistische Charakterisierung des RCM und auf der physikalischen Konsistenz. Letztere ist, definiert als die räumlich-zeitliche Konsistenz zwischen der systematisch korrigierten Variablen und den simulierten physikalischen Mechanismen, die diese Variable steuern, sowie auf den Korrelationen zwischen der systematisch korrigierten Variablen und anderen (simulierten) Klimavariablen. Fünf BC-Techniken wurden angewendet, um die systematischen Abweichungen in den Temperatur- und Niederschlags-RCM-Ausgaben Ergebnissen anzupassen. Die BC-Techniken sind lineare Skalierung, empirisches Quantil-Mapping, univariates Quantil-Delta-Mapping, sowie multivariates Quantil-Delta-Mapping, das Abhängigkeiten zwischen Standorten berücksichtigt, und multivariates Quantil-Delta-Mapping, das intervariable Abhängigkeiten (MBCn) berücksichtigt. Die Ergebnisse zeigen, dass jede BC-Technik einen Mehrwert bei der Reduzierung der Verzerrungen in den Statistiken der RCM-Ausgabe bringt, und dies, obwohl der Mehrwert von mehreren Faktoren abhängt, wie der zeitlichen Auflösung der Daten, der Wahl der RCM, der Klimavariable, der Region und desr verwendeten Massstabsetrik zur Bewertung der BC-Technik verwendet. Darüber hinaus reproduzierten die rohen RCMs Teile der beobachteten Modi der atmosphärischen Zirkulation in Westeuropa und die beobachteten meteorologischen Temperatur- und Niederschlagsmuster in Deutschland. Nach der BC wurden im Allgemeinen die raumzeitlichen Konfigurationen der simulierten meteorologischen Muster sowie die maßgeblichen großräumigen Mechanismen reproduziert. Auf einer stärker lokalisierten räumlichen Skala änderte der BC jedoch für die einzelnen meteorologischen Muster die simulierte Kovariabilität einiger Gitter, insbesondere für Niederschlag. Bezüglich der Kovariabilität zwischen den Variablen wurde sowohl in Modellen als auch in Beobachtungen eine physikalisch interpretierbare positive Korrelation zwischen Temperatur und Niederschlag im borealen Winter gefunden. Für die meisten Gitterboxen Gitterfelder im Untersuchungsbereich und auch im Durchschnitt änderten die BC-Techniken, die die Abhängigkeit zwischen den Variablen nicht anpassen, die simulierten Korrelationen zwischen den Klimavariablen nicht merklich. Allerdings neigen die (univariaten) BC-Techniken je nach Gitterbox Gitterfeld dazu, die simulierten zeitlichen Korrelationen zwischen Temperatur und Niederschlag zu verschlechtern. Darüber hinaus hat MBCn, das Verzerrungen in der Abhängigkeit zwischen Variablen anpasst, die Fähigkeit, die Korrelationen zwischen den simulierten Variablen gegenüber den Beobachtungen zu verbessern

On the Relationship between Circulation Patterns, the Southern Annular Mode, and Rainfall Variability in Western Cape

This study investigates circulation types (CTs) in Africa, south of the equator, that are related to wet and dry conditions in the Western Cape, the statistical relationship between the selected CTs and the Southern Annular Mode (SAM), and changes in the frequency of occurrence of the CTs related to the SAM under the ssp585 scenario. Obliquely rotated principal component analysis applied to sea level pressure (SLP) was used to classify CTs in Africa, south of the equator. Three CTs were found to have a high probability of being associated with wet days in the Western Cape, and four CTs were equally found to have a high probability of being associated with dry days in the Western Cape. Generally, the dry/wet CTs feature the southward/northward track of the mid-latitude cyclone, adjacent to South Africa; anti-cyclonic/cyclonic relative vorticity, and poleward/equatorward track of westerlies, south of South Africa. One of the selected wet CTs was significantly related to variations of the SAM. Years with an above-average SAM index correlated with the below-average frequency of occurrences of the wet CT. The results suggest that through the dynamics of the CT, the SAM might control the rainfall variability of the Western Cape. Under the ssp585 scenario, the analyzed climate models indicated a possible decrease in the frequency of occurrence of the aforementioned wet CT associated with cyclonic activity in the mid-latitudes, and an increase in the frequency of the occurrence of CT associated with enhanced SLP at mid-latitudes

Revisiting the 1992 severe drought episode in South Africa: the role of El Niño in the anomalies of atmospheric circulation types in Africa south of the equator

During strong El Niño events, below-average rainfall is expected in large parts of southern Africa. The 1992 El Niño season was associated with one of the worst drought episodes in large parts of South Africa. Using reanalysis data set from NCEP-NCAR, this study examined circulation types (CTs) in Africa south of the equator that are statistically related to the El Niño signal in the southwest Indian Ocean and the implication of this relationship during the 1992 drought episode in South Africa. A statistically significant correlation was found between the above-average Nino 3.4 index and a CT that features widespread cyclonic activity in the tropical southwest Indian Ocean, coupled with a weaker state of the south Indian Ocean high-pressure. During the analysis period, it was found that the El Niño signal enhanced the amplitude of the aforementioned CT. The impacts of the El Niño signal on CTs in southern Africa, which could have contributed to the 1992 severe drought episode in South Africa, were reflected in (i) robust decrease in the frequency of occurrence of the austral summer climatology pattern of atmospheric circulation that favors southeasterly moisture fluxes, advected by the South Indian Ocean high-pressure; (ii) modulation of easterly moisture fluxes, advected by the South Atlantic Ocean high-pressure, ridging south of South Africa; (iii) and enhancement of the amplitude of CTs that both enhances subsidence over South Africa, and associated with the dominance of westerlies across the Agulhas current. Under the ssp585 scenario, the analyzed climate models suggested that the impact of radiative heating on the CT significantly related to El Niño might result in an anomalous increase in surface pressure at the eastern parts of South Africa