Mid-summer Drought Research Articles

Exploring the utility of the Enhanced Vegetation Index as rainfall and agricultural proxy in a Caribbean case study event

Highly fragile small island states experience disproportionate climate impacts given their limited capacity to implement cost‐effective tools for detecting emerging signals of drying conditions and monitoring systems for sensitive sectors such as agriculture, especially for uncertain, ‘creeping’ events such as droughts. Despite the existence of open‐source Google Earth Engine datasets, untapped potential remains for their full deployment in disaster management infrastructure. Given this gap, this paper explores the utility of the Enhanced Vegetation Index (EVI) for detecting spatio‐temporal variations of Mid‐Summer Drought (MSD) impacts on vegetation in the small island of Jamaica, with emphasis on major historical drought events. Geospatial analyses of EVI datasets from the Terra Moderate‐Resolution Imaging Spectroradiometer (MODIS) between 2000−2015 archived by the United States Geological Survey (USGS), were computed, and validated by station‐based precipitation and production data for selected parishes for historical case study MSD events. Results revealed highly asymmetrical drought impacts, with Jamaica's agriculturally intense Southern coastline displaying the most stressed vegetation (EVI < 0.5). North‐Western and North‐Eastern regions had the healthiest vegetation during the MSD (EVI > 0.6). A ‘fair’ to ‘moderate’ concurrent correlation was found between EVI and precipitation (R > 0.6), with lower correlations vis‐a‐vis agricultural production (R = 0.2–0.4). The results provide evidence of EVI's utility as a drought monitoring tool in a small island context.

Upwelling-induced inflow pulses in a tropical bay during mid-summer drought

Bahía Santa Elena is a tropical bay located in the northern Pacific region of Costa Rica. This region experiences a period of reduced precipitation from July to August, known as mid-summer drought, induced by the intensification of northeastern winds from the Caribbean Low-Level Jet. Intensification of upwelling-favorable winds can cool surface waters adjacent to the bay, leading to a reduction in water temperatures within the bay, that alters the biological dynamics of coastal habitats. This study aims to analyze upwelling-induced inflow pulses in Bahía Santa Elena during mid-summer drought, focusing on the cooling effect of intensified upwelling-favorable winds and the subsequent warm water inflows following wind relaxation. We conducted two measuring campaigns from June to July in 2021 and in 2022. The first campaign consisted of a single acoustic Doppler current profiler (ADCP) moored inside the bay. The second campaign consisted of two mooring deployments: an ADCP with a thermistor chain inside the bay and an ADCP installed at the inlet. Each campaign presented five distinct events of upwelled water inflows into the bay promoted by an offshore Ekman transport. Upwelling-favorable wind peaks were followed by a decrease in temperature of the water column. When the upwelling-favorable wind relaxed, a warm water pulse entered the bay. These events are expected to play an important role in biological processes within tropical bays adjacent to upwelling zones during mid-summer drought.

Historical meteorological droughts over the CORDEX‐CAM (Central America, Caribbean and Mexico) domain: Evaluating the simulation of dry hot spots with RegCM4

AbstractHistorical meteorological droughts are analysed over the Coordinated Regional Downscaling Experiment‐Central America, Caribbean and Mexico (CORDEX‐CAM) domain during 1981–2010, with particular emphasis on the North American monsoon (NAM) and the mid‐summer drought (MSD) regions. We analyse droughts based on the standardized precipitation index (SPI‐12) and the standardized precipitation‐evapotranspiration index (SPEI‐12) using observations from CRU, CHIRPS, GPCP and ERA5‐Land reanalysis (ERA5), and assess the skill of the regional climate model RegCM4 (version 7) at 25 km resolution driven by ERA‐Interim (Reg‐ERA) and by three global climate models (Reg‐GCMs: Reg‐Had, Reg‐MPI and Reg‐GFDL). Observational data sets show large spatial variations in drought frequency, and both Reg‐ERA and Reg‐GCMs have difficulties simulating it. RegCM4 shows positive precipitation and water balance biases over mountain regions and negative ones over Central America, possibly due to the complex terrain and poor observational data coverage. Despite differences among observations, the trend in droughts, duration and severity show consistent dry hot spots (regions with long‐duration severe droughts) over the western United States, the United States‐Mexico border region, the NAM, the Yucatan Peninsula and northern Central America, with stronger values of SPEI‐12 than SPI‐12, particularly over the subtropical regions. Reg‐ERA and ERA5 show similar spatial patterns and similar positive and negative spatial biases relative to observations. Reg‐ERA and Reg‐Had adequately simulate the spatial patterns of the trend, duration and severity of droughts, with smaller biases in SPI‐12 than SPEI‐12; in contrast, Reg‐MPI and Reg‐GFDL overestimate the trend biases over northwest CAM. Observations, reanalysis, and RegCM4 capture an inverse drought response between the NAM and the MSD regions linked to climate teleconnections; however, a stronger drought signal is observed in the NAM, which appears to be linked to decadal variations from negative to positive phases of the Atlantic Multidecadal Oscillation combined with La Niña conditions (negative El Niño 1+2 phase).

Weather types for the seasonal transitions in Central America

Unsupervised learning techniques are employed to study the relationship between atmospheric circulation and precipitation over Central America and its surrounding areas. Specifically, the clustering algorithm k-means++ is applied to three coarse-grained datasets from ERA-interim reanalysis that are the candidates for representing the atmospheric state vector, each candidate contains its full temporal variability. Datasets are composed of: a) wind fields at 925, 800 and 200 hPa, b) same as “a)” plus convective available potential energy and c) same as “a)” plus total column water vapor. Clustering metrics, namely the variance ratio criterion, the silhouette criterion and the mean squared error, are computed to quantify clustering quality. Clusters are interpreted as weather types, recurrent configurations of the atmospheric state vector associated with observable weather states. The correct number of clusters for each dataset is determined with a Monte Carlo test of normality, to assure cluster existence. The main objective is to obtain a set of weather types containing elements that characterize the transition from and to the rainy season over the Pacific side of Central America as well as other elements of the seasonal cycle of regional precipitation, such as the Mid-Summer Drought. Besides the statistical metrics, in order to select between candidate datasets and plausible number of clusters, focus is given to the temporal characteristics of the clusters. Existing literature does not provide a set of weather types suitable to analyze seasonal transitions and the differences in the mechanisms associated with rainfall maxima.

Climatic characteristics of precipitation change and its multiscale causes over Central Qinghai–Tibet Plateau

AbstractRegional climates have changed as a result of global warming, which has sped up cirrus circulation and altered the temporal and spatial distribution of precipitation. As climate change intensifies, the pattern of precipitation in the Hoh Xil (HX) region has changed. The dislocation of rain and heat in summer hinders ecological restoration and brings great ecological threat. And it is important to clarify the causes and scopes of the midsummer drought (MSD). In this study we highlight the causes of MSD in terms of water vapour transport, circulation structure and the related influencing factors. We found that (1) the HX region gradually entered a drying‐warming process as MSD developed after 2005. (2) The change in the water vapour balance is the direct cause of MSD in the HX. (3) As a typical climate key zone, the HX is located in the transition region between the westerlies and the Indian monsoon. (4) Regional evaporation capacity is the main factor affecting the occurrence of MSD. The dominant factor shifted from being energy to water with the occurrence and enhancement of MSD. This study complements the scarce research on precipitation anomalies in the HX, provides support for clarifying the impact of climate change on the Qinghai–Tibet Plateau (TP) and contributes to understanding the trends and mechanisms of climate change over the TP under global warming.

Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica

Rainfall in Guanacaste, Costa Rica, has marked wet/dry phases: the rainy season is punctuated by a short midsummer drought, and the dry season frequently has months of no rain. In this region, spring and summer rainfall peaks are important for local rain-fed agriculture and annual total for groundwater recharge and hydroelectricity production. We propose a novel model of rainfall in this region, the double-Gaussian model, which uses monthly total rainfall data collected from 1980 to 2020 from two meteorological observation stations. Our model provides an intuitive way of describing the seasonality of rainfall, the inter-annual variability of the cycle, and variability due to the monthly Oceanic Niño Index, ONI. We also consider two alternative models, a regression model with ARMA errors and a Tweedie model, as a means of assessing the robustness of our conclusions to violations of the assumptions of the double-Gaussian model. We found that the data provide strong evidence of an increase/decrease in rainfall in both temporal maxima during La Niña/El Niño (negative/positive ONI) conditions but no evidence of a decade-scale trend after accounting for ONI effects. Finally, we investigated the problem of forecasting future rainfall based on our three models. We found that when ONI is incorporated as a predictor variable, our models can produce substantial gains in prediction accuracy of spring, summer, and annual totals over naive methods based on monthly sample means or medians.

Hydrological Response of Tropical Catchments to Climate Change as Modeled by the GR2M Model: A Case Study in Costa Rica

This study aimed to assess the impacts of climate change on streamflow characteristics of five tropical catchments located in Costa Rica. An ensemble of five General Circulation Models (GCMs), namely HadGEM2-ES, CanESM2, EC-EARTH, MIROC5, MPI-ESM-LR dynamically downscaled by two Regional Climate Models (RCMs), specifically HadRM3P and RCA4, was selected to provide an overview of the impacts of different climate change scenarios under Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 using the 1961–1990 baseline period. The GR2M hydrological model was used to reproduce the historical monthly surface runoff patterns of each catchment. Following calibration and validation of the GRM2 model, the projected impact of climate change on streamflow was simulated for a near-future (2011–2040), mid-future (2041–2070) and far-future (2071–2100) for each catchment using the bias-corrected GCM-RCM multimodel ensemble-mean (MEM). Results anticipate wetter conditions for all catchments in the near-future and mid-future periods under RCPs 2.6 and 4.5, whereas dryer conditions are expected for the far-future period under RCP 8.5. Projected temperature trends indicate consistently warmer conditions with increasing radiative forcing and future periods. Streamflow changes across all catchments however are dominated by variations in projected precipitation. Wetter conditions for the near-future and mid-future horizons under RCPs 2.6 and 4.5 would result in higher runoff volumes, particularly during the late wet season (LWS). Conversely, dryer conditions for the far-future period under RCP8.5 would result in considerably lower runoff volumes during the early wet season (EWS) and the Mid-Summer Drought (MSD). In consequence, projected seasonal changes on streamflow across all catchments may result in more frequent flooding, droughts, and water supply shortage compared to historical hydrological regimes.

Signatures of midsummer droughts over Central America and Mexico

The annual cycle of precipitation over most parts of Central America and southern Mexico is climatologically characterized by a robust bimodal distribution, normally termed as the midsummer drought (MSD), influencing a large range of agricultural economic and public insurances. Compared to studies focusing on mechanisms underpinning the MSD, less research has been undertaken related to its climatological signatures. This is due to a lack of generally accepted methods through which to detect and quantify the bimodal precipitation accurately. The present study focuses on characterizing the MSD climatological signatures over Central America and Mexico using daily precipitation observations between 1979 and 2017, aiming to provide a comprehensive analysis of MSD in fine scale over this region. This was completed using a new method of detection. The signatures were analyzed from three aspects, namely (1) climatological mean states and variability; (2) connections with large scale modes of climate variability (El Niño–Southern Oscillation (ENSO) and the Madden–Julian Oscillation (MJO)); and (3) the potential afforded by statistical modelling. The development of MSDs across the region is attributed to changes of surface wind–pressure composites, characterized by anomalously negative (positive) surface pressure and onshore (offshore) winds during the peak (trough) of precipitation. ENSO’s modulation of MSDs is also shown by modifying the surface wind–pressure patterns through MSD periods, inducing the intensified North Atlantic Subtropical High and associated easterlies from the Caribbean region, which induce relatively weak precipitation at corresponding time points and subsequently intensify the MSD magnitude and extend the MSD period. Building on previous research which showed MSDs tend to start/end in MJO phases 1 and 8, a fourth–order polynomial was used here to statistically model the precipitation time series during the rainy season. We show that the strength of the bimodal precipitation can be well modelled by the coefficient of the polynomial terms, and the intra-seasonal variability is largely covered by the MJO indices. Using two complete MJO cycles and the polynomial, the bimodal precipitation during the rainy season over Central America and Mexico is synoptically explained, largely contributing to our understanding of the MJO’s modulation on the MSD.

Effect of the Trans‐Volcanic Axis on meridional propagation of summer precipitation in western Mexico

AbstractThe Trans‐Volcanic Axis (TVA)—comprising ridges and terrain elevations above 1,900 m—strongly affects meridional propagation of summer precipitation in western Mexico. This barrier modifies atmospheric moisture content and changes the annual precipitation cycle configuration, which distinguishes it from the precipitation cycle on both sides of the TVA. Using upper‐air observations and rainfall records, this study demonstrates that the TVA is the region where the North American monsoon (NAM) and the mid‐summer drought (MSD) influence intersections regarding precipitation. This region affects both northward extent of double precipitation maxima with the MSD and the southward extent of the NAM single precipitation peak. This study proposes that the forcing mechanism that controls the annual precipitation cycle in the TVA region relies on latent heat loss via ground cooling by reducing air temperature below dewpoint temperature in the 700–500 hPa layer, consistent with local terrain elevations. The orographic effect increases specific humidity in the atmospheric column—sufficiently large to enhance local precipitation accumulation—resulting in a mid‐summer drought intensity decline but not enough to yield a single peak in precipitation. Consequently, the TVA becomes an uncategorized region that does not display the NAM nor the characteristic features of the MSD.

Atmospheric circulation types controlling rainfall in the Central American Isthmus

AbstractRainfall mechanisms in the Central American Isthmus are controlled by complex physical interactions across spatial and temporal scales, which are reflected on the dynamics of atmospheric circulation patterns affecting the region. However, physical mechanisms and their relationships with thermodynamic distributions connected to overturning circulations remain elusive. Here, a set of six recurrent daily atmospheric patterns, or weather types (WT), is defined using a k‐means++ clustering algorithm on standardized fields of Convective Available Potential Energy (CAPE) and winds at 925, 850, and 200 hPa. The relationships between these weather types, their temporal characteristics, and anomalous distributions of moisture flux divergence, equivalent potential temperature (saturated and unsaturated), and observed rainfall are used to describe physical processes controlling the latter, for all seasons. Regional observed rainfall is analysed from a set of 174 automatic stations from all countries from Mexico to Panama. By modulating vertically integrated moisture fluxes, these weather types, and the different climate drivers linked to them, control the temporal and spatial rainfall characteristics in the region, especially over the Pacific side of the isthmus. During some stages of the regional rainy season, described by two weather types, thermal anomalies in convective quasi‐equilibrium characteristic of the upward branch of the Hadley cell force westerly flow over Central America, enhancing rainfall. While during other stages, the enhancement of the trades and the displacement of convection to the ITCZ area over the eastern tropical Pacific, characteristic of the midsummer drought, diminishes rainfall. This study sets the stage for a better understanding of the mechanistic relationship between these weather types and rainfall characteristics in general, like onset, demise, and duration of rainy seasons. Hence, these results can inform process‐based model diagnostics aiming at bias‐correcting climate predictions at multiple timescales.

Seasonal prediction of the Caribbean rainfall cycle

Rainfall in the Caribbean is an important resource for numerous stakeholders in the region. Based on previous work, which identified several variables that could provide predictive skill of rainfall in the region, canonical correlation analysis is applied to assess forecast skill for station-averaged sub-regional frequency and intensity of the Early-Rainy Season (ERS) and Late-Rainy Season (LRS) wet days, and magnitude of the Mid-Summer Drought (MSD). Predictor fields are explored from the ERA-Interim and North American Multi-Model Ensemble (NMME). The use of sea-level pressure (SLP), 850 hPa zonal winds (u850), vertically integrated zonal (UQ), and meridional (VQ) moisture fluxes show comparable, if not better, forecast skill than sea-surface temperatures (SSTs), which is generally the commonly-used predictor in a given region’s seasonal climate forecasts. Generally, the highest predictive skill is found for the frequency of wet days. Rainfall characteristics in the Central and Eastern Caribbean have significant predictive skill. Forecast skill of rainfall characteristics in the Northwestern and Western Caribbean are lower and less consistent. The sub-regional differences and consistently significant skill across lead times up to at least two months can be attributed to persistent SST/SLP anomalies during the ERS that resemble the North Atlantic Oscillation, and that resembles the summer-time onset of the El Niño-Southern Oscillation during the LRS. The anomalous spatial patterns during the MSD bear resemblance to both the ERS and LRS signals. The results provide additional variables that can be used to forecast rainfall characteristics in the Caribbean and a way to tailor seasonal forecasts for each sub-region.

Revisiting mechanisms of the Mesoamerican Midsummer drought

Observations show that the seasonal cycle of precipitation in parts of southern Mexico and Central America exhibits a bimodal signal, known as the Midsummer drought (MSD), but there is no consensus on which processes are most relevant for the two-peak structure of the rainy season. This paper evaluates three hypotheses that could explain the MSD: the SST cloud-radiative feedback, the solar declination angle and the Caribbean Low-Level Jet (CLLJ) moisture transport hypotheses. Model experiments produced by the Met Office Hadley Centre (MOHC) for CMIP6 as well as ERA5 reanalysis data are used to critically assess the predictions of each hypothesis. The simulations capture the double peak signal of precipitation well and reasonably simulate the spatial and temporal variations of the MSD and other relevant climate features such as the CLLJ. Evidence from our analysis suggests that the Eastern Pacific SSTs do not increase in late summer in ERA5 data and only slightly increase in the simulations. More importantly, the Eastern Pacific SST variability in ERA5 and in the model experiments cannot explain the differences in the seasonality of precipitation. The net shortwave radiation at the surface shows a two-peak seasonal cycle; however, this behaviour appears to result from a strong anti-correlation of the incoming shortwave and convective activity due to cloud radiative-effects. There was no evidence found by this study of a causal link in which absorption of shortwave energy forces precipitation variations, as suggested by the solar declination angle hypothesis. The moisture convergence, CLLJ and the precipitable water vapor variations best explain the characteristics of the observed and simulated MSD, particularly for the onset of the MSD. The diagnosed variations of moisture convergence, which are synchronous with the timing of the MSD, point to a dynamic mechanism in which the low-level inflow from the Caribbean is more important for the MSD than other radiative mechanisms.

The effect of sea surface temperature and deforestation on the mid‐summer drought over Mexico and Central America

AbstractWe analyse the effects of deforestation and the projected differential sea surface temperature (SST) anomalies between the tropical North Atlantic and the eastern North Pacific on the mid‐summer drought (MSD) over southern Mexico and Central America. To address these issues, we performed a set of three 6‐year (1996–2001) sensitivity experiments with RegCM4 driven by the ERA‐Interim reanalysis and employing different SST (projected end of century patterns under the RCP8.5 scenario) and vegetation (turning forest landuse into grass) configurations. The model domain follows the specifications of the COrdinated Regional Downscaling EXperiment (CORDEX) for Central America. Results indicate that projected SST patterns cause the MSD signal to almost disappear from the regional mean annual cycle, with its spatial extent decreasing from ~82 to ~48%. In the vegetation sensitivity experiment, the MSD intensity increases along the Pacific coast and Central America, while the MSD spatial extent remains almost unchanged. These regional changes in MSD can be explained in terms of the regional precipitation response to deforestation, primarily due to changes in vertical moisture advection.

The climatic interdependence of extreme-rainfall events around the globe.

The identification of regions of similar climatological behavior can be utilized for the discovery of spatial relationships over long-range scales, including teleconnections. Additionally, it provides insights for the improvement of corresponding interaction processes in general circulation models. In this regard, the global picture of the interdependence patterns of extreme-rainfall events (EREs) still needs to be further explored. To this end, we propose a top-down complex-network-based clustering workflow, with the combination of consensus clustering and mutual correspondences. Consensus clustering provides a reliable community structure under each dataset, while mutual correspondences build a matching relationship between different community structures obtained from different datasets. This approach ensures the robustness of the identified structures when multiple datasets are available. By applying it simultaneously to two satellite-derived precipitation datasets, we identify consistent synchronized structures of EREs around the globe, during boreal summer. Two of them show independent spatiotemporal characteristics, uncovering the primary compositions of different monsoon systems. They explicitly manifest the primary intraseasonal variability in the context of the global monsoon, in particular, the "monsoon jump" over both East Asia and West Africa and the mid-summer drought over Central America and southern Mexico. Through a case study related to the Asian summer monsoon, we verify that the intraseasonal changes of upper-level atmospheric conditions are preserved by significant connections within the global synchronization structure. Our work advances network-based clustering methodology for (i) decoding the spatiotemporal configuration of interdependence patterns of natural variability and for (ii) the intercomparison of these patterns, especially regarding their spatial distributions over different datasets.

The Mesoamerican mid-summer drought: the impact of its definition on occurrences and recent changes

Abstract. The mid-summer drought, veranillo or canícula, is a phenomenon experienced in many areas, including Mexico, Central America, and the Caribbean. It generally is experienced as reduced rainfall in July–August, in the middle of the typical rainy season (May–September). Many past studies have attempted to quantify changes in mid-summer drought characteristics during the recent past or for future climate projections. To do this, objective definitions of a mid-summer drought's occurrence, strength, and duration have been developed by many researchers. In this effort we adopt a recent set of definitions and examine the impact of varying these on the characterization of mid-summer droughts and the detected changes over the past 4 decades. We find the selection of a minimum intensity threshold has a dramatic effect on the results of both the area considered as experiencing a mid-summer drought and the changes detected in the recent historical record. The intensity chosen can affect both the magnitude and direction of changes reported in the recent observed record. Further, we find that the typical mid-summer drought pattern may not be occurring during the time it has historically; whether examining past or future changes or developing improved seasonal forecasts, the non-stationarity of its timing should be accommodated.

An adaptive approach to quantify weather-within-climate rainfall characteristics

Knowledge of subseasonal-to-seasonal (S2S) rainfall characteristics such as onset, duration, and demise of the rainfall cycle, and characteristics of dry periods that are between rainfall seasons, can provide important insight for the agriculture, health, disaster, and energy industries. Several methods have attempted to calculate temporal characteristics of rainfall and few have worked with intermittent dry periods and calculate intermittent dry period characteristics. Issues arise when applying these methods for complex rainfall regimes, or regions that have one or more of the following: (1) multiple rainfall seasons in a given year, (2) a relatively wet dry season, (3) unclear transitions between wet and dry seasons. This study develops a new and comprehensive method for calculating S2S rainfall characteristics, especially for regions that have complex annual rainfall cycles. The method consists of three steps: (1) create the annual cycle climatology of rainfall and classify its modality by the presence or absence of intermittent dry period(s), (2) identify seasonal windows of the rainfall cycle based on its climatological modality, (3) calculate yearly intermittent dry period characteristics and calculate temporal rainfall characteristics for each year using information on daily rainfall amount and the concurrent rate of change. Application and results of the method are given for the Caribbean, which exhibits the properties of a region with complex rainfall regimes. The method can be utilized under a meteorological or agronomical lens and is able to delineate false meteorological and agronomical onsets and demises. Meteorological onsets and demises that are calculated via each year’s Early-Rainy Season (ERS) and Late-Rainy Season (LRS) mean thresholds effectively characterize the seasonal evolution of mean onsets and demises in the Caribbean. The year-to-year variability of Mid-Summer Drought (MSD) characteristics, and onsets and demises that are calculated by climatological ERS and LRS mean thresholds resemble the variability of seasonal rainfall totals in the Caribbean and are statistically significantly correlated with the identified dynamical processes that impact each seasonal component of the rainfall cycle. The method has important implications for prediction, modeling capabilities, and understanding the variability of rainfall across timescales.

Potential Influence of the Atlantic Multidecadal Oscillation in the Recent Climate of a Small Basin in Central Mexico

One of the main current challenges is detecting changes in the climate at the regional level. The present study tried to address this issue by looking for some influence of large-scale climate oscillations on the climate of a small and complex topography basin in Central Mexico. We collected temperature and precipitation data from 44 climate stations within an area of up to 20 km around the Apatlaco River sub-basin (~30 km south of Mexico City) during the period 1950–2013. Posteriorly, quality analysis and homogenization of the climate databases were performed by using the Climatol algorithm. We analyzed the trend of five ETCCDI climate indices through several statistical tests. Finally, we calculated simple Pearson correlations of those indices with four climate oscillation indices that have affected Mexico’s climate in the recent past. The results revealed that the Atlantic Multidecadal Oscillation had a clear influence on four of the five indices analyzed in the study area. The summer days and the extreme maximum and minimum temperatures accounted for a small increase in the temperature of the middle east (urban) basin compared to the middle west (rural), which could be a manifestation of the heat island effect or the difference in soil type (and therefore albedo) of the two zones. As expected, the midsummer drought effect predominated in most of the sub-basin, with only the uppermost part showing monsoon-type precipitation during a typical year.

A high resolution coupled ocean-atmosphere simulation of the regional climate over Central America

This study analyzes a relatively high resolution (15 km grid spacing), regional coupled ocean–atmosphere simulation configured over Central America. The simulation is conducted with the Regional Spectral Model-Regional Ocean Model System (RSM-ROMS) forced with global atmospheric and oceanic reanalysis for a period of 25 years (1986–2010). The spatial resolution of the RSM-ROMS simulation is unprecedented for the region. The highlights of the RCM simulation include the verifiable seasonal cycle of mesoscale features like the Low-Level Jets (LLJs), the Mid-Summer Drought (MSD), and the seasonal Tropical Cyclone (TC) activity both in the Pacific and in the Atlantic Oceans. However, some of the biases of the RSM-ROMS simulation of the frequency and amplitude of the MSD, the track density of the TCs in the two ocean basins, and the seasonal bias of the LLJs are noted. The seasonal cycle of the robust surface ocean currents in the eastern Pacific and the Costa Rica Dome is also well captured in the RSM-ROMS simulation. The RSM-ROMS simulation also resolves the seasonal cycle of the cyclonic Panama-Colombia Gyre and the anti-cyclonic Gulf of Papagayo-Tehuantepec Gyre. In many instances we find the RSM-ROMS improves upon the global reanalysis forcing the simulation, indicating the potential value of dynamic downscaling. Furthermore, the co-evolving components of the atmosphere and ocean in the RCM is an added benefit to the atmosphere only and ocean only global reanalysis forcing the simulation. However, the RCM displays significant biases that manifest in precipitation, precipitable water, SST, and winds which in the cases of prognostic variables of RSM-ROMS are perpetrated by the biases in the lateral boundary forcing (e.g., precipitable water) and in other instances forced by biases within the RSM-ROMS (e.g., precipitation, SST).

Sensitivity of precipitation and atmospheric low-level circulation patterns to domain size and choice of parameterization schemes in RegCM4.4 over Central America

The sensitivity of regional climate model simulations to domain size and position is becoming increasingly important for generating reliable climate scenarios. In this study, the Central America CORDEX domain (CCA) at 50 km horizontal resolution with a relaxation zone of 10° around the boundaries (CCA+) was taken as the basis to increase domain size in the RegCM4.4 model. The low-level circulation and precipitation patterns over Central America, the western Caribbean Sea, and the eastern tropical Pacific do not show strong sensitivity to domain size changes for an area increment of 18, 32, and 52% with respect to the size of CCA+. The physical configuration in RegCM4.4 has a greater impact on the representation of relevant climate characteristics and atmospheric processes. Simulated 925 hPa winds over the Caribbean low-level jet (CLLJ) region show unrealistic winter and summer intensities, especially in July. Similar issues were found in other studies for the CCA domain, using different models and physical configurations. A reduction of the critical Richardson number in the selected planetary boundary layer scheme resulted in little change in the strength of the summer component of the CLLJ. The model simulations do not completely capture key regional precipitation patterns such as the mid-summer drought, due to limitations in adequately representing low-level circulation. However, simulations using the Grell cumulus parameterization perform relatively better than those using a mixed scheme (Grell over land-Emanuel over ocean).

A wavelet transform method to determine monsoon onset and retreat from precipitation time‐series

AbstractA new method to determine monsoon onset and retreat timings using wavelet transform methodology applied to precipitation time‐series at the pentad scale is described. The principal advantage of this method is its portability, since it can be easily adapted for any region and dataset. The application of the method is illustrated for the North American Monsoon and the Indian Monsoon using four different precipitation datasets and climate model output. The method is shown to be robust across all the datasets and both monsoon regions. The mean onset and retreat dates agree well with previous methods. Spatial distributions of the precipitation and circulation anomalies identified around the onset and retreat dates are also consistent with previous work and illustrate that this method may be used at the grid‐box scale, not just over large area‐averaged regions. The method is also used to characterize the strength and timing of the Midsummer drought (MSD) in southern Mexico and Central America. A two peak structure is found to be a robust structure in only in 33% of the years, with other years showing only one peak or no signs of a bimodal distribution. The two‐peak structure analysed at the grid‐box scale is shown to be a significant signal in several regions of Central America and southern Mexico. The methodology is also applied to climate model output from the Met Office Hadley Centre UKESM1 and HadGEM3 CMIP6 experiments. The modelled onset and retreat dates agree well with observations in the North American Monsoon but not in the Indian Monsoon. The start and end of the modelled MSD in southern Mexico and Central America is delayed by one pentad and has a stronger bimodal signal than observed.