Data for 2019
Climate Readiness (ND-GAIN), 2019
2019, as ND-GAIN’s 2026 release gives it · stored as published, never rewritten
Climate Readiness (ND-GAIN), 2019 covers 192 countries. Singapore is highest, at 0.81126; Central African Republic is lowest, at 0.13096. The middle country reads 0.41007. Against 2018, 192 values changed (109 up, 83 down), the same countries are covered.
Climate Readiness (ND-GAIN) · Data for 2019
HighestSingapore
0.81126LowestCentral African Republic
0.13096Shaded by value in five groups of equal size, darkest at the better end.
01ND-GAIN’s rank
The table
Every country and every column of Climate Readiness (ND-GAIN), 2019, as published. The rank is ND-GAIN’s own, as printed. “=” marks a shared position.
Showing 25 of 192 countries · select a heading to sort
| 1 | SGPSouth-eastern Asia | 0.81126 |
| 2 | DNKNorthern Europe | 0.79236 |
| 3 | NORNorthern Europe | 0.78379 |
| 4 | MCOWestern Europe | 0.78253 |
| 5 | FINNorthern Europe | 0.76815 |
| 6 | SWENorthern Europe | 0.74662 |
| 7 | KOREastern Asia | 0.73646 |
| 8 | ISLNorthern Europe | 0.73302 |
| 9 | CHEWestern Europe | 0.71823 |
| 10 | NZLAustralia and New Zealand | 0.71031 |
| =11 | DEUWestern Europe | 0.70900 |
| =11 | GBRNorthern Europe | 0.70861 |
| 13 | JPNEastern Asia | 0.70422 |
| 14 | AUTWestern Europe | 0.70294 |
| 15 | AUSAustralia and New Zealand | 0.70124 |
| 16 | NLDWestern Europe | 0.70035 |
| 17 | LUXWestern Europe | 0.68505 |
| 18 | FRAWestern Europe | 0.67351 |
| 19 | USANorthern America | 0.66158 |
| 20 | CANNorthern America | 0.66119 |
| 21 | LIEWestern Europe | 0.64779 |
| 22 | ESTNorthern Europe | 0.64467 |
| 23 | SMRSouthern Europe | 0.64045 |
| 24 | IRLNorthern Europe | 0.61289 |
| 25 | SVNSouthern Europe | 0.60978 |
| 26 | LTUNorthern Europe | 0.60865 |
| 27 | BELWestern Europe | 0.60331 |
| 28 | AREWestern Asia | 0.59844 |
| 29 | PRTSouthern Europe | 0.59158 |
| 30 | LVANorthern Europe | 0.59024 |
| 31 | GEOWestern Asia | 0.57903 |
| 32 | MUSEastern Africa | 0.57291 |
| 33 | CZEEastern Europe | 0.56801 |
| 34 | ANDSouthern Europe | 0.56293 |
| =35 | NRUMicronesia | 0.55820 |
| =35 | POLEastern Europe | 0.55760 |
| =35 | KNACaribbean | 0.55786 |
| 38 | ESPSouthern Europe | 0.54964 |
| 39 | ISRWestern Asia | 0.54857 |
| 40 | CHLSouth America | 0.54737 |
| 41 | CYPWestern Asia | 0.54169 |
| 42 | CHNEastern Asia | 0.53961 |
| 43 | RUSEastern Europe | 0.53303 |
| =44 | GRCSouthern Europe | 0.53099 |
| =44 | ITASouthern Europe | 0.53055 |
| =46 | BRBCaribbean | 0.52776 |
| =46 | BRNSouth-eastern Asia | 0.52804 |
| =46 | MYSSouth-eastern Asia | 0.52803 |
| 49 | GRDCaribbean | 0.52227 |
| =50 | DMACaribbean | 0.51780 |
| =50 | QATWestern Asia | 0.51772 |
| 52 | ARMWestern Asia | 0.51527 |
| 53 | BLREastern Europe | 0.51099 |
| 54 | SAUWestern Asia | 0.50792 |
| =55 | OMNWestern Asia | 0.50670 |
| =55 | URYSouth America | 0.50732 |
| 57 | SVKEastern Europe | 0.50593 |
| 58 | MLTSouthern Europe | 0.50395 |
| 59 | HUNEastern Europe | 0.50117 |
| 60 | VCTCaribbean | 0.49899 |
| 61 | HRVSouthern Europe | 0.49635 |
| 62 | PLWMicronesia | 0.49442 |
| 63 | FJIMelanesia | 0.49195 |
| 64 | SYCEastern Africa | 0.48774 |
| 65 | KAZCentral Asia | 0.48687 |
| 66 | MNESouthern Europe | 0.48555 |
| 67 | THASouth-eastern Asia | 0.47861 |
| =68 | ROUEastern Europe | 0.47468 |
| =68 | TURWestern Asia | 0.47523 |
| 70 | BGREastern Europe | 0.47426 |
| =71 | BHRWestern Asia | 0.47009 |
| =71 | BTNSouthern Asia | 0.47010 |
| =71 | CRICentral America | 0.46959 |
| 74 | MKDSouthern Europe | 0.46452 |
| 75 | ATGCaribbean | 0.45491 |
| 76 | SRBSouthern Europe | 0.45286 |
| 77 | CPVWestern Africa | 0.44807 |
| 78 | TUNNorthern Africa | 0.44708 |
| 79 | LCACaribbean | 0.44613 |
| =80 | BHSCaribbean | 0.44292 |
| =80 | WSMPolynesia | 0.44266 |
| 82 | AZEWestern Asia | 0.44094 |
| 83 | MNGEastern Asia | 0.43925 |
| 84 | MARNorthern Africa | 0.43239 |
| =85 | SLBMelanesia | 0.42534 |
| =85 | VNMSouth-eastern Asia | 0.42484 |
| =87 | BWASouthern Africa | 0.42363 |
| =87 | TONPolynesia | 0.42437 |
| 89 | TUVPolynesia | 0.42271 |
| =90 | MHLMicronesia | 0.42182 |
| =90 | MDAEastern Europe | 0.42163 |
| 92 | MDVSouthern Asia | 0.42123 |
| 93 | UKREastern Europe | 0.41868 |
| 94 | KWTWestern Asia | 0.41808 |
| 95 | ALBSouthern Europe | 0.41168 |
| 96 | PERSouth America | 0.41089 |
| 97 | JORWestern Asia | 0.40925 |
| 98 | LKASouthern Asia | 0.40826 |
| 99 | TLSSouth-eastern Asia | 0.40487 |
| 100 | PANCentral America | 0.40222 |
| 101 | RWAEastern Africa | 0.39760 |
| 102 | JAMCaribbean | 0.39276 |
| 103 | IDNSouth-eastern Asia | 0.39162 |
| 104 | IRNSouthern Asia | 0.38430 |
| 105 | NAMSouthern Africa | 0.37849 |
| 106 | KGZCentral Asia | 0.37674 |
| 107 | ARGSouth America | 0.37468 |
| 108 | COLSouth America | 0.37193 |
| 109 | KIRMicronesia | 0.37113 |
| 110 | MEXCentral America | 0.36839 |
| =111 | STPMiddle Africa | 0.36658 |
| =111 | VUTMelanesia | 0.36720 |
| =113 | BIHSouthern Europe | 0.36633 |
| =113 | UZBCentral Asia | 0.36647 |
| =115 | INDSouthern Asia | 0.36291 |
| =115 | ZAFSouthern Africa | 0.36306 |
| 117 | FSMMicronesia | 0.36165 |
| 118 | DOMCaribbean | 0.36000 |
| 119 | PRKEastern Asia | 0.35860 |
| 120 | SENWestern Africa | 0.35479 |
| 121 | TTOCaribbean | 0.35356 |
| =122 | SLVCentral America | 0.35202 |
| =122 | PRYSouth America | 0.35186 |
| 124 | GHAWestern Africa | 0.34826 |
| 125 | BRASouth America | 0.34450 |
| 126 | MRTWestern Africa | 0.34106 |
| =127 | BLZCentral America | 0.33922 |
| =127 | NPLSouthern Asia | 0.33862 |
| =129 | CUBCaribbean | 0.33700 |
| =129 | EGYNorthern Africa | 0.33701 |
| =129 | GUYSouth America | 0.33674 |
| 132 | DJIEastern Africa | 0.33615 |
| 133 | ECUSouth America | 0.33391 |
| 134 | BENWestern Africa | 0.33310 |
| 135 | PHLSouth-eastern Asia | 0.33246 |
| 136 | NERWestern Africa | 0.32985 |
| 137 | SURSouth America | 0.32910 |
| =138 | DZANorthern Africa | 0.32583 |
| =138 | GMBWestern Africa | 0.32559 |
| =138 | TGOWestern Africa | 0.32567 |
| 141 | SWZSouthern Africa | 0.31348 |
| =142 | GTMCentral America | 0.31231 |
| =142 | TJKCentral Asia | 0.31170 |
| =144 | GINWestern Africa | 0.31146 |
| =144 | LAOSouth-eastern Asia | 0.31141 |
| 146 | ZMBEastern Africa | 0.30710 |
| 147 | LBNWestern Asia | 0.30462 |
| 148 | LSOSouthern Africa | 0.30397 |
| 149 | SLEWestern Africa | 0.30124 |
| 150 | ETHEastern Africa | 0.29570 |
| 151 | TZAEastern Africa | 0.29548 |
| =152 | CIVWestern Africa | 0.28709 |
| =152 | PAKSouthern Asia | 0.28732 |
| 154 | MLIWestern Africa | 0.28640 |
| =155 | IRQWestern Asia | 0.28399 |
| =155 | KENEastern Africa | 0.28434 |
| 157 | KHMSouth-eastern Asia | 0.28244 |
| 158 | NICCentral America | 0.27970 |
| 159 | GABMiddle Africa | 0.27828 |
| =160 | COMEastern Africa | 0.27749 |
| =160 | PNGMelanesia | 0.27734 |
| 162 | LBRWestern Africa | 0.27620 |
| 163 | BFAWestern Africa | 0.27507 |
| 164 | BOLSouth America | 0.27365 |
| 165 | MMRSouth-eastern Asia | 0.27287 |
| =166 | MOZEastern Africa | 0.26808 |
| =166 | UGAEastern Africa | 0.26788 |
| 168 | MWIEastern Africa | 0.26637 |
| 169 | MDGEastern Africa | 0.26548 |
| =170 | BGDSouthern Asia | 0.26167 |
| =170 | GNBWestern Africa | 0.26169 |
| =170 | HNDCentral America | 0.26212 |
| 173 | BDIEastern Africa | 0.25374 |
| =174 | CMRMiddle Africa | 0.24867 |
| =174 | SDNNorthern Africa | 0.24876 |
| 176 | SOMEastern Africa | 0.24617 |
| 177 | YEMWestern Asia | 0.24529 |
| 178 | TKMCentral Asia | 0.24051 |
| 179 | AGOMiddle Africa | 0.24037 |
| 180 | GNQMiddle Africa | 0.23522 |
| 181 | SYRWestern Asia | 0.23099 |
| =182 | AFGSouthern Asia | 0.22826 |
| =182 | LBYNorthern Africa | 0.22825 |
| 184 | NGAWestern Africa | 0.22501 |
| 185 | HTICaribbean | 0.22242 |
| 186 | COGMiddle Africa | 0.20880 |
| 187 | ZWEEastern Africa | 0.20075 |
| 188 | CODMiddle Africa | 0.18805 |
| 189 | ERIEastern Africa | 0.18506 |
| 190 | VENSouth America | 0.17464 |
| 191 | TCDMiddle Africa | 0.16881 |
| 192 | CAFMiddle Africa | 0.13096 |
02In 2019
At either end
The 5 countries at each end of the headline.
Lowest
- #192
Central African Republic0.13096
- #191
Chad0.16881
- #190
Venezuela0.17464
- #189
Eritrea0.18506
- #188
DR Congo0.18805
A higher value is the better result. The middle country reads 0.41007. “Shared” marks a value another country also holds.
032018 → 2019
Since 2018
What changed between 2018 and this one: who joined or left, and how far the headline moved.
- +0 / −0countries joined / left
- 192values changed, of 192 in both
- 109 · 83rose · fell
- 0unchanged
Rose most
Monaco0.69473 → 0.78253+0.08780
China0.47245 → 0.53961+0.06716
Andorra0.53843 → 0.56293+0.02450
Azerbaijan0.41862 → 0.44094+0.02232
Türkiye0.45860 → 0.47523+0.01664
Fell most
New Zealand0.79099 → 0.71031−0.08067
Dominica0.53677 → 0.51780−0.01897
Malta0.51881 → 0.50395−0.01486
Poland0.57216 → 0.55760−0.01456
Norway0.79756 → 0.78379−0.01378
Both years come from the same release, so a difference here is a change in the data, not a revision of it. Every country’s full history is charted on the statistic page.
04Caveats
Read before you use
What this edition’s numbers are and are not, worked out from the file itself.
One year of the 2026 release
Every year in this series comes from ND-GAIN’s 2026 release, recalculated on one method. It can differ from what was first published for 2019.
The rank is ND-GAIN’s
Printed as the publisher ranked the countries; never re-ranked here.
Nothing missing
Every one of the 192 countries has every column.
05The files
Download and cite
The table as a file, digit for digit, what this site changed, and a citation for this edition.
- .csv
For a spreadsheet or code
192 rows · 8.1 KB · UTF-8, opens in Excel
Opens with 11 lines of source notes; the table starts on row 13.
Download climate-readiness-2019-nations-inquiry.csv - ↗
The publisher’s original
ND-GAIN’s own file, on its own site.
resources-2026-14-07-13h00.zip
What this site changed: Reshaped into one row per country: regional and income-group totals are left out, only the columns listed are kept, each row gets its ISO 3166 code, and some country names are brought to one spelling. No value is recalculated, rescaled or rounded.
Licence: CC BY 3.0 Unported · what it allows, in plain words
Cite this edition
Notre Dame Global Adaptation Initiative (ND-GAIN), University of Notre Dame (2019). Climate Readiness (ND-GAIN), 2019 [data set], describing 2019. As held by Nations Inquiry, https://nationsinquiry.com/datasets/climate-readiness/2019
0630 held
Other years
‹ The year before
Climate Readiness (ND-GAIN), 2018192 countries
The year after ›
Climate Readiness (ND-GAIN), 2020192 countries
All of them
Climate Readiness (ND-GAIN): every year30 held, with the data dictionary, coverage and licence.
How it has moved, charted by country
07Questions
Climate Readiness (ND-GAIN), 2019: questions and answers
Which country has the highest climate adaptation readiness in Climate Readiness (ND-GAIN), 2019?
Singapore, at 0.81126, of the 192 countries in the file.
What year does Climate Readiness (ND-GAIN), 2019 describe?
2019.
How many countries does Climate Readiness (ND-GAIN), 2019 cover?
192.
Where can I download Climate Readiness (ND-GAIN), 2019?
On this page, as a CSV file holding every value exactly as published, or from the publisher’s own site, linked below.
Is Climate Readiness (ND-GAIN), 2019 the newest?
No. The newest held here is Climate Readiness (ND-GAIN), 2024.