Reanalysis Sea Level Pressure Research Articles

Spatiotemporal changes and background atmospheric factors associated with forest fires in Turkiye.

In this study, spatiotemporal analysis of forest fires in Turkiye was undertaken, with a specific focus on the large-scale atmospheric systems responsible for causing these fires. For this purpose, long-term variations in forest fires were classified based on the occurrence types (i.e. natural/lightning, negligence/inattention, arson, accident, unknown). The role of large-scale atmospheric circulations causing natural originated forest fires was investigated using NCEP/NCAR Reanalysis sea level pressure, and surface wind products for the selected episodes. According to the main results, Mediterranean (MeR), Aegean (AR), and Marmara (MR) regions of Turkiye are highly susceptible to forest fires. Statistically significant number of forest fires in the MeR and MR regions are associated with global warming trend of the Eastern Mediterranean Basin. In monthly distribution, forest fires frequently occur in the MeR part of Turkiye during September, August, and June months, respectively, and heat waves are responsible for forest fires in 2021. As a consequence of the extending summer Asiatic monsoon to the inner parts of Turkiye and the location of Azores surface high over Balkan Peninsula result in atmospheric blocking and associated calm weather conditions in the MeR (e.g. Mugla and Antalya provinces). When this blocking continues for a long time, southerly winds on the back slopes of the Taurus Mountains create a foehn effect, calm weather conditions and lack of moisture in the soil of Antalya and Mugla settlements trigger the formation of forest fires.

Exploring the limits of the Jenkinson–Collison weather types classification scheme: a global assessment based on various reanalyses

The Jenkinson–Collison weather typing scheme (JC-WT) is an automated method used to classify regional sea-level pressure into a reduced number of typical recurrent patterns. Originally developed for the British Isles in the early 1970’s on the basis of expert knowledge, the method since then has seen many applications. Encouraged by the premise that the JC-WT approach can in principle be applied to any mid-to-high latitude region, the present study explores its global extra-tropical applicability, including the Southern Hemisphere. To this aim, JC-WT is applied at each grid-box of a global 2.5^{circ } regular grid excluding the inner tropics (± 5^{circ } band). Thereby, 6-hourly JC-WT catalogues are obtained for 5 distinct reanalyses, covering the period 1979–2005, which are then applied to explore (1) the limits of method applicability and (2) observational uncertainties inherent to the reanalysis datasets. Using evaluation criteria, such as the diversity of occurring circulation types and the frequency of unclassified situations, we extract empirically derived applicability thresholds which suggest that JC-WT can be generally used anywhere polewards of 23.5^{circ }, with some exceptions. Seasonal fluctuations compromise this finding along the equatorward limits of the domain. Furthermore, unreliable reanalysis sea-level pressure estimates in elevated areas with complex orography (such as the Tibetan Plateau, the Andes, Greenland and Antarctica) prevent the application of the method in these regions. In some other regions, the JC-WT classifications obtained from the distinct reanalyses substantially differ from each other, which may bring additional uncertainties when the method is used in model evaluation experiments.

Arctic Cyclone Activity and the Beaufort High

AbstractThe Beaufort high (BH) and its accompanying anticyclonic winds drive the Arctic Ocean’s Beaufort Gyre, the major freshwater reservoir of the Arctic Ocean. The Beaufort Gyre circulation and its capacity to accumulate or release freshwater rely on the BH intensity. The migration of Nordic seas cyclones into the Arctic has been hypothesized to moderate the strength of the BH. We explore this hypothesis by analyzing reanalysis sea level pressure fields to characterize the BH and identify and track cyclones north of 60°N during 1948–2019. A cluster analysis of Nordic seas cyclone trajectories reveals a western pathway (through the Arctic interior) associated with a relatively weak BH and an eastern pathway (along the Arctic periphery) associated with a relatively strong BH. Furthermore, we construct cyclone activity indices (CAIs) in the Arctic and Nordic seas that take into account multiple cyclone parameters (number, strength, and duration). There are significant correlations between the BH and the CAIs in the Arctic and Nordic seas during 1948–2019, with anomalously strong cyclone activity related to an anomalously weak BH, and vice versa. We show how the Arctic and Nordic seas CAIs experienced a regime shift toward increased cyclone activity between the first four decades analyzed (1948–88) and the most recent three decades (1989–2019). Over the same two time periods, the BH exhibits a weakening. Increased cyclone activity and an accompanying weakening of the BH may be consistent with expectations in a warming Arctic and have implications for Beaufort Gyre dynamics and freshwater.

Dynamics and predictability of cold spells over the Eastern Mediterranean

The accurate prediction of extreme weather events is an important and challenging task, and has typically relied on numerical simulations of the atmosphere. Here, we combine insights from numerical forecasts with recent developments in dynamical systems theory, which describe atmospheric states in terms of their persistence (θ−1) and local dimension (d), and inform on how the atmosphere evolves to and from a given state of interest. These metrics are intuitively linked to the intrinsic predictability of the atmosphere: a highly persistent, low-dimensional state will be more predictable than a low-persistence, high-dimensional one. We argue that θ−1 and d, derived from reanalysis sea level pressure (SLP) and geopotential height (Z500) fields, can provide complementary predictive information for mid-latitude extreme weather events. Specifically, signatures of regional extreme weather events might be reflected in the dynamical systems metrics, even when the actual extreme is not well-simulated in numerical forecasting systems. We focus on cold spells in the Eastern Mediterranean, and particularly those associated with snow cover in Jerusalem. These rare events are systematically associated with Cyprus Lows, which are the dominant rain-bearing weather system in the region. In our analysis, we compare the ‘cold spell Cyprus Lows’ to other ‘regular’ Cyprus Low days. Significant differences are found between cold spells and ‘regular’ Cyprus Lows from a dynamical systems perspective. When considering SLP, the intrinsic predictability of cold spells is lowest hours before the onset of snow. We find that the cyclone’s location, depth and magnitude of air-sea fluxes play an important role in determining its intrinsic predictability. The dynamical systems metrics computed on Z500 display a different temporal evolution to their SLP counterparts, highlighting the different characteristics of the atmospheric flow at the different levels. We conclude that the dynamical systems approach, although sometimes challenging to interpret, can complement conventional numerical forecasts and forecast skill measures, such as model spread and absolute error. This methodology outlines an important avenue for future research, which can potentially be fruitfully applied to other regions and other types of weather extremes.

Physical-empirical models for prediction of seasonal rainfall extremes of Peninsular Malaysia

Abstract Reliable prediction of rainfall extremes is vital for disaster management, particularly in the context of increasing rainfall extremes due to global climate change. Physical-empirical models have been developed in this study using three widely used Machine Learning (ML) methods namely, Support Vector Machines (SVM), Random Forests (RF), Bayesian Artificial Neural Networks (BANN) for the prediction of rainfall and rainfall related extremes during Northeast Monsoon (NEM) in Peninsular Malaysia from synoptic predictors. The gridded daily rainfall data of Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) was used to estimate four rainfall indices namely, rainfall amount, average rainfall intensity, days having >95-th percentile rainfall, and total number of dry days in Peninsular Malaysia during NEM for the period 1951–2015. The National Centers for Environmental Prediction (NCEP) reanalysis sea level pressure (SLP) data was used for the prediction of rainfall indices with different lead periods. The recursive feature elimination (RFE) method was used to select the SLP at different NCEP grid points which were found significantly correlated with NEM rainfall indices. The results showed superior performance of BANN among the ML models with normalised root mean square error of 0.04–0.14, Nash-Sutcliff Efficiency of 0.98–1.0, and modified agreement index of 0.97–0.99 and Kling-Gupta efficient index 0.65–0.96 for one-month lead period prediction. The 95% confidence interval (CI) band for BANN was found narrower than the other ML models. Almost all the forecasted values by BANN were also found with 95% CI, and therefore, the p-factor and the r-factor for BANN in predicting rainfall indices were found in the range of 0.95–1.0 and 0.25–0.49 respectively. Application of BANN in prediction of rainfall indices with higher lead time was also found excellent. The synoptic pattern revealed that SLP over the north of South China Sea is the major driver of NEM rainfall and rainfall extremes in Peninsular Malaysia.

Evaluation and Postprocessing of Ensemble Fire Weather Predictions over the Northeast United States

AbstractThe Short-Range Ensemble Forecast (SREF) system is verified and bias corrected for fire weather days (FWDs) defined as having an elevated probability of wildfire occurrence using a statistical Fire Weather Index (FWI) over a subdomain of the northeastern United States (NEUS) between 2007 and 2014. The SREF is compared to the Rapid Update Cycle and Rapid Refresh analyses for temperature, relative humidity, specific humidity, and the FWI. An additive bias correction is employed using the most recent previous 14 days [sequential bias correction (SBC)] and the most recent previous 14 FWDs [conditional bias correction (CBC)]. Synoptic weather regimes on FWDs are established using cluster analysis (CA) on North American Regional Reanalysis sea level pressure, 850-hPa temperature, 500-hPa temperature, and 500-hPa geopotential height. SREF severely underpredicts FWI (by two indices at FWI = 3) on FWDs, which is partially corrected using SBC and largely corrected with CBC. FWI underprediction is associated with a cool (ensemble mean error of −1.8 K) and wet near-surface model bias (ensemble mean error of 0.46 g kg−1) that decreases to near zero above 800 hPa. Although CBC improves reliability and Brier skill scores on FWDs, ensemble FWI values exhibit underdispersion. CA reveals three synoptic weather regimes on FWDs, with the largest cool and wet biases associated with a departing surface low pressure system. These results suggest the potential benefit of an operational analog bias correction on FWDs. Furthermore, CA may help elucidate model error during certain synoptic weather regimes.

Incorporating circulation statistics in bias correction of GCM ensembles: hydrological application for the Rhine basin

An adapted statistical bias correction method is introduced to incorporate circulation-dependence of the model precipitation bias, and its influence on estimated discharges for the Rhine basin is analyzed for a historical period. The bias correction method is tailored to time scales relevant to flooding events in the basin. Large-scale circulation patterns (CPs) are obtained through Maximum Covariance Analysis using reanalysis sea level pressure and high-resolution precipitation observations. A bias correction using these CPs is applied to winter and summer separately, acknowledging the seasonal variability of the circulation regimes in North Europe and their correlation with regional precipitation rates over the Rhine basin. Two different climate model ensemble outputs are explored: ESSENCE and CMIP5. The results of the CP-method are then compared to observations and uncorrected model outputs. Results from a simple bias correction based on a delta factor (NoCP-method) are also used for comparison. For both summer and winter, the CP-method offers a statistically significant improvement of precipitation statistics for subsets of data dominated by particular circulation regimes, demonstrating the circulation-dependence of the precipitation bias. Uncorrected, CP and NoCP corrected model outputs were used as forcing to a hydrological model to simulate river discharges. The CP-method leads to a larger improvement in simulated discharge in the Alpine area in winter than in summer due to a stronger dependence of Rhine precipitation on atmospheric circulation in winter. However, the NoCP-method, in comparison to the CP-method, improves the discharge estimations over the entire Rhine basin.

Multi-scale variability patterns in NCEP/NCAR reanalysis sea-level pressure

Atmospheric pressure varies within a wide range of scales and thus a multi-scale description of its variability is particularly appealing. In this study, a scale-by-scale analysis of the global sea-level pressure field is carried out from reanalysis data. Wavelet-based analysis of variance is applied in order to describe the variability of the pressure field in terms of patterns representing the contribution of each scale to the overall variance. Signals at the seasonal scales account for the largest fraction of sea-level pressure variance (typically more than 60%) except in the Southern Ocean, in the Equatorial Pacific and in the North Atlantic. In the Southern Ocean and over the North Atlantic, high-frequency signals contribute to a considerable fraction (30–50%) of the overall variance in sea-level pressure. In the Equatorial Pacific, large-scale variability, associated with ENSO, contributes up to 40% of the total variance.

Climatology of Cyclone Size Characteristics and Their Changes during the Cyclone Life Cycle

Abstract Climatology of the atmospheric cyclone sizes and their change over the cyclone life cycle is analyzed on the basis of tracking 57 yr of NCEP–NCAR reanalysis sea level pressure data over the Northern Hemisphere. To quantify the atmospheric cyclone sizes a coordinate transform was used, which allows for the collocation of the cyclone center with the virtual pole and for the establishment of a unique coordinate system for the further determination of cyclone geometry. This procedure was incorporated into a numerical cyclone tracking scheme and provided quantitative estimation of cyclone geometry at every stage of the cyclone development. Climatological features of the distribution of the cyclone size characteristics (effective radius, asymmetry) are considered for the cyclones with different central pressure, deepening rate, and lifetime. Mean effective cyclone radius may experience significant changes, ranging from 300–400 km over the continents to more than 900 km over the oceans. There is found to be a strong dependence of the cyclone effective radius on the cyclone lifetime and intensity, implying the largest cyclone sizes for the most intense and long-living transients. Analysis of size changes during the cyclone life cycle implies that the cyclone radius increases during the development stage from 50% to 150%. Size evolution during the cyclone life cycle implies a universal dependence of the normalized cyclone effective radius and the normalized cyclone age. The actual maximum cyclone radius can be determined from these two nondimensional parameters and cyclone central pressure. Further application of the analysis of cyclone size and shape are discussed.

Evidence of deceleration of atmospheric vertical overturning circulation over the tropical Pacific

Analyses of ship‐based measurements of sea level pressure reveal a systematic weakening of the horizontal pressure gradient across the Pacific in the last fifty years. This reduction is also present in the NCAR/NCEP and ECMWF reanalysis sea level pressure products. The magnitude is estimated to be between 2% to 13%. This weakening is consistent with simulations from general circulation models when sea‐surface temperatures are uniformly raised. It is also consistent with reductions of the large‐scale subsidence over the eastern Pacific in the models. Since the reduction of vertical overturning circulation in the models can be explained through fundamental thermodynamic constraints on the atmospheric circulation, we postulate that the weakening of the sea‐level pressure gradient is an intrinsic characteristic of the tropical atmosphere in a warmer climate, and the observed trend in the sea‐level pressure provides an indirect evidence of the reduction of atmospheric vertical overturning circulation in the tropical Pacific. It is also pointed out that the weakening of the vertical overturning circulation does not mean the weakening of the hydrological cycle.

A cyclone statistics for the Arctic based on European Centrere-analysis data

Based on the six-hourly re-analysis sea-level pressure data of the European Centre for Medium-Range Weather Forecast (ECMWF) a cyclone statistics for the Arctic region north of 60° is elaborated for the period 1 November 1986 to 31 October 1991. For each low pressure center on a weather map its location, central pressure and horizontal pressure gradients in E, W, N, and S direction are determined. Furthermore, cyclone centers are followed with time to calculate trajectories, pressure tendencies, and lifetimes. A horizontal grid of 300 km × 300 km is used as unit area for the statistical computations. A unit area experiences about 20 cyclone passages per year (range 5–40). On the average, six cyclones occur simultaneously in the Arctic region. Lifetimes vary from 6 h to 15 days. The annual cyclone activity over the 5-year period is nearly the same. Cyclones are more frequent in summer (about 94 per month) than in winter (77 per month). In general summer cyclones are weaker than winter cyclones. On the average, the minimum central pressure during the lifetime of a cyclone is about 1000 hPa (typical range 980–1020) in summer and about 988 hPa (typical range 940–1030) in winter. In winter, a zone of high cyclone frequency extends from the region near Iceland over the Greenland Sea, Barents Sea, and Kara Sea to the Laptev Sea while the interior of the Arctic shows little cyclone frequency. In summer, the region near Iceland and the interior of the Arctic are separate centers of high cyclone frequency. Both in winter and summer very high cyclone frequencies are observed over the northern Baffin Bay. The regional distribution of mean central pressures and maximum pressure gradients roughly follows the distribution of cyclone frequencies except for the Baffin Bay cyclones which are generally weak. Cyclolysis dominates cyclogenesis over largest parts of the Arctic. Regions of high cyclone frequency are also regions of frequent cyclogenesis and frequent cyclolysis. One third of all cyclones is generated in a region with an already existing cyclonic circulation. Cyclones in the Fram Strait are studied in more detail because of their special impact on the ice export from the Arctic Ocean to the Atlantic Ocean. On the average, there are 5 cyclones per month. the cyclone frequency in the Fram Strait is higher during the winter period than during the summer period. This is in contrast to the overall Arctic frequency which is higher in summer than in winter. Cyclogenesis predominates in winter and cyclolysis in summer in the Fram Strait. The most frequent direction of motion is from SW to NE.

The 1997–98 El Niño Evolution Relative to Previous El Niño Events

The evolution of the 1997–98 El Niño is described using NCEP SST and OLR data, NCEP–NCAR reanalysis sea level pressure (SLP) fields, and The Florida State University surface wind data. From November 1996 to January 1997, the eastern Pacific is characterized by equatorial cold SST and high SLP anomalies, while the western Pacific is marked by off-equatorial warm SST anomalies and off-equatorial anomalous cyclones. Corresponding to this distribution are high OLR anomalies in the equatorial central Pacific and low OLR anomalies in the off-equatorial far western Pacific. The off-equatorial anomalous cyclones in the western Pacific are associated with a switch in the equatorial wind anomalies over the western Pacific from easterly to westerly. These equatorial westerly anomalies then appear to initiate early SST warmings around the date line in January/February 1997 and around the far eastern Pacific in March 1997. Subsequently, both the westerly wind and warm SST anomalies, along with the low OLR anomalies, grow and progress eastward. The eastward propagating warm SST anomalies merge with the slower westward spreading warm SST anomalies from the far eastern Pacific to form large-scale warming in the equatorial eastern and central Pacific. The anomaly patterns in the eastern and central Pacific continue to develop, reaching their peak values around December 1997. In the western Pacific, the off-equatorial SST anomalies reverse sign from warm to cold. Correspondingly, the off-equatorial SLP anomalies in the western Pacific also switch sign from low to high. These off-equatorial high SLP anomalies initiate equatorial easterly wind anomalies over the far western Pacific. Like the equatorial westerly wind anomalies that initiate the early warming, the equatorial easterly wind anomalies over the far western Pacific appear to have a cooling effect in the east and hence help facilitate the 1997–98 El Niño decay. This paper also compares the 1997–98 El Niño with previous warm events and discusses different ENSO mechanisms relevant to the 1997–98 El Niño.