ENSO and precipitation variability over Mexico during the last 90 years

Latin America has been shown to be susceptible to climatic anomalies during El Niño/Southern Oscillation (ENSO) events (eg, Aceituno 1988; Ropelewshi and Halpert 1987; Kiladis and Diaz 1989). While these studies have emphasized ENSO-related rainfall and temperature anomalies over Central and South America, less work has been done on the climatic effects of ENSO over the Mexican region. In this study we are investigating interannual and intraseasonal fluctuation in temperature and precipitation over the southwestern United States and Mexico since the turn of the century. We are particularly interested in the effects of ENSO on the interannual variability over this region. This report focuses on the association between ENSO and interannual variability of precipitation over Mexico

A Python Package to Calculate the OLR-Based Index of the Madden- Julian-Oscillation (OMI) in Climate Science and Weather Forecasting

The Madden-Julian Oscillation (MJO) is a prominent feature of the intraseasonal variability of the atmosphere. The MJO strongly modulates tropical precipitation and has implications around the globe for weather, climate and basic atmospheric research. The time-dependent state of the MJO is described by MJO indices, which are calculated through sometimes complicated statistical approaches from meteorological variables. One of these indices is the OLR-based MJO Index (OMI; OLR stands for outgoing longwave radiation). The Python package mjoindices, which is described in this paper, provides the first open source implementation of the OMI algorithm, to our knowledge. The package meets state-of-the-art criteria for sustainable research software, like automated tests and a persistent archiving to aid the reproducibility of scientific results. The agreement of the OMI values calculated with this package and the original OMI values is also summarized here. There are several reuse scenarios; the most probable one is MJO-related research based on atmospheric models, since the index values have to be recalculated for each model run

Seasonality of African Precipitation from 1996 to 2009

Abstract A precipitation climatology of Africa is documented using 12 years of satellite-derived daily data from the Global Precipitation Climatology Project (GPCP). The focus is on examining spatial variations in the annual cycle and describing characteristics of the wet season(s) using a consistent, objective, and well-tested methodology. Onset is defined as occurring when daily precipitation consistently exceeds its local annual daily average and ends when precipitation systematically drops below that value. Wet season length, rate, and total are then determined. Much of Africa is characterized by a single summer wet season, with a well-defined onset and end, during which most precipitation falls. Exceptions to the single wet season regime occur mostly near the equator, where two wet periods are usually separated by a period of relatively modest precipitation. Another particularly interesting region is the semiarid to arid eastern Horn of Africa, where there are two short wet seasons separated by nearly dry periods. Chiefly, the summer monsoon spreads poleward from near the equator in both hemispheres, although in southern Africa the wet season progresses northwestward from the southeast coast. Composites relative to onset are constructed for selected points in West Africa and in the eastern Horn of Africa. In each case, onset is often preceded by the arrival of an eastward-propagating precipitation disturbance. Comparisons are made with the satellite-based Tropical Rainfall Measuring Mission (TRMM) and gauge-based Famine Early Warning System (FEWS NET) datasets. GPCP estimates are generally higher than TRMM in the wettest parts of Africa, but the timing of the annual cycle and average onset dates are largely consistent

North American monsoon and convectively coupled equatorial waves simulated by IPCC AR4 coupled GCMs

This study evaluates the fidelity of North American monsoon and associated intraseasonal variability in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general circulation models (CGCMs). Twenty years of monthly precipitation data from each of the 22 models' twentieth-century climate simulations, together with the available daily precipitation data from 12 of them, are analyzed and compared with Global Precipitation Climatology Project (GPCP) monthly and daily precipitation. The authors focus on the seasonal cycle and horizontal pattern of monsoon precipitation in conjunction with the two dominant convectively coupled equatorial wave modes: the eastward-propagating Madden-Julian oscillation (MJO) and the westward-propagating easterly waves. The results show that the IPCC AR4 CGCMs have significant problems and display a wide range of skill in simulating the North American monsoon and associated intraseasonal variability. Most of the models reproduce the monsoon rainbelt, extending from southeast to northwest, and its gradual northward shift in early summer, but overestimate the precipitation over the core monsoon region throughout the seasonal cycle and fail to reproduce the monsoon retreat in the fall. Additionally, most models simulate good westward propagation of the easterly waves, but relatively poor eastward propagation of the MJO and overly weak variances for both the easterly waves and the MJO. There is a tendency for models without undiluted updrafts in their deep convection scheme to produce better MJO propagation.open221

Seasonal cycle of precipitation variability in South America on intraseasonal timescales

The seasonal cycle of the intraseasonal (IS) variability of precipitation in South America is described through the analysis of bandpass filtered outgoing longwave radiation (OLR) anomalies. The analysis is discriminated between short (10--30 days) and long (30--90 days) intraseasonal timescales. The seasonal cycle of the 30--90-day IS variability can be well described by the activity of first leading pattern (EOF1) computed separately for the wet season (October--April) and the dry season (May--September). In agreement with previous works, the EOF1 spatial distribution during the wet season is that of a dipole with centers of actions in the South Atlantic Convergence Zone (SACZ) and southeastern South America (SESA), while during the dry season, only the last center is discernible. In both seasons, the pattern is highly influenced by the activity of the Madden--Julian Oscillation (MJO). Moreover, EOF1 is related with a tropical zonal-wavenumber-1 structure superposed with coherent wave trains extended along the South Pacific during the wet season, while during the dry season the wavenumber-1 structure is not observed. The 10--30-day IS variability of OLR in South America can be well represented by the activity of the EOF1 computed through considering all seasons together, a dipole but with the stronger center located over SESA. While the convection activity at the tropical band does not seem to influence its activity, there are evidences that the atmospheric variability at subtropical-extratropical regions might have a role. Subpolar wavetrains are observed in the Pacific throughout the year and less intense during DJF, while a path of wave energy dispersion along a subtropical wavetrain also characterizes the other seasons. Further work is needed to identify the sources of the 10--30-day-IS variability in South America

The Intricacies of Identifying Equatorial Waves

Equatorial waves (EWs) are synoptic- to planetary-scale propagating disturbances at low latitudes with periods from a few days to several weeks. Here, this term includes Kelvin waves, equatorial Rossby waves, mixed Rossby–gravity waves, and inertio-gravity waves, which are well described by linear wave theory, but it also other tropical disturbances such as easterly waves and the intraseasonal Madden–Julian Oscillation with more complex dynamics. EWs can couple with deep convection, leading to a substantial modulation of clouds and rainfall. EWs are amongst the dynamic features of the troposphere with the longest intrinsic predictability, and models are beginning to forecast them with an exploitable level of skill. Most of the methods developed to identify and objectively isolate EWs in observations and model fields rely on (or at least refer to) the adiabatic, frictionless linearized primitive equations on the sphere or the shallow-water system on the equatorial -plane. Common ingredients to these methods are zonal wave-number–frequency filtering (Fourier or wavelet) and/or projections onto predefined empirical or theoretical dynamical patterns. This paper gives an overview of six different methods to isolate EWs and their structures, discusses the underlying assumptions, evaluates the applicability to different problems, and provides a systematic comparison based on a case study (February 20–May 20, 2009) and a climatological analysis (2001–2018). In addition, the influence of different input fields (e.g., winds, geopotential, outgoing long-wave radiation, rainfall) is investigated. Based on the results, we generally recommend employing a combination of wave-number–frequency filtering and spatial-projection methods (and of different input fields) to check for robustness of the identified signal. In cases of disagreement, one needs to carefully investigate which assumptions made for the individual methods are most probably not fulfilled. This will help in choosing an approach optimally suited to a given problem at hand and avoid misinterpretation of the results

Subseasonal variability associated with Asian summer monsoon simulated by 14 IPCC AR4 coupled GCMs

This study evaluates the subseasonal variability associated with the Asian summer monsoon in 14 coupled general circulation models (GCMs) participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Eight years of each model's twentieth-century climate simulation are analyzed. The authors focus on the three major components of Asian summer monsoon: the Indian summer monsoon (ISM), the western North Pacific summer monsoon (WNPSM), and the East Asian summer monsoon (EASM), together with the two dominant subseasonal modes: the eastward- and northward-propagating boreal summer intraseasonal oscillation (BSIO) and the westward-propagating 12-24-day mode. The results show that current state-of-the-art GCMs still have difficulties and display a wide range of skill in simulating the subseasonal variability associated with Asian summer monsoon. During boreal summer (May-October), most of the models produce reasonable seasonal-mean precipitation over the ISM region, but excessive precipitation over the WNPSM region and insufficient precipitation over the EASM region. In other words, models concentrate their rain too close to the equator in the western Pacific. Most of the models simulate overly weak total subseasonal (2-128 day) variance, as well as too little variance for BSIO and the 12-24-day mode. Only 4-5 models produce spectral peaks in the BSIO and 12-24-day frequency bands; instead, most of the models display too red a spectrum, that is, an overly strong persistence of precipitation. For the seven models with three-dimensional data available, five reproduce the preconditioning of moisture in BSIO but often with a too late starting time, and only three simulate the phase lead of low-level convergence. Interestingly, although models often have difficulty in simulating the eastward propagation of BSIO, they tend to simulate well the northward propagation of BSIO, together with the westward propagation of the 12-24-day mode. The northward propagation in these models is thus not simply a NW-SE-tilted tail protruding off of an eastward-moving deep-tropical intraseasonal oscillation.open444