Regional Atmospheric Modeling Research Articles

Impact of the extremely warm Gulf Stream on heavy precipitation induced by Hurricane Sandy (2012) during its extratropical transition

This study investigated the role of the extremely warm sea surface temperature (EWSST) over the Gulf Stream (GS) in heavy precipitation induced by Hurricane Sandy in October 2012 during its extratropical transition (ET). A control (CTL) run with observed SST and a climate (CLM) run with climatological SST over the GS were performed using a high-resolution regional atmospheric model. Sandy-induced precipitation over the Mid-Atlantic coastal region was larger by approximately 40% in the CTL run than in the CLM run during its ET phase. The western sector of Sandy in the CTL run exhibited the westward-tilting lower-to-middle tropospheric front and the pronounced convectively unstable layer created by large surface fluxes of sensible and latent heat from the EWSST region. The intensified convective instability was released by the frontal deep updrafts, enhancing frontal precipitation in the western part of Sandy. A backward trajectory analysis demonstrated that the abundant moisture evaporated from the GS was imported into the western frontal rainbands by the low-level easterlies passing the northern sector of Sandy. The EWSST facilitated the moistening process of air parcels transported by the easterlies due to the active heat and moisture supply from the underlying current, contributing to the increase in moisture influx toward the western front. Another trajectory analysis indicated that the formation of low-level easterlies north of Sandy originated from the combination of Sandy and high-latitude synoptic-scale systems such as an anomalous high over the Labrador Sea and an extratropical cyclone east of Sandy. These results corroborate the importance of the extremely warm midlatitude ocean and complex high-latitude weather systems to the enhancement of Sandy-induced heavy precipitation.

Sea2Cloud: From Biogenic Emission Fluxes to Cloud Properties in the Southwest Pacific

Abstract The goal of the Sea2Cloud project is to study the interplay between surface ocean biogeochemical and physical properties, fluxes to the atmosphere, and ultimately their impact on cloud formation under minimal direct anthropogenic influence. Here we present an interdisciplinary approach, combining atmospheric physics and chemistry with marine biogeochemistry, during a voyage between 41° and 47°S in March 2020. In parallel to ambient measurements of atmospheric composition and seawater biogeochemical properties, we describe semicontrolled experiments to characterize nascent sea spray properties and nucleation from gas-phase biogenic emissions. The experimental framework for studying the impact of the predicted evolution of ozone concentration in the Southern Hemisphere is also detailed. After describing the experimental strategy, we present the oceanic and meteorological context including provisional results on atmospheric thermodynamics, composition, and flux measurements. In situ measurements and flux studies were carried out on different biological communities by sampling surface seawater from subantarctic, subtropical, and frontal water masses. Air–Sea-Interface Tanks (ASIT) were used to quantify biogenic emissions of trace gases under realistic environmental conditions, with nucleation observed in association with biogenic seawater emissions. Sea spray continuously generated produced sea spray fluxes of 34% of organic matter by mass, of which 4% particles had fluorescent properties, and which size distribution resembled the one found in clean sectors of the Southern Ocean. The goal of Sea2Cloud is to generate realistic parameterizations of emission flux dependences of trace gases and nucleation precursors, sea spray, cloud condensation nuclei, and ice nuclei using seawater biogeochemistry, for implementation in regional atmospheric models.

Comparison between the Operational and Statistical Daily Maximum and Minimum Temperature Forecasts on the Central Coast of Peru

Abstract Multiple linear regression models were developed for 1–3-day lead forecasts of maximum and minimum temperature for two locations in the city of Lima, on the central coast of Peru (12°S), and contrasted with the operational forecasts issued by the National Meteorological and Hydrological Service—SENAMHI and the output of a regional numerical atmospheric model. We developed empirical models, fitted to data from the 2000–13 period, and verified their skill for the 2014–19 period. Since El Niño produces a strong low-frequency signal, the models focus on the high-frequency weather and subseasonal variability (60-day cutoff). The empirical models outperformed the operational forecasts and the numerical model. For instance, the high-frequency annual correlation coefficient and root-mean-square error (RMSE) for the 1-day lead forecasts were 0.37°–0.53° and 0.74°–1.76°C for the empirical model, respectively, but from around −0.05° to 0.24° and 0.88°–4.21°C in the operational case. Only three predictors were considered for the models, including persistence and large-scale atmospheric indices. Contrary to our belief, the model skill was lowest for the austral winter (June–August), when the extratropical influence is largest, suggesting an enhanced role of local effects. Including local specific humidity as a predictor for minimum temperature at the inland location substantially increased the skill and reduced its seasonality. There were cases in which both the operational and empirical forecast had similar strong errors and we suggest mesoscale circulations, such as the low-level cyclonic vortex over the ocean, as the culprit. Incorporating such information could be valuable for improving the forecasts. Significance Statement We wanted to compare the temperature of the operational forecast of the Meteorological and Hydrological Service, an atmospheric model, and persistence with the observed temperatures on the Peruvian central coast. In addition, we generated an empirical forecast model considering both atmospheric and local predictors. We got better results with this empirical model, considering the highest Pearson correlations and the lowest RMSE values. These results will allow us to use this empirical model as the main tool to automate the forecast on the central coast of Peru. Future work should be aimed at testing the skill of this model for forecasting in other cities of Peru.

A Comparative Study Between Regional Atmospheric Model Simulations Coupled and Uncoupled to a Regional Ocean Model of the Indian Summer Monsoon

AbstractWe evaluate the impact of air‐sea coupling in simulating the characteristics of the Indian summer monsoon (ISM) and its intraseasonal oscillations (ISOs) by using a coupled ocean‐atmosphere regional climate model (CRSM) and an atmosphere‐only regional climate model (URSM). These 20‐km resolution regional climate models (RCMs) were driven by the boundary conditions from Community Climate System Model version 4 (CCSM4) global model. The mean ISM rainfall simulated by URSM and CRSM is comparable with observations and shows an improvement over the CCSM4. The systematic error in the spatial distribution of the mean June–September low‐level and upper‐level winds, sea surface temperature, and latent heat flux shows that CRSM performs better than URSM, suggesting the benefits of air‐sea coupling in the RCM simulations of the mean ISM. Both the CRSM and the URSM perform reasonably and comparably in capturing the spatiotemporal evolution of 10–20‐day high‐frequency and 20–70‐day low‐frequency ISOs of the ISM rainfall. These RCMs simulated the observed features of the ISO‐filtered rainfall anomalies that propagate at a faster rate across the Arabian Sea compared to that over the Bay of Bengal. Furthermore, the difference in the track density of the monsoon low‐pressure systems between the wet and the dry phases of ISOs shows insignificant differences between CRSM and URSM but is found to be superior to the CCSM4 simulation. This study suggests a relative insensitivity of air‐sea coupling in the RCM for simulating ISO and LPS features of ISM, which is likely abetted by the realistic ISO signals in the parent CCSM4.

Signals of northward propagating monsoon intraseasonal oscillations (MISOs) in the RegCM4.7 CORDEX-CORE simulation over South Asia domain

Northward propagating summer monsoon intraseasonal oscillations (MISOs) in the Indian Ocean region remain poorly understood and difficult to predict. Here we examine a free-running high-resolution regional atmospheric model (RegCM4.7 with 25 km resolution), forced distantly at the boundaries by atmospheric observations (ERA-Interim, 0.75 $$^{\circ }$$ ) and forced locally by observed sea-surface temperature (SST) over the period 1979–2016, to assess its ability to reproduce key aspects of these MISOs. We find that the model MISO exhibits spatial structures and northward propagation characteristics broadly similar to observed MISO when confining the analysis to the 25–90 day period band. The MISO precipitation anomalies are then shown to be consistent with previously known observed relationships to broad-scale sea-level pressure patterns, Inter-Tropical Convergence Zone (ITCZ) positioning, and changes in the regional Hadley Cell component. The total simulated seasonal (JJAS) rainfall anomalies over India are not significantly correlated with observations, indicating that intrinsic variations in the regional model atmosphere dominate most of the precipitation variability. However, the bandpass-filtered MISO anomalies surprisingly exhibit a significant correlation (0.61) with observations. This suggests that instabilities in the regional broad-scale atmospheric circulation, e.g., linked to the ITCZ position or strength, may be partly controlled by the large-scale atmospheric flows specified at the domain boundaries and/or that specified local SST anomalies may help to guide some fraction of the developing model MISO to follow observations. This result motivates further research on MISO initiation and development using this type of regional atmospheric model.

Evaluation of Western North Pacific Typhoon Track Forecasts in Global and Regional Models during the 2021 Typhoon Season

The track forecasts of tropical cyclones (TC) in the western North Pacific (WNP) basin during 2021 typhoon season with five global models and four regional models are evaluated here. The results show that the average direct position errors (DPEs) of the global and regional models are approximately 80, 150, 200, 300, and 400 km at 24 h, 48 h, 72 h, 96 h, and 120 h lead-times, respectively. The European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) achieved the best track forecast performance at each lead among the five global models. Among the four regional models, The China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) attained the smallest DPEs within a 72 h lead, while The Hurricane Weather Research and Forecasting (HWRF) achieved the best track forecast performance at 96 h and 120 h leads. Most of the models produced an obvious westward systematic bias on track forecast from a 24 h to a 120 h lead. Further correlation and cluster analyses indicate that initial TC intensity and size and environmental steering flow can be regarded as good predictors for TC DPEs. TCs with a stronger initial intensity, a bigger initial size, and a larger environmental steering flow in general attain a smaller DPE, and the improvements may go up to 36% at short lead-time.

Heat balance characteristics in the South China Sea and surrounding areas simulated using the TRAMS model—a case study of a summer heavy rain and a winter cold spell

Introduction: This study is first to apply d iagnostic analysis of the forecast tendencies to evaluate the simulation of equilibrium features in the South China Sea and its surrounding areas using The Tropical Regional Atmosphere (TRAMS) model, and further identify the sources of simulation biases of the model.Methods: On the basis of the quasi equilibrium between dynamic and physical processes, the deviation of net forecast tendencies, which reflects the overall equilibrium of the model, serves as a good indicator of the model simulations bias. The sources of the forecast error can be further inferred by decomposing the net forecast tendencies into the dynamic and each physical process.Results: Focusing on moisture and temperature tendencies, the results show that the TRAMS model generally captures the thermal equilibrium characteristics and the contributions of each physical process, which are markedly different between summer and winter and are affected by the Northwest Pacific Subtropical High (WPSH) and deep trough of East Asia respectively. Furthermore, the underestimation of vapour consumption by cloud microphysical parameterisation and the overestimation of sea surface heat flux by boundary layer parameterisation near the surface contribute the most to systematic model bias. The temperature bias from 900 to 300 hPa during winter mainly originates from the responses of radiation, cumulus convection, and cloud microphysical parameterisations because water vapour absorbs long wave radiation, heating the atmosphere, and clouds reduce short wave radi ation absorption, cooling it.Discussion: The presented analyses provide a reference for further optimisation and improvement of the model.

The second-generation real-time ecological environment prediction system for the Guangdong–Hong Kong–Marco Greater Bay Area: Model setup, validation, improvements, and online visualization

With the rapidly growing population and socioeconomic development of the Guangdong–Hong Kong–Marco Greater Bay Area of China, inputs of diverse contaminants have rapidly increased. This poses threats to the water quality of the Pearl River Estuary (PRE) and adjacent seas. To provide valuable information to assist the governors, stakeholders, and decision-makers in tracking changes in environmental conditions, daily nowcasts and two-day forecasts from the ecological prediction system, namely the Coupled Great Bay Ecological Environmental Prediction System (CGEEPS), has been setup. These forecast systems have been built on the Coupled Ocean–Atmosphere–Wave–Sediment Transport modelling system. This comprises an atmospheric Weather Research Forecasting module and an oceanic Regional Ocean Modelling System module. Daily real-time nowcasts and 2-day forecasts of temperature, salinity, NO2 + NO3, chlorophyll, and pH are continuously available. Visualizations of the forecasts are available on a local website (http://www.gbaycarbontest.xyz:8008/). This paper describes the setup of the environmental forecasting system, evaluates model hindcast simulations from 2014 to 2018, and investigates downscaling and two-way coupling with the regional atmospheric model. The results shown that though CGEEPS lacks accuracy in predicting the absolute value for biological and biogeochemical environmental variables. It is quite informative to predict the spatio-temporal variability of ecological environmental changes associated with extreme weather events. Our study will benefit of developing real-time marine biogeochemical and ecosystem forecast tool for oceanic regions heavily impact by extreme weathers.

Establishment of an analytical model for remote sensing of typical stratocumulus cloud profiles under various precipitation and entrainment conditions

Abstract. Structural patterns of cloud effective radius (ER) and liquid water content (LWC) profiles are essential variables of cloud lifecycle and precipitation processes, while observing cloud profiles from passive remote-sensing sensors remains highly challenging. Understanding whether there are typical structural patterns of ER and LWC profiles in liquid clouds and how they are linked to cloud entrainment or precipitating status is critical in developing algorithms to derive cloud profiles from passive satellite sensors. This study aims to address these questions and provide a preliminary foundation for the development of liquid cloud profile retrievals for the Multi-viewing, Multi-channel and Multi-polarization Imaging (3MI) sensor aboard the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation (EPS-SG) satellite, which is scheduled to be launched in 2025. Firstly, we simulate a large ensemble of stratocumulus cloud profiles using the Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS). The empirical orthogonal function (EOF) analysis is adopted to describe the shape of simulated profiles with a limited number of elemental profile variations. Our results indicate that the first three EOFs of LWC and ER profiles can explain >90 % of LWC and ER profiles. The profiles are divided into four prominent patterns and all of these patterns can be simplified as triangle-shaped polylines. The frequency of these four patterns is found to relate to intensities of the cloud-top entrainment and precipitation. Based on these analyses, we propose a simplified triangle-shaped cloud profile parameterization scheme allowing us to represent these main patterns of LWC and ER. This simple yet physically realistic analytical model of cloud profiles is expected to facilitate the representation of cloud properties in advanced retrieval algorithms such as those developed for the 3MI/EPS-SG.

Impact of Extratropical Northeast Pacific SST on U.S. West Coast Precipitation

AbstractThe rainfall over the U.S. West Coast is known to be highly influenced by large‐scale atmospheric circulation and tropical climate teleconnections. However, the role of North Pacific oceanic variability is less understood. Using high‐resolution regional atmospheric model simulations forced by sustained positive and negative phases of the extratropical Pacific Decadal Oscillation sea surface temperature anomalies (SSTa), we diagnose the precipitation changes over the U.S. West Coast during 2010–2020. We find that precipitation anomalies are up to 60% stronger (weaker) for the warm (cold) cases, especially over Northern and Central California during wintertime, and Baja California in the summertime. In both seasons, precipitation is predominantly modulated through changes in the water vapor flux, which are directed toward the coast in wintertime and away from the coast during summertime. These flux anomalies are primarily driven by large‐scale changes in the wind associated with the atmospheric adjustment to the strong ocean SSTa.

One-degree resolution mascon solution over Antarctic derived from GRACE Level-2 data

The mass loss of the Antarctic Ice Sheet (AIS) is an important contributor to global sea-level rise in response to the warming ocean and atmospheric temperatures as well as the changes in current systems and precipitation patterns. In this study, a regional mascon method is developed to squeeze more mass change signals, in which the pseudo-observations of the geopotential are generated from the unfiltered GRACE Level-2 data whereas the regularization matrix is constructed with the prior information derived from filtered GRACE Level-2 data. A series of mascon solutions with 1°×1° equal-area resolution over AIS is derived from the updated Tongji-Grace2018 model spanning April 2002 to December 2016. Compared to the filtering results from P4M6 decorrelation and 100 km Gaussian filtering, our mascon solutions can effectively suppress the strips, improve the spatial resolution over AIS, and get a stronger signal with an improvement of 116.86% in the Antarctic Peninsula Ice Sheet (APIS), and more coincide with the features of glaciers and ice streams, such as the most striking ice mass loss in Totten, Getz, Thwaites and Pine Island, and the ice mass gain in Kamb Ice Stream. During the period from 2002 to 2016, the mass change rates from our mascon solution are −103.6 ± 5.6 Gt/yr, 63.0 ± 4.3 Gt/yr, −143.3 ± 4.9 Gt/yr and −23.29 ± 1.2 Gt/yr in AIS, East AIS, West AIS, and APIS, respectively. The mass change signals at the basin scale are with even more distinguishing features, with the highest mass gain rates of 18.03 ± 1.88 Gt/yr and 14.55 ± 0.60 Gt/yr at Basin 7 and Basin 18, and the highest mass loss rates of −58.57 ± 2.48 Gt/yr and −44.12 ± 2.27 Gt/yr at Basin 21 and Basin 22. Relative to the cumulated surface mass balance from the regional atmospheric climate model, the correlation coefficients of our mascon solutions are 0.91, 0.94, and 0.96 in East AIS, West AIS, and APIS.

Modulation of the seasonal cycle of the Antarctic sea ice extent by sea ice processes and feedbacks with the ocean and the atmosphere

Abstract. The seasonal cycle of the Antarctic sea ice extent is strongly asymmetric, with a relatively slow increase after the summer minimum followed by a more rapid decrease after the winter maximum. This cycle is intimately linked to the seasonal cycle of the insolation received at the top of the atmosphere, but sea ice processes as well as the exchanges with the atmosphere and ocean may also play a role. To quantify these contributions, a series of idealized sensitivity experiments have been performed with an eddy-permitting (1/4∘) NEMO-LIM3 (Nucleus for European Modelling of the Ocean–Louvain-la-Neuve sea ice model version 3) Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM2 regional atmospheric model. In those experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake and release upon sea ice growth and melt, ice dynamics, and surface albedo. We find that the evolution of sea ice extent during the ice advance season is largely independent of the direct effect of the perturbation and appears thus mainly controlled by initial state in summer and subsequent insolation changes. In contrast, the melting rate varies strongly between the experiments during the retreat, in particular if the surface albedo or sea ice transport are modified, demonstrating a strong contribution of those elements to the evolution of ice coverage through spring and summer. As with the advance phase, the retreat is also influenced by conditions at the beginning of the melt season in September. Atmospheric feedbacks enhance the model winter ice extent response to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere.

The Merits of Ocean Prediction for the Prediction of 2010, 2016, and 2021 Summer Heavy Rainfall Events in Japan

The merits of ocean prediction for heavy rainfall prediction were examined using hindcast experiments for three summer heavy rainfall events in 2010, 2016, and 2021 in Japan. In these events, the rainfall stemmed from Baiu and stationary fronts. The hindcast experiments were conducted using regional atmospheric and coupled models (RUN-ATM and RUN-CPL). The results show that RUN-CPL predicted more accurate rainfall properties than RUN-ATM. RUN-ATM underestimated the accumulated rainfall compared with RUN-CPL, and the underestimation became more significant as the lead time increased. This was due to decreased horizontal vapor transport in the ocean southwest of Japan. Pressure patterns that dominated the vapor transport were different in each case. When an atmospheric model was used, the sea level pressure difference between the Pacific high and Japan was weakened, contributing to weaker vapor transport from the southwest because of the weakened anticyclonic and cyclonic circulations at the region of Pacific high and over Japan. The degraded pressure patterns generated by RUN-ATM stemmed from incorrect latent heat flux response to the sea surface temperature. When air-sea was decoupled in the atmospheric model, the decrease of sea surface temperature by latent heat flux did not occur, so the latent heat flux was overestimated. Also, this caused the decrease in the pressure difference between Pacific high and Japan areas, leading to a weaker moisture transport from the ocean southwest of Japan. The heat budget analysis in the ocean mixed layer suggests that ocean dynamics, especially vertical mixing, contributes to suppress the overestimation of latent heat flux around the Pacific high. It is concluded that heavy rainfall prediction that incorporates appropriate air-sea coupling and ocean prediction provides better results than atmosphere-only model prediction for front-derived heavy rainfall events.

Snow stratigraphy observations from Operation IceBridge surveys in Alaska using S and C band airborne ultra-wideband FMCW (frequency-modulated continuous wave) radar

Abstract. During the concluding phase of the NASA Operation IceBridge (OIB), we successfully completed two airborne measurement campaigns (in 2018 and 2021, respectively) using a compact S and C band radar installed on a Single Otter aircraft and collected data over Alaskan mountains, ice fields, and glaciers. This paper reports seasonal snow depths derived from radar data. We found large variations in seasonal radar-inferred depths with multi-modal distributions assuming a constant relative permittivity for snow equal to 1.89. About 34 % of the snow depths observed in 2018 were between 3.2 and 4.2 m, and close to 30 % of the snow depths observed in 2021 were between 2.5 and 3.5 m. We observed snow strata in ice facies, combined percolation and wet-snow facies, and dry-snow facies from radar data and identified the transition areas from wet-snow facies to ice facies for multiple glaciers based on the snow strata and radar backscattering characteristics. Our analysis focuses on the measured strata of multiple years at the caldera of Mount Wrangell (K'elt'aeni) to estimate the local snow accumulation rate. We developed a method for using our radar readings of multi-year strata to constrain the uncertain parameters of interpretation models with the assumption that most of the snow layers detected by the radar at the caldera are annual accumulation layers. At a 2004 ice core and 2005 temperature sensor tower site, the locally estimated average snow accumulation rate is ∼2.89 m w.e. a−1 between the years 2003 and 2021. Our estimate of the snow accumulation rate between 2005 and 2006 is 2.82 m w.e. a−1, which matches closely to the 2.75 m w.e. a−1 inferred from independent ground-truth measurements made the same year. The snow accumulation rate between the years 2003 and 2021 also showed a linear increasing trend of 0.011 m w.e. a−2. This trend is corroborated by comparisons with the surface mass balance (SMB) derived for the same period from the regional atmospheric climate model MAR (Modèle Atmosphérique Régional). According to MAR data, which show an increase of 0.86 ∘C in this area for the period of 2003–2021, the linear upward trend is associated with the increase in snowfall and rainfall events, which may be attributed to elevated global temperatures. The findings of this study confirmed the viability of our methodology, as well as its underlying assumptions and interpretation models.

Response of Intensity and Structure of Typhoon Jebi (2018) before Landfall to 2-K and 4-K Warmed Future Climates in Dynamical Downscaling Experiments

To investigate the effects of global warming on Typhoon Jebi (2018), we performed high-resolution pseudo-global 2-K and 4-K warming simulations with initial time ensembles using a regional atmospheric model. The pseudo-global warming experiments demonstrated the further facilitation of Jebi's development with a higher rise in the temperature. The intensity over the ocean to the south of Japan increased by 8% (20%) in the climate warmed 2-K (4-K) to the current climate. Typhoon Jebi, in the 4-K warming simulations, maintained a robust inner-core characterized by a compact and deep eyewall and well-developed primary and secondary circulations even immediately before landfall, in contrast to the result in the 2-K warming simulations. The sustained robust axisymmetric structure immediately before landfall in the 4-K warming runs was strongly associated with the enhanced ocean warming around Japan, notable moistening of the lower-to-middle troposphere in the vicinity of Typhoon Jebi, and a significant decrease in vertical wind shear under the extremely warmed future climate. The nonlinear responses of Typhoon Jebi to the tropospheric temperature rise are attributable to the drastic changes in the midlatitude's thermodynamic and dynamic environments under climate changes resulting from 2-K to 4-K global warming.

Predicting Groundwater Level Using Climate Change Scenarios in the Southern Part of Mali

Groundwater is mainly demanded in all the activities for the population of the southern part especially in the Koda catchment, the studied area. These resources are affected by various factors especially climate change. Therefore, knowing the impact of projected climate change on groundwater recharge is an important issue for water resources management, especially for those responsible for the Koda catchment. In this work, the impact of climate change on groundwater resources in the study area in Mali, West Africa is investigated. The Hydrogeological modeling was performed using the Gardenia model, and the monthly precipitation and temperature data were used as the Baseline. These data considered the past 30-year period (1987-2016) and the projections for the next 30 years (2021-2050). Projected precipitation and air temperatures, extracted from the Rossby Centre regional Atmospheric climate model (RCA 4) statistically downscaled from the GCM-IHEC-EC-EARTH and the GCM-MPI-M-MPI-ESM-LR under the Representative Concentration Pathways RCP 4.5 and RCP 8.5 and corrected with the Multiscale Quantile Mapping bias correction method, were used as input data to the gardenia model. Potential evapotranspiration (PET) values estimated from Blaney Criddle method and groundwater levels measured in three piezometers were used to calibrate the Gardenia model. The outputs display the reduction of groundwater level in the three piezometers in the Koda catchment for all the two Regional Climate Models (RCMs) during the periods of rainy season from July to October. From the results of GCM IHEC-EC-EARTH, the projected decline in GWL reaches 1.09 m for the RCP 4.5 and it up to 1.26 m for the RCP 8.5 in the study area while the GCM MPI-M-MPI-ESM-LR presentes the decline in groundwater level (GWL) during winter season from about 0.62 m for the RCP 4.5 up to 1.93 m for the RCP 8:5. Both RCMs project a reduction trend of groundwater recharge over time. It is noticeable that this decline is greater in RCP8.5 for all the three piezometers. The results also show that the average groundwater recharge (90 mm) in the future (2021-2050) is lower (180 mm) than that of the current drought (1987-2016), which could lead to severe drought events. The projected impacts of climate change would have a significant impact on groundwater in the period of 2029-2039; this situation could have a negative impact the socioeconomic activities especially on agriculture, which depends on water resources. The results will help also to take some adaptation measures to climate change, the famers could have a possibility to know the period of groundwater recharge where they have more water infiltration therefore, where to seek crops that need less or more water. The study area presents numerous potential of groundwater, the results could be a tool for groundwater management and to determine the favorable sites to implant new boreholes.

Discussing an extreme mock/what-if scenario over the antarctic peninsula: the effect of intense melt on surface mass balance

This discussion paper interprets the findings of a recent study comparing melt estimates from the regional atmospheric model MAR, those derived from Automatic Weather Stations (AWS), and microwave remote sensing images over the Antarctic Peninsula from 2019 to 2021. Our interpretation reveals a paradox: MAR overestimates melt when compared to AWS-based melt estimates, yet underestimates melt when compared to satellite imagery. This discrepancy underscores a fundamental gap in our understanding of surface processes. To illustrate the potential implications of this gap, we present a fictional (“what-if”) scenario that explores an extreme case of melting, based on parametrizations from Kittel et al., 2022, and the outliers of Dethinne et al., 2023. We examine the potential impact on the ice sheet's surface mass balance (SMB), drawing parallels with the situation in Greenland during the 1990s, where increased melt production had cascading effects on SMB. Moreover, we highlight that the presence of liquid water at the surface of the snowpack can be a precursor to significant destabilization processes over ice shelves, although this aspect is not the focus of our current paper. By opening a debate on the accuracy and interpretation of melt modeling, we aim to draw attention to the potential consequences of extreme melting events on the Antarctic Ice Sheet's SMB and stability.

Atmospheric impacts of local sea surface temperatures versus remote drivers during strong South China Sea winter cold tongue events

AbstractSea surface temperatures (SSTs) in the western part of the South China Sea (SCS) are cooler than in the eastern part in boreal winter, owing to a winter climatological cold tongue (CT). In this study, using a regional atmospheric model configured for the Maritime Continent, we assess the atmospheric impacts of local (or SCS) SSTs versus those from remote drivers (e.g., western tropical Pacific SSTs) during strong CT events with anomalously cool SSTs. In the local run, more rainfall is observed over the eastern SCS, but no significant atmospheric impacts are found over the CT region when SSTs associated with strong CT events are imposed within the SCS while climatological conditions are imposed elsewhere. SCS SST anomalies during strong CT events do not significantly modify the regional wind circulation. The lack of atmospheric response to SSTs over the CT region may be explained by the wintertime mean SSTs (i.e., <27–28°C) over the CT region that are inadequate to trigger deep atmospheric convection, while eastern SCS SSTs are high enough. The increase of anomalous positive moist static energy (MSE) near the sea level over the eastern SCS indicates underlying warm eastern SCS SST anomalies could be influencing positive rainfall anomalies. In the remote run, imposing climatological SCS SSTs but remote SSTs and lateral boundary conditions linked to strong CT events results in cyclonic wind and positive rainfall anomalies over the eastern SCS and Philippines, which are a Matsuno–Gill response to the diabatic heating anomalies over the warm western tropical Pacific SST anomalies. Positive rainfall and cloud cover anomalies associated with the cyclonic wind anomalies are due to the anomalous positive MSE import into the eastern SCS by horizontal advection.

Simulation and forecasting of atmospheric CO2 using RAMS

Concentration of carbon dioxide as the main greenhouse gas has been increasing, which has serious impacts on climate change, ecosystem, and human health. This study uses the Regional Atmospheric Modeling System (RAMS V6.2) with the Simple Biosphere (SiB-2) sub-model to simulate and forecast the concentration of carbon dioxide over the Daintree Rainforest in Australia. To evaluate the performance of the model, results are compared with the satellite product (MultiInstrumentFusedXCO2). This work evaluates the impact of various grid sizes, different combinations of diffusion parameters, and boundary conditions on CO2 simulations. Results reveal that RAMS can remarkably improve the statistical measures of the simulations particularly compared with the previous modeling analysis. The maximum mean bias error and RMSE in this study for all simulations are smaller than 1.85 and 2.07 ppm, respectively. The most proper simulation type (type III) leads to the average bias error and RMSE of 0.34 and 0.94 ppm, respectively. Furthermore, results show that the fuzzy algorithm is a proper method to provide initial CO2 in forecasting. This study shows that RAMS can be efficiently used in CO2 simulation and forecasting, which is valuable for CO2 monitoring, climate, environment, and management applications.

Circulation and stratification drivers during the summer season in the upwelling bay of Paracas (Peru): A modelling study

The circulation and stratification in the shallow semi-enclosed bay of Paracas located downstream of the main upwelling cell off the Peruvian coast were studied during the summer season using a regional circulation model and in situ observations. A downscaling strategy based on a series of three embedded grids, from 10 km to 500 m resolution in the bay allows to take into account the influence of remote perturbations on the bay dynamics. Debiased surface winds from a high-resolution regional atmospheric model were used to force the model. The shortwave absorption depth was parameterized using satellite measurements of surface chlorophyll.Sensitivity experiments to the model forcing and parameterizations were performed to investigate the impact of the wind diurnal variability, tidal forcing, freshwater discharge from a nearby river and shortwave absorption depth on the bay stratification. Results show that: debiasing the wind intensity reduced the model cold bias in the bay and increase the stratification; a shallow shortwave absorption depth induced a cooling of the subsurface water, increasing the stratification; freshwater discharge from the Pisco river north of the bay increased slightly the stratification in the bay during days of weak wind. The high sensitivity of the bay stratification to the atmospheric forcing calls for the need to use more realistic wind forcing products.The circulation in the bay under strong (>5.5 m s−1) and weak (<3 m s−1) winds was also examined. The summer circulation during strong upwelling-favorable wind conditions was characterized by northward surface currents transporting the bay surface waters outward and subsurface currents transporting cold deeper waters into the bay along its western shore. During weak wind conditions, the current is outward in the bottom layer and a surface southward current related to the poleward undercurrent flowing over the continental slope and shelf transported warm waters into the bay, generating a cyclonic circulation in the bay.