Incoming Shortwave Radiation Research Articles

Growth phase-specific evaporative demand and nighttime temperatures determine Maize (Zea Mays L.) yield deviations as revealed from a long-term field experiment

Weather impacts on crop productivity have emerged as a significant research area, and agroecosystems globally have been evaluated for these impacts. However, only a limited body of research relies on experimental determination of field-scale impacts, relative to coarser-scale estimations. Experimental frameworks can control confounding factors that potentially undesirably affect coarser-scale assessments. Here, we employ a long-term (31-year) experimental trial to investigate weather-related signatures on rainfed maize (Zea Mays L.) yield in the western Corn Belt, at seasonal and sub-seasonal scales. Among all the weather indices evaluated [(maximum, minimum, and average air temperatures (Tmax, Tmin, Tavg), precipitation (Pcp), incoming shortwave radiation (Rs), wind speed (u2), relative humidity (RH), vapor pressure deficit (VPD), alfalfa-reference evapotranspiration (ETr), and aridity index (AI)], ETr accounted for the most (⁓50%) yield variance, followed by Tavg, Tmax, VPD, Rs, Tmin, Pcp, u2, RH, and AI. Weather indices most effectively accounted for yield variance during the late reproductive (R) phase, followed by early R phase, late vegetative (V) phase and lastly, early V phase. While seasonal ETr was responsible for highest yield sensitivity (-0.69 s.d. s.d.−1), sub-seasonal weather indices were also identified for highest yield sensitivity (u2, Tavg, ETr, Tmax during early V, late V, early R, and late R, respectively). Among all possible combinations, a multiple linear regression model consisting of ETr and Tmin best predicted yield deviations (R2=0.64) at the seasonal scale, while a sub seasonal model consisting of early V ETr, early R ETr, and late R Tmin performed the best (R2=0.66). Both models were validated for five independent counties to predict USDA estimates of rainfed maize yield deviations. Recent advances in mechanistic understanding of nighttime warming (increasing Tmin) and evaporative demand impacts on crop performance concur with our experimental inference of importance of ETr and Tmin for rainfed maize yields.

Preliminary study on the temperature relationship at remotely-sensed tree canopy and below-canopy air and ground surface

Thermal infrared remote sensing is a popular tool to measure the impacts of land cover on land surface temperature (LST) in cities. Tree-covered areas usually exhibit a lower LST than other urban surfaces such as concrete, suggesting that urban trees can improve human thermal comfort. However, the remotely-sensed LST of trees is only representative of their canopy temperature. The linkage between the LST of trees and the below-canopy thermal conditions has not been investigated scientifically. This study aimed to measure the differences and determine the correlations between tree canopy temperature (Tc), below-canopy ground surface temperature (Ts) and below-canopy air temperature (Ta) from 42 trees of 16 species in a golf course in Hong Kong. Under the meteorological conditions of the study period (air temperature: ~26 °C; mean radiant temperature: ~30 °C), t-tests showed that mean ± SD Tc (24.1 ± 2.9 °C) did not significantly differ from Ts (24.5 ± 1.8 °C, p = 0.158), but it was significantly lower than Ta (25.4 ± 2.3 °C, p < 0.001). Tc was highly and significantly correlated with Ts (r = 0.81, p < 0.001) and Ta (r = 0.92, p < 0.001). Further analyses showed that the differences between Tc and Ts (ΔTcs) and between Tc and Ta (ΔTca) were significantly dependent on background air temperature (ΔTcs only), relative humidity, mean radiant temperature and incoming shortwave radiation. This study serves as a preliminary investigation on an important knowledge gap in urban climate research. The findings are particularly relevant to researchers who use remotely-sensed LST data to study human thermal comfort.

Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe

This study is dedicated to improving the daily release of ragweed pollen emission in the context of deterministic regional modelling for analysis and forecast. First, correlations are calculated between daily modelled meteorological variables (wind speed, temperature, humidity, precipitation, surface fluxes) and daily pollen counts at nine stations in Hungary, Croatia and France between 2005 and 2011. The 2 m temperature is the most correlated parameter, followed by convective velocity and incoming shortwave radiation, while precipitation rate and 2 m specific humidity act as limiting factors. Using these results, a ragweed pollen daily release formulation is proposed. This formulation is implemented in the CHIMERE chemistry-transport model and tested during the whole year of 2010. Results are compared to observations, and it is shown that the new formulation provides a more realistic day-to-day variability: the spatio-temporal correlation between surface measurements and modelled concentrations is 0.77, greater than two other known emission schemes.

Relationships between single-tree mountain birch summertime albedo and vegetation properties

Understanding and quantifying the influence of tree structure and ground vegetation on albedo in the boreal-alpine treeline is urgently needed to assess and predict the biophysical climatic feedback effect of forest- and treeline expansion. Fine-spatial resolution in-situ radiation measurements sensitive to small-scale variability enable precise albedo estimation for complex heterogeneous landscapes. In this study, horizontally measured single-tree albedo of mountain birch and their spatially consistent tree- and ground vegetation properties were collected in the boreal-alpine treeline over a period of 14 days in summertime. The aim was to identify properties of tree structure and ground vegetation driving single-tree mountain birch albedo. In addition, it was of interest to analyze the relationship between the vegetation properties and a slope-estimated albedo when a simplified correction of slope and aspect of the terrain was applied to the horizontally measured incoming shortwave radiation. Both properties of tree structure and ground vegetation were strongly related to albedo. The results imply that expansion of mountain birch forests at the expense of the prevalence of bright-colored lichens, bare rock, graminoids and mosses will reduce summertime boreal-alpine treeline albedo. Taller trees with wider tree crowns will absorb more solar radiation than smaller trees and hence also reduce albedo. Overall average difference of albedo of sample plots with and without presence of mountain birch was 0.06, corresponding to 27% of the albedo for plots without birch. Horizontally measured albedo was more strongly correlated with the vegetation properties than when corrected for terrain slope and aspect. The findings show that the appropriateness of horizontally measured albedo of single trees and tree clusters in open sloping terrain, depends on the spatial size of the footprint of the downward-looking radiation sensor relative to the size of the tree subject to observation.

Atmospheric Blocking Drives Recent Albedo Change Across the Western Greenland Ice Sheet Percolation Zone

Greenland Ice Sheet (GrIS) albedo has decreased over recent decades, contributing to enhanced surface melt and mass loss. However, it remains unclear whether GrIS darkening is due to snow grain size increases, higher concentrations of light-absorbing impurities (LAIs), or a combination. Here, we assess albedo controls in the western GrIS percolation zone using in situ albedo, LAI, and grain size measurements. We find a significant correlation between albedo and snow grain size (p < 0.01), but not with LAIs. Modeling corroborates that LAI concentrations are too low to significantly reduce albedo, but larger grain sizes could reduce albedo by at least ∼3%. Strong atmospheric blocking increases grain sizes and reduces albedo through increased surface temperature, fewer storms, and higher incoming shortwave radiation. These findings clarify the mechanisms by which anomalously strong blocking contributed to recent GrIS albedo decline and mass loss, highlighting the importance of improving projections of future blocking.

Multi-year observations of the high mountain water cycle in the Langtang catchment, Central Himalaya.

The Langtang catchment is a high mountain, third order catchment in the Gandaki basin in the Central Himalaya (28.2°N, 85.5°E), that eventually drains into the Ganges. The catchment spans an elevation range from 1400 to 7234 m a.s.l. and approximately one quarter of the area is glacierized. Numerous research projects have been conducted in the valley during the last four decades, with a strong focus on the cryospheric components of the catchment water balance. Since 2012 multiple weather stations and discharge stations provide measurements of atmospheric and hydrologic variables. Full weather stations are used to monitor at an hourly resolution all four radiation components (incoming and outgoing shortwave and longwave radiation; SWin/out and LWin/out), air temperature, humidity, wind speed and direction, and precipitation, and cover an elevational range of 3862–5330 m a.s.l. Air temperature and precipitation are monitored along elevation gradients for investigations of the spatial variability of the high mountain meteorology. Dedicated point‐scale observations of snow cover, depth and water equivalent as well as ice loss have been carried out over multiple years and complement the observations of the water cycle. All data presented is openly available in a database and will be updated annually.

Can we replace observed forcing with weather generator in land surface modeling? Insights from long-term simulations at two contrasting boreal sites

This study evaluates the simulation of water balance components at half-hourly time steps from the Canadian Land Surface Scheme (CLASS) when driven by a 500-year stochastic meteorological data set produced by the Advanced WEather GENerator (AWE-GEN) at two boreal sites with contrasting water availability. The CLASS was driven by ERA5 reanalysis data (CLASS-CTL) over 39 years and its output was used as a surrogate for land surface observations. At both sites, the mean monthly and annual values of all meteorological variables used to drive CLASS, including precipitation, are well captured by AWE-GEN, but their variability is, sometimes, biased. In general, CLASS driven by stochastic data (CLASS-WG) tends to produce higher evapotranspiration compared to values simulated by CLASS-CTL, especially during spring and summer at the wet site. The interannual evapotranspiration-precipitation and runoff-precipitation relationships derived from CLASS-WG and those derived from CLASS-CTL were very similar to each other at the dry site; they both indicate that evapotranspiration and runoff are limited by water availability. At the wet site, however, CLASS-WG only captured well the interannual runoff-precipitation relationship. The sensitivity analysis shows that CLASS water fluxes are particularly affected by the replacement of physically consistent input time series of incoming short-wave radiation, precipitation, temperature, and specific humidity. In conclusion, the results show that even though a weather generator can produce coherent climate time series, the use of this synthetic data as meteorological forcing in a physically based land surface model does not necessarily reproduce the complex surface processes, such as the surface water fluxes. More studies are encouraged to further analyze the constraints of this framework.

A numerical study on the mixed layer depth variability and its influence on the sea surface temperature during 2013–2014 in the Bay of Bengal and Equatorial Indian Ocean

This study addresses the air–sea interaction processes and mixed layer variability, which cause the intraseasonal oscillations in the sea surface temperature (SST) during January 2013–December 2014 using the Regional Ocean Modeling System (ROMS). We have analyzed the SST variability at three locations—northern Bay of Bengal (BoB)/15°N, 90°E (R15), central BoB/12°N, 90°E (R12), and equatorial Indian Ocean (EIO)/0°N, 80.5°E (R0). During northeast monsoon (NEM) and southwest monsoon (SWM), intraseasonal SST variability is respectively controlled by the intense outgoing fluxes (sum of longwave radiation, latent heat flux, and sensible heat flux) and zonal wind stress. The intraseasonal SST variability in spring and fall is modulated by intense incoming shortwave radiation. There is a profound impact of mixed layer depth (MLD) variations on the intraseasonal SST oscillations in the BoB and EIO. At R15, and R12, deepened simulated MLD is associated with the lowered SST variability in the NEM and SWM. In spring and fall, the shallow MLD variability corresponds to higher intraseasonal SST variability at the buoy locations. In the northern BoB, ROMS cannot capture barrier layer (BL) and temperature inversion (TI) accurately in the winter and premonsoon season due to salinity bias, resulting in the difference between simulated and actual MLD. But the simulated MLD bias does not affect the intraseasonal SST structures in the NEM and pre-SWM. In the northern BoB, the proper representation of salinity structure may represent BL, TI, and MLD, accurately in the simulation during the winter and premonsoon season.

Is Turning Down the Sun a Good Proxy for Stratospheric Sulfate Geoengineering?

AbstractDeliberately blocking out a small portion of the incoming solar radiation would cool the climate. One such approach would be injecting SO2 into the stratosphere, which would produce sulfate aerosols that would remain in the atmosphere for 1–3 years, reflecting part of the incoming shortwave radiation. The cooling produced by the aerosols can offset the warming produced by increased greenhouse gas (GHG) concentrations, but it would also affect the climate differently, leading to residual differences compared to a climate not affected by either. Many climate model simulations of geoengineering have used a uniform reduction of the incoming solar radiation as a proxy for stratospheric aerosols, both because many models are not designed to adequately capture relevant stratospheric aerosol processes, and because a solar reduction has often been assumed to capture the most important differences between how stratospheric aerosols and GHG would affect the climate. Here we show that dimming the sun does not produce the same surface climate effects as simulating aerosols in the stratosphere. By more closely matching the spatial pattern of solar reduction to that of the aerosols, some improvements in this idealized representation are possible, with further improvements if the stratospheric heating produced by the aerosols is included. This is relevant both for our understanding of the physical mechanisms driving the changes observed in stratospheric‐sulfate geoengineering simulations, and in terms of the relevance of impact assessments that use a uniform solar dimming.

Daily Actual Evapotranspiration Estimation in a Mediterranean Ecosystem from Landsat Observations Using SEBAL Approach

Quantifying actual evapotranspiration (ETa) over natural vegetation is crucial in evaluating the water status of ecosystems and the water-use patterns in local or regional hydrological basins. Remote sensing-based surface energy balance models have been used extensively for estimating ETa in agro-environments; however, the application of these models to natural ecosystems is still limited. The surface energy balance algorithm for land (SEBAL) physical-based surface energy balance model was applied to estimate the actual evapotranspiration over a heterogeneous coverage of Mediterranean maquis in a natural reserve in Sardinia, Italy. The model was applied on 19 Landsat 5 and 8 images from 2009 to 2014, and the results were compared to the data of a micrometeorological station with eddy covariance flux measurements. Comparing the SEBAL-based evaporative fraction (ΛS) to the corresponding tower-derived evaporative fractions (ΛT) showed good flux estimations in the Landsat overpass time (Coefficient of determination R2 = 0.77, root mean square error RMSE = 0.05 and mean absolute error MAE = 0.076). Three methods were evaluated for upscaling instantaneous latent heat flux (λE) to daily actual evapotranspiration (ETa,D). The upscaling methods use the evaporative fraction (Λ), the reference evapotranspiration fraction (EFr) and the ratio of daily to instantaneous incoming shortwave radiation (Rs24/Rsi) as upscaling factors under the hypothesis of diurnal self-preservation. A preliminary analysis performed using only in-situ measured data demonstrated that the three factors were relatively self-preserved during the daytime, and can yield good ETa,D estimations, particularly when obtained at near the Landsat scene acquisition time (≈10:00 UTC). The upscaling factors obtained from SEBAL retrieved instantaneous fluxes, and some ancillary measured meteorological data were used to upscale SEBAL-estimated instantaneous actual λ to daily ET. The Λ EFr and Rs24/Rsi methods on average overestimated the measured ETa,D by nearly 20, 61 and 18%, respectively. The performance of the Λ and Rs24/Rsi methods was considered satisfactory, bearing in mind the high variable ground cover and the inherent variability of the biome composition, which cannot be properly represented in the Landsat moderate spatial resolution. In this study, we tested the potential of the SEBAL model application in a complex natural ecosystem. This modeling approach will be used to represent the spatial dynamics of ET, which will be integrated into further environmental and hydrological applications.

Meteorological Conditions and Cloud Effects on Surface Radiation Balance Near Helheim Glacier and Jakobshavn Isbræ (Greenland) Using Ground-Based Observations

The surface radiation budget is an essential component of the total energy exchange between the atmosphere and the Earth’s surface. Measurements of radiative fluxes near/on ice surfaces are sparse in the polar regions, including on the Greenland Ice Sheet (GrIS), and the effects of cloud on radiative fluxes are still poorly studied. In this work, we assess the impacts of cloud on radiative fluxes using two metrics: the longwave-equivalent cloudiness, derived from long-wave radiation measurements, and the cloud transmittance factor, obtained from short-wave radiation data. The metrics are applied to radiation data from two automatic weather stations located over the bare ground near the ice front of Helheim (HG, 66.3290°N, 38.1460°W) and Jakobshavn Isbræ(JI, 69.2220°N, 49.8150°W) on the GrIS. Comparisons of meteorological parameters, surface radiation fluxes, and cloud metrics show significant differences between the two sites. The cloud transmittance factor is higher at HG than at JI, and the incoming short-wave radiation in the summer at HG is about 50.0 W m−2 larger than at JI. Cloud metrics derived at the two sites reveal partly cloudy conditions were frequent (42 and 65% of the period at HG and JI) with a high dependency on the wind direction. The total cloud radiative effect (CREnet) generally increases during melt season at the two stations due to long-wave CRE enhancement by cloud fraction. CREnet decreases from May to June and increases afterward, due to the strengthened short-wave CRE. The annually averaged CREnet were 3.0 ± 7.4 W m−2 and 1.9±15.1 W m−2 at JI and HG. CREnet estimated from AWS indicates that clouds cool the JI and HG during melt season at different rates.

Comparing Measured Incoming Shortwave and Longwave Radiation on a Glacier Surface with Estimated Records from Satellite and Off-Glacier Observations: A Case Study for the Forni Glacier, Italy

The development of methods for quantifying meltwater from glaciated areas is very important for better management of water resources and because of the strong impact of current and expected climate change on the Alpine cryosphere. Radiative fluxes are the main melt-drivers, but they can generally not be derived from in situ measures because glaciers are usually located in remote areas where the number of meteorological stations is very low. For this reason, focusing, as a case study, on one of the few glaciers with a supraglacial automatic weather station (Forni Glacier), we investigated methods based on both satellite records and off-glacier surface observations to estimate incoming short- and long-wave radiation at the glacier surface (SWin and LWin). Specifically, for SWin, we considered CM SAF SARAH satellite gridded surface solar irradiance fields and data modeled by cloud transmissivity parametrized from both CM SAF COMET satellite cloud fractional cover fields and daily temperature range observed at the closest off-glacier station. We then used the latter two data sources to derive LWin too. Finally, we used the estimated SWin and LWin records to assess the errors obtained when introducing estimated rather than measured incoming radiation data to quantify glacier melting by means of an energy balance model. Our results suggest that estimated SWin and LWin records derived from satellite measures are in better agreement with in situ observations than estimated SWin and LWin records parametrized from observations performed at the closest off-glacier station. Moreover, we find that the former estimated records permit a significantly better quantification of glacier melting than the latter estimated ones.

Development of a Seamless Forecast for Solar Radiation Using ANAKLIM++

A novel approach for a blending between nowcasting and numerical weather prediction (NWP) for the surface incoming shortwave radiation (SIS) for a forecast horizon of 1–5 h is presented in this study. The blending is performed with a software tool called ANAKLIM++ (Adjustment of Assimilation Software for the Reanalysis of Climate Data) which was originally designed for the efficient assimilation of two-dimensional data sets using a variational approach. A nowcasting for SIS was already presented and validated in earlier publications as seamless solar radiation forecast (SESORA). For our blending, two NWP models, namely the ICON (Icosahedral Non-hydrostatic model) from the German weather Service (DWD) and the IFS (Integrated Forecasting System) from the European Centre for Medium-Range Weather Forecasts (ECMWF), were used. The weights for the input data for ANAKLIM++ vary for every single forecast time and pixel, depending on the error growth of the nowcasting. The results look promising, since the root mean square error (RMSE) and mean absolute error (MAE) of the blending are smaller than the error measures of the nowcasting or NWP models, respectively.

Application of integral parametrization “SAIL” for climatology incoming shortwave radiation fluxes

Along with field and satellite data, the calculation of fluxes using integral parameterizations can become a source of information about incoming shortwave radiation fluxes on the sea surface. In this work, we used the results of applying the SAIL parametrization created at the IO RAS, based on measurements of incoming shortwave radiation fluxes to the surface of the Atlantic Ocean and the corresponding meteorological parameters. The main task of such parameterizations is to construct climatology of shortwave radiation fluxes according to VOS data. In the course of the work, the new cloud climatology CLAAS ed.2 was used as input to calculate the average daily fields of the incoming shortwave radiation fluxes to the surface of the Atlantic Ocean. As reference data, we used a satellite database of shortwave radiation fluxes for the Atlantic Ocean - SARAH ed. 2. In conclusion, it can be noted that the SAIL parameterization works very well for a total cloud score of up to 4 octa. Further development of the SAIL parameterization is possible by separately taking into account the direct and diffuse flux of incoming shortwave radiation, since as part of the growth of possible cloud regimes, it is very important to know when the flux prevails over the diffuse and when vice versa.

The Enhancement of the Impact of the Wintertime North Atlantic Oscillation on the Subsequent Sea Surface Temperature over the Tropical Atlantic since the Middle 1990s

AbstractThe impact of the wintertime North Atlantic Oscillation (NAO) on the subsequent sea surface temperature (SST) anomalies over the tropical Atlantic has experienced obvious interdecadal changes during 1950–2015. During 1995–2015, the negative (positive) phase of the wintertime NAO favors positive (negative) SST anomalies over the tropical Atlantic in the subsequent spring–summer, whereas the NAO–SST connection is insignificant during 1970–94 and is confined to the northern tropical Atlantic (NTA) during 1950–69. Compared to 1970–94, the much stronger influence on the NTA SST during 1995–2015 and 1950–69 is associated with a southward shift of the southern boundary of the NAO. During 1995–2015, the inverted NAO-related warming of the tropical Atlantic consists of three stages: 1) the pronounced increase in SST over the subtropical North Atlantic (SNA) and the tropical South Atlantic (TSA) during December–January, 2) the pronounced increase in SST over the northwestern tropical Atlantic (NWTA) during February–April, and 3) the persistent warming over the tropical Atlantic during May–August. The increases in SST over the SNA and the TSA are attributed to significant positive latent heat flux anomalies via the wind–evaporation effect, which are connected by the suppressed regional Hadley circulation. Afterward, the associated anomalous downward motion over the NWTA persists into February–April, which induces more incoming shortwave radiation and results in a significant increase in the local SST via the cloud–radiation effect. In contrast, during 1950–69, due to the decreased interannual variability of the vertical motion over the NWTA, the anomalous downward branch aloft and the low-level cross-equatorial northwesterly winds associated with the inverted NAO are not evident, and thus the regions with an increase in SST are confined to the Northern Hemisphere.

Transient Climate Response to Arctic Sea Ice Loss with Two Ice-Constraining Methods

AbstractThe impact of Arctic sea ice loss on the ocean and atmosphere is investigated focusing on a gradual reduction of Arctic sea ice by 20% of the annual mean, occurring within 30 years, starting from present-day conditions. Two ice-constraining methods are explored to melt Arctic sea ice in a coupled climate model, while keeping present-day conditions for external forcing. The first method uses a reduction of sea ice albedo, which modifies the incoming surface shortwave radiation. The second method uses a reduction of thermal conductivity, which changes the heat conduction flux inside ice. Reduced thermal conductivity inhibits oceanic cooling in winter and sea ice basal growth, reducing the seasonality of sea ice thickness. For similar Arctic sea ice area loss, decreasing the albedo induces larger Arctic warming than reducing the conductivity, especially in spring. Both ice-constraining methods produce similar climate impacts, but with smaller anomalies when reducing the conductivity. In the Arctic, the sea ice loss leads to an increase of the North Atlantic water inflow in the Barents Sea and eastern Arctic, while the salinity decreases and the gyre intensifies in the Beaufort Sea. In the North Atlantic, the subtropical gyre shifts southward and the Atlantic meridional overturning circulation weakens. A dipole of sea level pressure anomalies sets up in winter over northern Siberia and the North Atlantic, which resembles the negative phase of the North Atlantic Oscillation. In the tropics, the Atlantic intertropical convergence zone shifts southward as the South Atlantic Ocean warms. In addition, Walker circulation reorganizes and the southeastern Pacific Ocean cools.

Comparison of different techniques for estimation of incoming longwave radiation

Global warming and climate change have left developing countries fragile in terms of agricultural production, and this vulnerability is expected to increase in the near future. The surface energy budget approach is a different perspective to the investigation of energy change over a landscape. In terms of budget items, the net radiation absorbed by the earth is equal to the difference between the sum of the incoming shortwave and longwave radiation and the sum of the reflected shortwave and emitted longwave radiation. The longwave radiation has important effects on dew deposition and drying on crop leaves in agricultural meteorology. A pyranometer provides routine measurement of the daytime radiation, but the longwave part of this radiation cannot be so readily measured at night time. In this study, multiple linear regression, artificial neural networks, deep learning, adaptive network-based fuzzy inference systems (ANFIS) and empirical models have been applied to model and estimate the mean incoming longwave radiation using atmospheric parameters. The ANFIS model appears to show good agreement between the measured and the estimated values for all days considered than other models.

Impact of fire on montane snowpack energy balance in Snow Gum forest stands

Forest stands fundamentally alter hydrology of a region through impacting area micrometeorology and corresponding variability in snow accumulation and melt. Bushfires significantly change these interactions through removal of forest canopy, darkening of tree stems, and post-fire stem decay. This study quantified the impact of pre- and post-bushfire E. pauciflora (Snow Gum) forest stands on snowpack energy balance in the Snowy Mountains of Southeast Australia. Forest canopy cover in undisturbed forest stands moderated snowpack energy exchange through reductions to incoming shortwave radiation and turbulent fluxes. Energy flux to the snowpack was at a maximum in the fire-disturbed forest due to lower snowpack albedo resulting in greater net shortwave radiation and an increased sensible heat emission from decaying tree stems. The fire-disturbed forest also experienced the largest evaporation rate with 8.1% of snowpack SWE being lost to the atmosphere. Dominant energy fluxes to the snowpack were shortwave radiation in the unforested area and fire-disturbed forest stand, and sensible heat in the undisturbed forest stand.

Impact of chlorophyll concentration on thermodynamics and dynamics in the tropical Indian ocean

It is well known that the physical properties of the ocean impact marine biological activity. Conversely, ocean biology feeds back to affect physical properties through the influence of phytoplankton on the ocean's absorption of incoming shortwave radiation. In this study, we explore this feedback in the tropical Indian Ocean (TIO) throughout the seasonal cycle by comparing solutions to a biophysical ocean model with and without chlorophyll concentrations. Phytoplankton-induced absorption increases near-surface temperature, thereby increasing evaporation and thinning the mixed layer. The resulting evaporation and restratification lower sea level and thereby affect circulation, particularly the summer monsoon current and the fall Wyrtki Jet. The circulation and evaporation changes in turn affect sea surface salinity. Finally, with chlorophyll there is a tendency for the model's sea-surface-temperature and mixed-layer depth-biases to shift closer to their observed values throughout the TIO, with the largest improvements occurring in the Arabian Sea and the Bay of Bengal.

Impacts of the Madden–Julian Oscillation on wintertime Australian minimum temperatures and Southern Hemisphere circulation

As a potential source of multiweek predictability, we investigate impacts of the Madden–Julian Oscillation (MJO) on temperature extremes during Austral winter using observational data analysis. We find a significant MJO influence on weekly mean minimum temperatures across much of northern and eastern Australia, with lower than normal minimum temperatures tending to occur during MJO phases 6 and 7. The likelihood of extreme weekly mean minimum temperatures also increases by at least of factor of 2 during these phases. In contrast, negligible impacts on maximum temperatures are observed. The proximate cause of the lower than normal minimum temperatures in these MJO phases is the anomalous equatorward advection of cool/dry continental air and enhanced night-time radiative cooling due to the drier conditions. The lack of any impact on maximum temperatures presumably stems from compensating day time warming from enhanced incoming shortwave radiation. The circulation anomalies over Australia during MJO phases 5–7 are shown to be a combination of the direct baroclinic response to the anomalous tropical convection driven by the MJO and the Rossby wave train that propagates from the tropics to the extratropics that is primarily confined to the Australian sector. The confinement of the extratropical Rossby wave train to the Australian sector results from a combination of localization of the Rossby wave source to the north of Australia and localization of wave propagation stemming from the refractive characteristics of the mean state zonal wind, which does not support tropical-extratropical wave paths to the east of Australia. An extratropical wave source due to feedback from transient eddies acts as an effective source of the extratropical response to the south of Australia and for the wave train that impinges on South America.