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The biophysical effects of forests on climate have been extensively studied with climate models. However, models cannot accurately reproduce local climate effects due to their coarse spatial resolution and uncertainties, and field observations are valuable but often insufficient due to their limited coverage. Here we present new evidence acquired from global satellite data to analyse the biophysical effects of forests on local climate. Results show that tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually; and boreal forests have strong warming in winter and moderate cooling in summer with net warming annually. The spatiotemporal cooling or warming effects are mainly driven by the two competing biophysical effects, evapotranspiration and albedo, which in turn are strongly influenced by rainfall and snow. Implications of our satellite-based study could be useful for informing local forestry policies. Local climatic effects of forests remain poorly understood due to the coarse spatial resolution of models and field observations. Here, the authors use global satellite data to analyse the spatiotemporal cooling or warming effects of tropical, temperate and boreal forests on climate.

Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse ecosocial impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. The authors have developed a method to generate a near-real-time remotely sensed drought severity index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly, and annual frequencies. The new DSI integrates and exploits information from current operational satellite-based terrestrial evapotranspiration (ET) and vegetation greenness index [normalized difference vegetation index (NDVI)] products, which are sensitive to vegetation water stress. Specifically, this approach determines the annual DSI departure from its normal (2000–11) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (correlation coefficient r = 0.43) with the precipitation-based Palmer drought severity index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite-based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely sensed global terrestrial DSI enhances capabilities for nearreal-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

The VIIRS instrument on the JPSS-2 (renamed NOAA-21 upon reaching orbit) spacecraft was launched in November 2022, making it the third sensor in the VIIRS series, following those onboard the SNPP and NOAA-20 spacecrafts, which are operating nominally. As a multi-disciplinary instrument, the VIIRS provides the worldwide user community with high-quality imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. This study provides an early assessment of the calibration stability and radiometric consistency of the NOAA-21 VIIRS RSBs using the latest NASA SIPS C2 L1B products. Vicarious approaches are employed, relying on reflectance data obtained from the Libya-4 desert and Dome C sites, deep convective clouds, and simultaneous nadir overpasses, as well as intercomparison with the first two VIIRS instruments using MODIS as a transfer radiometer. The impact of existing band spectral differences on sensor-to-sensor comparison is corrected using scene-specific a priori hyperspectral observations from the SCIAMACHY sensor onboard the ENVISAT platform. The results indicate that the overall radiometric performance of the newly launched NOAA-21 VIIRS is quantitatively comparable to the NOAA-20 for the VIS and NIR bands. For some SWIR bands, the measured reflectances are lower by more than 2%. An upward adjustment of 6.1% in the gain of band M11 (2.25 µm), based on lunar intercomparison results, generates more consistent results with the NOAA-20 VIIRS.

The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key instruments on the recently launched NOAA-21 (previously known as JPSS-2) satellite. The VIIRS, like its predecessors on the SNPP and NOAA-20 satellites, provides daily global coverage in 22 spectral bands from 412 nm to 12 μm. The geometrically and radiometrically calibrated observations are the basis for many operational applications and scientific research studies. A total of 14 of the 22 bands are reflective solar bands (RSBs), covering photon wavelengths from 412 nm to 2.25 μm. The RSBs were radiometrically calibrated prelaunch and have been regularly calibrated on orbit through the onboard solar diffuser (SD) and scheduled lunar observations. The on-orbit SD’s reflectance change is determined by the onboard solar diffuser stability monitor (SDSM). We review the calibration algorithms and present the early mission performance of the NASA N21 VIIRS RSBs. Using the calibration data collected at both the yaw maneuver and regular times, we derive the screen transmittance functions. The visible and near-infrared bands’ radiometric gains have been stable, nearly independent of time, and so were the radiometric gains of the shortwave-infrared bands after the second mid-mission outgassing. Further, we assess the Earth-view striping observed in the immediate prior collection (Collection 2.0) and apply a previously developed algorithm to mitigate the striping. The N21 VIIRS RSB detector signal-to-noise ratios are all above the design values with large margins. Finally, the uncertainties of the retrieved Earth-view top-of-the-atmosphere spectral reflectance factors at the respective typical spectral radiance levels are estimated to be less than 1.5% for all the RSBs, except band M11 whose reflectance factor uncertainty is 2.2%.

Two MODIS sensors onboard the Terra and Aqua spacecraft have been successfully operating for over twenty-three and twenty-one years, respectively, providing the worldwide user community with high-quality imagery and radiometric Earth observations of the land, atmosphere, cryosphere, and oceans. This study provides an assessment of the radiometric calibration stability and consistency of Terra and Aqua MODIS RSB using the L1B from the upcoming Collection 7 release. Several independent vicarious approaches based on measurements from the Libya-4 desert, Dome C, DCC, and SNO are used to assess the calibration stability at the beginning of scan, nadir, and end of scan. Results indicate that both Terra and Aqua RSB are stable to within 1% over their mission periods. Comparison of the normalized reflectances with either a BRDF model or a common reference sensor provides a radiometric assessment of Terra and Aqua calibration consistency. Comparison results show the VIS/NIR bands are in good agreement around the nadir and at the beginning of the scan for all the approaches. For cases at the end of the scan, the agreement varies depending on the approach but is typically within ±2%. The differences observed in the SWIR bands are slightly larger than the VIS/NIR bands, which are likely due to their high sensitivity to atmospheric conditions and relatively larger electronic crosstalk impact on the Terra instrument.

We developed a water‐centric monthly scale simulation model (WaSSI‐C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI‐C model was evaluated with basin‐scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE) estimates by multiple independent methods across 2103 eight‐digit Hydrologic Unit Code watersheds in the conterminous United States from 2001 to 2006. Our results indicate that WaSSI‐C captured the spatial and temporal variability and the effects of large droughts on key ecosystem fluxes. Our modeled mean (±standard deviation in space) ET (556 ± 228 mm yr−1) compared well to Moderate Resolution Imaging Spectroradiometer (MODIS) based (527 ± 251 mm yr−1) and watershed water balance based ET (571 ± 242 mm yr−1). Our mean annual GEP estimates (1362 ± 688 g C m−2 yr−1) compared well (R2 = 0.83) to estimates (1194 ± 649 g C m−2 yr−1) by eddy flux‐based EC‐MOD model, but both methods led significantly higher (25–30%) values than the standard MODIS product (904 ± 467 g C m−2 yr−1). Among the 18 water resource regions, the southeast ranked the highest in terms of its water yield and carbon sequestration capacity. When all ecosystems were considered, the mean NEE (−353 ± 298 g C m−2 yr−1) predicted by this study was 60% higher than EC‐MOD's estimate (−220 ± 225 g C m−2 yr−1) in absolute magnitude, suggesting overall high uncertainty in quantifying NEE at a large scale. Our water‐centric model offers a new tool for examining the trade‐offs between regional water and carbon resources under a changing environment. Key Points A monthly scale water‐centric model developed Examined spatial and temporal dynamics of carbon and water fluxes Growing season precipitation critical to GEP and NEE

Evapotranspiration (ET), or the sum of water released to the atmosphere from ground surfaces, intercepts canopy precipitation through evaporation and plant transpiration and is one of the most significant components in the water cycle. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) 16 global terrestrial ET products were validated at 17 flux tower locations in Asia. Overall, overestimations due to energy balance misclosure distorted the trend of the data at nine locations [r: 0.27–0.82; bias: −21.41–2.38 mm 8-d −1 ; Root Mean Square Error (RMSE): 6.12–21.81 mm 8-d −1 ]. Regardless of variation in the scattering patterns, good agreements between MODIS-based ET and ET measured at the flux towers were observed at five locations (r: 0.50–0.76; bias: −1.42–1.99 mm 8-d −1 ; RMSE: 1.99–8.96 mm 8-d −1 ). Underestimation at one site (r = 0.28, bias = −17.00 mm 8-d −1 , RMSE = 17.41 mm 8-d −1 ) was accompanied by mismatches at two sites (r = 0.12–0.18; bias = −4.19 — −0.04 mm 8-d −1 , RMSE = 5.76–7.66 mm 8-d −1 ). The best performances of the MOD16 ET algorithm were observed at sites with forested land cover, but no substantial differences were found under a variety of climate conditions. This study is the first comprehensive trial to validate global terrestrial MODIS ET in Asia, showing that a MODIS global terrestrial ET product can estimate actual ET with reasonable accuracy. We believe that our results can be used as baseline ET values for satellite image-based ET mapping research in South Korea.

Two VIIRS sensors onboard the SNPP and NOAA20 satellites have been successfully operating for over 10 and 4 years, respectively, providing the worldwide user community with high-quality imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. This study provides a temporal radiometric stability and calibration consistency assessment of the SNPP and NOAA20 VIIRS reflective solar bands using the latest NASA SIPS C2 L1B products. Several independent vicarious approaches are used to examine the stability of SNPP VIIRS and consistency of the at-sensor reflectance between the two VIIRS instruments. These approaches include observations from simultaneous nadir overpasses, the Libya-4 desert and Dome C snow/ice sites, and deep convective clouds. The impact of existing band spectral differences on the reflectance measurements is accounted for utilizing scene-specific hyperspectral observations provided by the SCIAMACHY sensor onboard the ENVISAT platform. Results indicate that both SNPP and NOAA20 VIIRS reflectances are stable within 1% over their mission periods for all bands, except for a few bands in the visible range from SNPP VIIRS that show more upward drifts at high radiances. NOAA20 VIIRS reflectances are systematically lower than SNPP by 2 to 4% for most bands, with the exception of few short wavelength bands where it is seen to be up to 7%.

MODIS reflective solar bands are calibrated on-orbit using a solar diffuser and near-monthly lunar observations. To monitor the performance and effectiveness of the on-orbit calibrations, pseudo-invariant targets such as deep convective clouds (DCCs), Libya-4, and Dome-C are used to track the long-term stability of MODIS Level 1B product. However, the current MODIS operational DCC technique (DCCT) simply uses the criteria set for the 0.65- m band. We optimize several critical DCCT parameters including the 11- micrometer IR-band Brightness Temperature (BT11) threshold for DCC identification, DCC core size and uniformity to help locate DCCs at convection centers, data collection time interval, and probability distribution function (PDF) bin increment for each channel. The mode reflectances corresponding to the PDF peaks are utilized as the DCC reflectances. Results show that the BT11 threshold and time interval are most critical for the Short Wave Infrared (SWIR) bands. The Bidirectional Reflectance Distribution Function model is most effective in reducing the DCC anisotropy for the visible channels. The uniformity filters and PDF bin size have minimal impacts on the visible channels and a larger impact on the SWIR bands. The newly optimized DCCT will be used for future evaluation of MODIS on-orbit calibration by MODIS Characterization Support Team.

The soil moisture and evapotranspiration (ET) influence on ecosystem dynamics has been studied only in a limited way owing to the lack of large-scale measurements. The Normalized Difference Vegetation Index (NDVI) data retrieved using the Moderate Resolution Imaging Spectroradiometer (MODIS) was successfully used in this study to identify the ecological relationships that involve soil moisture and ET at 132 sites located on different continents around the world. Optimal relationships exist between NDVI and soil moisture within time lags of 10 days at forest and grassland sites, and 25 days at cropland and shrub land sites. The ecological correlations between NDVI and the hydrological variables are affected mainly by the land-cover type. The densely vegetated areas show shorter time lags for NDVI to ET owing to canopy evaporation and plant transpiration, which are almost simultaneous with NDVI.