Column Water Vapor Research Articles

Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns

Abstract. We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products https://doi.org/10.15770/EUM_SAF_AC_0048, AC SAF, 2023a; monthly products https://doi.org/10.15770/EUM_SAF_AC_0049, AC SAF, 2023b). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.

A pathway analysis method for quantifying the contributions of precipitation and potential evapotranspiration anomalies to soil moisture drought

Soil moisture drought, as one of the most important drought categories, is determined by both water supply (e.g., precipitation) and demand (e.g., potential evapotranspiration). To shed light on the underlying mechanisms driving soil moisture drought, the statistical multiple linear regression, machine learning, and modeling experiments methods have been pervasively used in early studies. However, these methods neglect the collinearity and interactions of climate variables, and thus cannot reflect the direct and indirect interaction of factors leading to soil moisture drought. To reveal the synergistic effects of water supply and demand on soil moisture drought, this study quantified the contributions of key drivers to the change of soil moisture drought by a path analysis method to exhibit the relationships between atmospheric movement state and soil moisture drought. Prior to applying the systematic path analysis model, we identified the spatial patterns of soil moisture droughts at different depths by using a state-of-art three-dimensional drought recognition method in China. Our results showed that precipitation deficits dominated the interannual variation of soil moisture drought while increasing potential evapotranspiration only had marginal intensification in drought. The response of soil moisture drought to potential evapotranspiration was magnified by drought deterioration, especially in basically severe drought conditions. The total column water vapor and the horizontal divergence of the vapor flux, as well as temperature, directly affected precipitation and potential evapotranspiration and led to soil moisture drought through various direct and indirect processes. This study highlighted that the interactions among precipitation, potential evapotranspiration, and atmospheric vapor movement state in space and time were important for understanding the drought development mechanisms.

Satellite observations of smoke–cloud–radiation interactions over the Amazon rainforest

Abstract. The Amazon rainforest routinely experiences intense and long-lived biomass burning events that result in smoke plumes that cover vast regions. The spatial and temporal extent of the plumes and the complex pathways through which they interact with the atmosphere have proved challenging to measure for purposes of gaining a representative understanding of smoke impacts on the Amazonian atmosphere. In this study, we use multiple collocated satellite sensors on board AQUA and TERRA platforms to study the underlying smoke–cloud–radiation interactions during the diurnal cycle. An 18-year time series for both morning and afternoon overpasses is constructed, providing collocated measurements of aerosol optical depth (AOD; column-integrated aerosol extinction), cloud properties, top-of-atmosphere radiative fluxes, precipitation, and column water vapour content from independent sources. The long-term time series reduces the impact of interannual variability and provides robust evidence that smoke significantly modifies the Amazonian atmosphere. Low loadings of smoke (AOD ≤ 0.4) enhance convective activity, cloudiness, and precipitation, but higher loadings (AOD > 0.4) strongly suppress afternoon convection and promote low-level cloud occurrence. Accumulated precipitation increases with convective activity but remains elevated under high smoke loadings, suggesting fewer but more intense convective cells. Contrasting morning and afternoon cloud responses to smoke are observed, in line with recent simulations. Observations of top-of-atmosphere radiative fluxes support the findings and show that the response of low-level cloud properties and cirrus coverage to smoke results in a pronounced and consistent increase in top-of-atmosphere outgoing radiation (cooling) of up to 50 W m−2 for an AOD perturbation of +1.0. The results demonstrate that smoke strongly modifies the atmosphere over the Amazon via widespread changes to the cloud field properties. Rapid adjustments work alongside instantaneous radiative effects to drive a stronger cooling effect from smoke than previously thought, whilst contrasting morning and afternoon responses of liquid and ice water paths highlight a potential method for constraining aerosol impacts on climate. Increased drought susceptibility, land use change, and deforestation will have important and widespread impacts on the region over the coming decades. Based on this analysis, we anticipate that further increases in anthropogenic fire activity will associated with an overall reduction in regional precipitation and a negative forcing (cooling) on the Earth's energy budget.

The Variations of Outgoing Longwave Radiation in East Asia and Its Influencing Factors

Outgoing longwave radiation (OLR) data are one of the key factors in studying the radiation balance of the earth–atmosphere system in East Asia. It is of great significance to explore the influence factors on OLR. This paper processes the data of nearly 19 years, from September 2002 to February 2022, and conducts in-depth research using the exponential smoothing method, empirical orthogonal decomposition (EOF), correlation analysis, and other methods. We found that the spatial distribution of OLR is zonal symmetry and gradually decreases with the increase of latitude. Using EOF analysis, it is found that the total variance contribution of the first four decomposed spatial features exceeds 70%, and the overall change trend of the four-time coefficients in the past 19 years all show a downward trend. OLR is positively correlated with total column water vapor (TCWV), air temperature (AT), and cloud top temperature (CTT), but negatively correlated with cloud top pressure (CTP). OLR has a similar spatial correlation distribution with TCWV and AT, while the spatial correlation between OLR and CTP is opposite to the first two parameters. In most parts of East Asia, the spatial correlation with CTT exceeds 0.8. The change in OLR value is affected by various meteorological parameters. In East Asia, the positive correlation between 30° N and 60° N is significantly affected by TCWV, AT, and CTT; and the negative correlation is more significantly affected by CTP. At 0–25° N, the positive correlation is significantly affected by CTP and CTT, while the negative correlation is significantly affected by TCWV and AT.

Enhanced ENSO-Unrelated Summer Variability in the Indo–Western Pacific under Global Warming

Abstract El Niño–Southern Oscillation (ENSO) is an important but not the only source of interannual variability over the Indo–western Pacific. Non-ENSO forced variability in the region has received recent attention because of the implications for rainy-season prediction. Using a 35-member CESM1 Large Ensemble (CESM-LE) and 30 CMIP6 models, this study shows that the ensemble means project intensified interannual variability for precipitation, low-level winds, and sea level pressure under global warming, associated with the enhanced large-scale anomalous anticyclone (AAC) over the tropical northwestern (NW) Pacific after the ENSO signal is removed. A decomposition based on the column water vapor budget reveals that enhanced precipitation variability is due to the increased background specific humidity. The resultant anomalous diabatic heating intensifies the AAC, which further strengthens the precipitation anomalies. Over the tropical NW Pacific, the wind-induced evaporative cooling on the southeastern flank of the AAC is countered by the increased shortwave radiation due to the strengthened precipitation reduction. Tropospheric temperature anomalies in the ensemble means show no significant change, suggesting no apparent change of the interbasin positive feedback between the AAC and northern Indian Ocean SST. Intermodel analysis based on CMIP6 reveals that models with a larger increase in ENSO-unrelated precipitation variability over the NW Pacific are associated with stronger background warming in the eastern equatorial Pacific, due to the modulated Walker and Hadley circulations.

Observation of an Extremely Dry Atmospheric Air Column above Bern

The water vapour column density or vertically integrated water vapour (IWV) ranges from about 8 mm in winter to about 25 mm in summer in Bern, Switzerland. However, there can be day episodes when IWV drops to 2 mm or even less so that the atmosphere is extremely dry. We selected an event in February 2021 when the tropospheric water radiometer TROWARA measured a mean IWV value of about 1.5 ± 0.2 mm for a time interval of about one day in Bern. The ECMWF reanalysis ERA5 indicated a slightly higher IWV value of about 2.2 ± 0.4 mm where the uncertainty is the standard deviation of IWV during the time of IWV depression. The ERA5 profiles of relative humidity and specific humidity during this episode are reduced by 50% and more compared to the monthly mean profiles. On a global map, it can be seen that Bern is within a mesoscale dry region on that day with descending wind. Back trajectory analysis gives the result that the dry air masses in Bern came from the North and the trajectories are descending in altitude so that dry air from the mid troposphere came into the lower troposphere. These descending air masses from the North explain the minimum of IWV observed in Bern on 13–14 February 2021. The surface climate in Switzerland was dominated by a cold wave at that time. At the same time, severe cold waves occurred in Greece and Northern America.

Global scaling of precipitation extremes using near-surface air temperature and dew point temperature

Global warming has altered the energy budget and water cycle processes of the land–atmosphere system, which has resulted in significant effects on precipitation extremes. Previous studies have identified a hook structure between near-surface temperature and precipitation extremes, in which extremes increase with temperature rises and decline thereafter. However, the underlying physical mechanisms of this association remain poorly understood. In this study, global-scale responses of precipitation extremes to near-surface air temperature (SAT) and dew point temperature (DPT) were quantified using the ERA5 reanalysis dataset. The results reveal a hook structure between precipitation extremes scaling and temperature, for both SAT and DPT, over many regions worldwide. The peak point temperature (T pp) ranges from 15 °C to 25 °C, increasing as latitude decreased. The association of precipitation extremes with SAT is negative in many areas in the tropics, whereas that with DPT is almost always positive; this suggests that moisture supply is the main factor limiting precipitation at higher surface temperatures. The hook structure and scaling rates incompatible with Clausius–Clapeyron scaling are associated with various factors including precipitation duration, total column water vapour, convective available potential energy, and relative humidity.

The Sensitivityof GPS Precipitable Water Vapor Jumps to Intense Precipitation Associated with Tropical Organized Convective Systems

The Global Positioning System (GPS) consists of a constellation of satellites that transmit radio frequency signals to many users with varied applications. For meteorological purposes, the based-ground GPS receivers can provide high-quality column or precipitable water vapor (PWV), as obtained by radiosondes, but with high temporal resolution and low cost. A dense GPS network containing 16 ground-based receivers was installed in Belém city, Brazil, during the period 2–29 June 2011. This network provides a unique opportunity to evaluate the sensitivityof rapid increases in GPS PWV (GPS PWV jumps to the intense precipitation often associated with tropical organized convective systems. Results reveal a characteristic timescale of water vapor convergence before GPS-PWV maximum, which can be used for indicating the occurrence of precipitation associated with organized convective systems. A PWV increase of 4 mm h−1 in a period of an hour or 30 min before the maximum peak GPS-PWV (a peak of at least 57 mm) was observed during organized convection events. The contingency table obtained indicates a probability of detection of 84% and a false alarm ratio of 25% to forecast precipitation events. These results obtained suggest that GPS-PWV jumps can be employed to predict the events associated with organized convection.

Realization of an efficient radiative cooling emitter with double layer inorganic SiO2 and TiO2 metamaterial

A novel double-layer thermal emitter consisting of inorganic SiO2 and TiO2 metamaterials is proposed and numerically investigated. It can achieve ultrahigh absorption of 96.42 % and 92.97 % in the first and second atmospheric transparency window simultaneously, which helps to achieve efficient radiative cooling. On the premise of obtaining high absorption, a comparative study on the design with and without the metal substrate has been conducted, verifying our simple design can be adopted without the metal substrate. Meanwhile, the high emissivity still persists under different incident angles, air mass and water vapor column. Under the influence of convection coefficients, a net cooling power of 164.39 W/m2 is achieved. Finally, we establish a steady heat balance system to mimic the thermal emitter and obtain an average temperature drop of 9.6℃ with the Jacobian iteration method. Therefore, our design with excellent cooling capacity may provide a new guidance in the application of radiative cooling device.

TROPOMI/S5P Total Column Water Vapor validation against AERONET ground-based measurements

Abstract. Water vapor plays an important role in the greenhouse effect, rendering it an atmospheric constituent that requires continuous and global monitoring by different types of remote sensing instruments. The TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI/S5P) Total Column Water Vapor (TCWV) is a new product retrieved from the visible blue spectral range (435–455 nm), using an algorithm that was originally developed for the GOME-2/MetOp sensors. For the purposes of this work, 2.5 years of continuous satellite observations at high spatial resolution are validated against co-located (in space and in time) precipitable water Level 2.0 (quality-assured) ground-based measurements from the NASA AERONET (AErosol RObotic NETwork). The network uses Cimel Sun photometers located at approximately 1300 stations globally to monitor precipitable water among other products. Based on data availability, 369 of the stations were used in this study. The two datasets, satellite- and ground-based, were co-located, and the relative differences of the comparisons were calculated and statistically analyzed. The Pearson correlation coefficient of the two products is found to be 0.91, and the mean bias of the overall relative percentage differences is of the order of −2.7 %. For the Northern Hemisphere midlatitudes (30–60∘ N), where the density of the ground-based stations is high, the mean relative bias was found to be −1.8 %, while in the tropics (±15∘) the TROPOMI TCWV product has a relative dry bias of up to −10 %. The effect of various algorithm and geophysical parameters, such as air mass factor, solar zenith angle, clouds and albedo, is also presented and discussed. It was found that the cloud properties affect the validation results, leading the TCWV to a dry bias of −20 % for low cloud heights (cloud top pressure (CTP) >800 hPa). Moreover, cloud albedo introduces a wet bias of 15 % when it is below 0.3 and a dry bias up to −25 % when the clouds are more reflective. Overall, the TROPOMI/S5P TCWV product, on a global scale and for moderate albedo and cloudiness, agrees well at -2.7±4.9 % with the AERONET observations but probably within about −8 % to −13 % with respect to the “truth”.

Comparisons of simulated radiation, surface wind stress and SST fields over tropical pacific by the GISS CMIP6 versions of global climate models with observations

This study compares the overall performance between versions 2.1 and 3 of National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) global climate models (referred to as GISS-E2.1 and GISS-E3, respectively), in simulating the present-day Pacific climate using the CMIP6 protocol. Model physical representations and configurations are extensively changed from GISS-E2.1 to GISS-E3, which result in greatly reduced discrepancies, including ice water path (IWP), ice water content (IWC), radiative fluxes, surface wind stress (TAU), sea surface temperature (SST), precipitation (PR) and column water vapor (PRW), relative to satellite-based observational products over south Pacific oceans. Cloud only IWP (CIWP) shows the largest change, decreasing biases from ∼400 g kg−1 in GISS-E2.1 to 10–20 g kg−1 in GISS-E3. The combination of improved CIWP and the inclusion of snow in GISS-E3 may play roles on reducing overestimated outgoing longwave radiation, overestimated reflected shortwave at the top of atmosphere, and underestimated surface downward shortwave in GISS-E2.1. Both models’ intertropical convergence zones (ITCZs) are, however, located far too north of the equator, as found in radiative fluxes, PR and PRW but not in SST relative to observations. This introduces biases in TAU, PR and PRW over north flank of the equator and north Pacific. Over south Pacific, especially the trade wind regions, the improvements of radiation fluxes, SST, PR and PRW appear to be due to improved TAU associated with inclusion of snow-radiative effects. In particular, GISS-E3 reduces a longstanding too warm SST bias over trade-wind regions, from 4 K in GISS-E2.1 to within 0.5 K, and too cold SST bias over north Pacific Ocean. Although GISS-E3 shows improved geographic patterns of the simulated fields in particular over south Pacific oceans compared to GISS-E2.1, our results suggest that the location of ITCZ needs to be further improved.

Improved Algorithm to Derive All-Sky Longwave Downward Radiation From Space: Application to Fengyun-4A Measurements

Longwave downward radiation (LWDR) is an important parameter that modulates the earth’s radiation and energy balance, and is also a key variable that affects the global warming. Currently, although many reanalysis LWDR products and satellite-based algorithms are available, their coarse spatio-temporal resolutions as well as the difficulties in organizing the corresponding driving parameters seriously limit their applications. As China’s new generation geostationary satellite, Fengyun-4A (FY-4A) provides higher spatial and temporal resolutions (4 km @nadir, 15min at full disk mode) at longwave infrared channels which can routinely monitor the changes of the earth’s radiation in near real-time and therefore provide great potentials in generating various high-accuracy radiation products. Unfortunately, the existing official LWDR products of FY-4A can only provide estimates under clear skies, and its accuracy still has much room for improvement. For above-mentioned points, an improved general all-sky parameterization algorithm is proposed based on readily available input variables, such as land surface temperature (LST), column water vapor (CWV) and cloud-top temperature (CTT). Then the new algorithm is applied to FY-4A aiming to derive believable all-sky LWDR. The validation results show that, the new algorithm does show a noticeable improvement over the original one by reducing the relatively large errors in LWDR under conditions of extremely cold and dry (flux range <150 W/m²), as well as the large bias in the polar and high altitude regions. Moreover, the new method can generate more reliable LWDR than that of FY-4A official product in terms of both spatio-temporal continuity and accuracy, with RMSE less than 22 W/m² and bias less than 0.5 W/m² under all-sky conditions. The easy-to-use and believable performance of the new algorithm provide an opportunity to accurately derive all-sky LWDR from FY-4A and similar satellite missions with high resolutions.

Horizontal small-scale variability of water vapor in the atmosphere: implications for intercomparison of data from different measuring systems

Abstract. Water vapor concentration structures in the atmosphere are well approximated horizontally by Gaussian random fields at small scales (≲6 km). These Gaussian random fields have a spatial correlation in accordance with a structure function with a two-thirds slope, following the corresponding law from Kolmogorov's theory of turbulence. This is proven by showing that the horizontal structure functions measured by several satellite instruments and radiosonde measurements do indeed follow the two-thirds law. High-spatial-resolution retrievals of total column water vapor (TCWV) obtained from the Ocean and Land Color Instrument (OLCI) on board the Sentinel-3 series of satellites also qualitatively show a Gaussian random field structure. As a consequence, the atmosphere has an inherently stochastic component associated with the horizontal small-scale water vapor features, which, in turn, can make deterministic forecasting or nowcasting difficult. These results can be useful in areas where high-resolution modeling of water vapor is required, such as the estimation of the water vapor variance within a region or when searching for consistency between different water vapor measurements in neighboring locations. In terms of weather forecasting or nowcasting, the water vapor horizontal variability could be important in estimating the uncertainty of the atmospheric processes driving convection.

Changes in Aerosols, Meteorology, and Radiation in the Southeastern U.S. Warming Hole Region during 2000 to 2019

Abstract Surface air temperatures in the southeastern United States that did not change from the climatological mean from 1900 to 2000 have increased since the year 2000. Analyzed herein are factors modulating the surface air temperatures in the region for a 20-yr period (2000–19) using space- and surface-based observations, and output from a reanalysis model. The 20-yr period is segregated into two decades, 2000–09 and 2010–19, corresponding to different tropospheric chemical regimes. Changes in seasonal and decadal averages are examined. The later decade experienced higher average surface air temperatures with significant warming during summer and fall seasons. Decadal and seasonal averages of cloud properties, column water vapor, rain rates, and top-of-atmosphere outgoing longwave radiation did not exhibit statistically significant differences between the two decades. The region experienced strong warm and moist advection during the winter months and very weak advection during the summer months. The later decade exhibited higher low-level moisture advection during the winter months than the earlier decade with insignificant changes in the temperature advection between the two decades. The later decade had significantly lower aerosol dry and liquid water mass during all seasons, along with lower aerosol optical depth, higher single scattering albedo, and lower top-of-the-atmosphere outgoing shortwave radiation during cloud-free conditions in the summer season. Collectively, these results suggest that changes in the aerosol direct radiative forcing are responsible for warming during summer months that experience weak advection and highlight seasonal differences in the temperature controlling mechanisms in the region.

Global precipitation system scale increased from 2001 to 2020

How precipitation responds to global warming has drawn much interest from the scientific community. However, as one of the important properties of precipitation, changes in the precipitation system scale have rarely been studied. The latest retrospective merged satellite precipitation product has provided a great opportunity to investigate quasi-global precipitation system scale changes. This study uses the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) data during 2001–2020 to investigate quasi-global precipitation system scale changes. Our results indicate that, generally, quasi-global precipitation system scales exhibit a significant increasing trend, which is more significant in winter and spring than that in summer and autumn over both hemispheres. The scale of nearly all precipitation systems over land regions has increased over the last two decades. In oceanic regions, precipitation system scales increase over tropical oceans but decrease over subtropical oceans. Medium-scale precipitation systems (100–1000 km) significantly increase in scale and decrease in frequency, while large-scale precipitation systems significantly increase in frequency, which both lead to a quasi-global increase in the precipitation system scale. Diagnostic investigation based on atmospheric analysis reveals that an increase in atmospheric stability tends to suppress local convective precipitation, while an increase in the total column water vapor could help maintain and enhance precipitation system scale, which jointly contribute to quasi-global precipitation system scale increase.

Non-linear intensification of monsoon low-pressure systems by the BSISO

Abstract. More than half of the rainfall brought to the Indian subcontinent by the summer monsoon is associated with low-pressure systems (LPSs). Yet their relationship with the boreal summer intraseasonal oscillation (BSISO) – the dominant intraseasonal forcing on the monsoon – is only superficially understood. Using reanalysis data, we explore the relationship between the BSISO and LPS intensity, propagation and precipitation, and associated underlying mechanisms. The BSISO has a large impact on mean monsoon vorticity and rainfall as it moves northward – maximising both in phases 2–3 over southern India and phases 5–6 over northern India – but a much weaker relationship with total column water vapour. We present evidence that LPS genesis also preferentially follows these phases of the BSISO. We identify significant relationships between BSISO phase and LPS precipitation and propagation: for example, during BSISO phase 5, LPSs over northern India produce 51 % heavier rainfall and propagate northwestward 20 % more quickly. Using a combination of moisture flux linearisation and quasi-geostrophic theory, we show that these relationships are driven by changes to the underlying dynamics rather than the moisture content or thermodynamic structure of the monsoon. Using the example of LPSs over northern India during BSISO phase 5, we show that the vertical structure of anomalous vorticity can be split into contributions from the BSISO background circulation and the non-linear response of the LPS to anomalous BSISO circulation. Complementary hypotheses emerge about the source of this non-linear vorticity response: non-linear frictional convergence and secondary barotropic growth. We show that both are important. The BSISO imparts greater meridional shear on the background state, supporting LPS intensification. The BSISO background and non-linear LPS response both contribute significantly to anomalous boundary layer convergence, and we show through vortex budget arguments that the former supports additional LPS intensification in boundary layer, while the latter supports faster westward propagation. This work therefore yields important insights into the scale interactions controlling one of the dominant synoptic systems contributing to rainfall during the monsoon.

Deep neural network-based spatial gap-filling of MODIS ice surface temperatures over the Arctic using satellite and reanalysis data

ABSTRACT Because ice surface temperature (IST) controls snow melt, sea ice growth and air–ocean heat exchange, it is a key parameter in analyses of the Arctic climate system. However, optical satellite-based IST data often have missing values due to the satellite orbit, clouds and polar night. In this study, we estimated IST using a deep neural network (DNN) algorithm based on meteorological, sea ice and geometric variables that are strongly correlated with IST. Moderate-Resolution Imaging Spectroradiometer (MODIS)/Terra IST data were used, and the input data were 2 m air temperature (Ta), 30-year averaged Ta (Ta climatology), total column water vapour (TCWV), solar zenith angle (SZA), local solar noon angle (LSN) and latitude. The data were classified into six cases according to sea ice age (SIA) and Ta to create an efficient DNN model that supplemented the IST data missing from the existing dataset. Model validation based on the MODIS IST data revealed a correlation coefficient of 0.94, root mean square error of 3.54 K and relative root mean square error of 1.35%, showing high accuracy.

Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI

Abstract. Mitigating the impact of atmospheric effects on optical remote sensing data is critical for monitoring intrinsic land processes and developing Analysis Ready Data (ARD). This work develops an approach to this for the NERC NCEO medium resolution ARD Landsat 8 (L8) and Sentinel 2 (S2) products, called Sensor Invariant Atmospheric Correction (SIAC). The contribution of the work is to phrase and solve that problem within a probabilistic (Bayesian) framework for medium resolution multispectral sensors S2/MSI and L8/OLI and to provide per-pixel uncertainty estimates traceable from assumed top-of-atmosphere (TOA) measurement uncertainty, making progress towards an important aspect of CEOS ARD target requirements. A set of observational and a priori constraints are developed in SIAC to constrain an estimate of coarse resolution (500 m) aerosol optical thickness (AOT) and total column water vapour (TCWV), along with associated uncertainty. This is then used to estimate the medium resolution (10–60 m) surface reflectance and uncertainty, given an assumed uncertainty of 5 % in TOA reflectance. The coarse resolution a priori constraints used are the MODIS MCD43 BRDF/Albedo product, giving a constraint on 500 m surface reflectance, and the Copernicus Atmosphere Monitoring Service (CAMS) operational forecasts of AOT and TCWV, providing estimates of atmospheric state at core 40 km spatial resolution, with an associated 500 m resolution spatial correlation model. The mapping in spatial scale between medium resolution observations and the coarser resolution constraints is achieved using a calibrated effective point spread function for MCD43. Efficient approximations (emulators) to the outputs of the 6S atmospheric radiative transfer code are used to estimate the state parameters in the atmospheric correction stage. SIAC is demonstrated for a set of global S2 and L8 images covering AERONET and RadCalNet sites. AOT retrievals show a very high correlation to AERONET estimates (correlation coefficient around 0.86, RMSE of 0.07 for both sensors), although with a small bias in AOT. TCWV is accurately retrieved from both sensors (correlation coefficient over 0.96, RMSE &lt;0.32 g cm−2). Comparisons with in situ surface reflectance measurements from the RadCalNet network show that SIAC provides accurate estimates of surface reflectance across the entire spectrum, with RMSE mismatches with the reference data between 0.01 and 0.02 in units of reflectance for both S2 and L8. For near-simultaneous S2 and L8 acquisitions, there is a very tight relationship (correlation coefficient over 0.95 for all common bands) between surface reflectance from both sensors, with negligible biases. Uncertainty estimates are assessed through discrepancy analysis and are found to provide viable estimates for AOT and TCWV. For surface reflectance, they give conservative estimates of uncertainty, suggesting that a lower estimate of TOA reflectance uncertainty might be appropriate.

Impact of cloud and total column water vapor on annual performance of passive daytime radiative cooler

The surface temperature of a passive daytime radiative cooler (PDRC) can be lower than the ambient temperature without consuming any extra energy. Thus, the technology of the PDRC has attracted the attention of researchers recently. However, most current studies only focused on the short-term performance of the PDRC during sunny and cloudless days. The influence of clouds and variations of atmosphere total column water vapor on the long-term performance of PDRC have not been investigated in previous research. In this study, a radiative cooling model considering the influence of total column water vapor and clouds was developed for PDRC, and TMY weather data files with total column water vapor were generated for estimating the annual performance of PDRC in five selected major climate zones in China. The results showed that the high total column water vapor would deteriorate the performance of the PDRC. Considering the impact of cloud or not, the difference in potential of achieving sub-ambient cooling during daytime annually ranged from 12.68 % to 43.35 % in five cities, i.e., Harbin, Beijing, Shanghai, Kunming, and Guangzhou. The results also indicated that the selective PDRC always achieved a slightly better performance than the broadband one. Finally, the potential of applying PDRC in five selected cities was estimated. The results demonstrated that the PDRC could yield satisfying performance in Beijing, Shanghai, Guangzhou, and Kunming, with the energy-saving potential of 39.53 kWh/m2, 221.40 kWh/m2, 435.82 kWh/m2, 97.26 kWh/m2, respectively.

Convective Couplings with Equatorial Rossby Waves and Equatorial Kelvin Waves. Part II: Coupled Precipitation Characteristics

Abstract Detailed precipitation characteristics coupled with equatorial Rossby and Kelvin waves are investigated. We prepare a rainfall event dataset using the Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) level 2 data. Utilizing three indices, area size, maximum echo-top height, and stratiform precipitation ratio, rainfall events are classified into mesoscale convective system (MCS), deep, congestus, and shallow convective events, and “other” type. We perform composite analyses based on the wave phase defined in Part I. Precipitation amount in Rossby waves is in phase with column water vapor (CWV) anomalies and is mainly contributed by MCSs, which are simultaneously activated with deep convection. The large CWV can support deep development and organization of convection. Shallow and congestus convective events indicate their peaks just before the active phase on 10°N or in the later part of the convectively suppressed phase on the equator. A five-step evolution is shown in Kelvin waves. In the first stage, shallow convective events are triggered by high SST, followed by a dominance of congestus convective events. Then, in the developing stage, deep convective events become dominant. In the mature stage, heavy precipitation is contributed by MCSs, and mostly stratiform rain is maximized at later stages. Kelvin waves indicate relatively weak connection to CWV fluctuation. Although contrasted evolutions are indicated, large contributions by MCSs to precipitation amount are common among the two coupled waves. This is considered to result in the commonality of the equivalent depths with their top-heavy heating. Significance Statement A coupling mechanism between equatorial waves and convective activity is a key issue in the tropical meteorology. While many previous idealized studies suggested some instability mechanisms, detailed precipitation characteristics is not enough investigated. We prepare rainfall-event dataset observed from a spaceborne Precipitation Radar on board the TRMM satellite to quantify detailed precipitation characteristics statistically and compare equatorial Rossby waves and equatorial Kelvin waves. We found that organized convective systems and deep convection are simultaneously activated in the Rossby waves and a clear transition of convective activity is shown in the Kelvin waves. These characteristics highly correspond to waves’ synoptic-scale structures. Our observational results of detailed evolutions of rainfall events will improve understanding of coupling processes.